paper_id stringlengths 10 10 | paper_url stringlengths 37 80 | title stringlengths 4 518 | abstract stringlengths 3 7.27k | arxiv_id stringlengths 9 16 ⌀ | url_abs stringlengths 18 601 | url_pdf stringlengths 21 601 | aspect_tasks sequence | aspect_methods sequence | aspect_datasets sequence |
|---|---|---|---|---|---|---|---|---|---|
9gWe1QI8-1 | https://paperswithcode.com/paper/on-the-minimal-teaching-sets-of-two | On the minimal teaching sets of two-dimensional threshold functions | It is known that a minimal teaching set of any threshold function on the
twodimensional rectangular grid consists of 3 or 4 points. We derive exact
formulae for the numbers of functions corresponding to these values and further
refine them in the case of a minimal teaching set of size 3. We also prove that
the average ... | 1307.1058 | http://arxiv.org/abs/1307.1058v2 | http://arxiv.org/pdf/1307.1058v2.pdf | [] | [] | [] |
M1kGtE6A1m | https://paperswithcode.com/paper/gradient-boost-with-convolution-neural | Gradient Boost with Convolution Neural Network for Stock Forecast | Market economy closely connects aspects to all walks of life. The stock forecast is one of task among studies on the market economy. However, information on markets economy contains a lot of noise and uncertainties, which lead economy forecasting to become a challenging task. Ensemble learning and deep learning are the... | 1909.09563 | https://arxiv.org/abs/1909.09563v1 | https://arxiv.org/pdf/1909.09563v1.pdf | [] | [] | [] |
yusO5UR4MN | https://paperswithcode.com/paper/learning-data-manifolds-with-a-cutting-plane | Learning Data Manifolds with a Cutting Plane Method | We consider the problem of classifying data manifolds where each manifold
represents invariances that are parameterized by continuous degrees of freedom.
Conventional data augmentation methods rely upon sampling large numbers of
training examples from these manifolds; instead, we propose an iterative
algorithm called M... | 1705.09944 | http://arxiv.org/abs/1705.09944v1 | http://arxiv.org/pdf/1705.09944v1.pdf | [
"Data Augmentation"
] | [] | [] |
bsbiMfdWcf | https://paperswithcode.com/paper/guided-stereo-matching-1 | Guided Stereo Matching | Stereo is a prominent technique to infer dense depth maps from images, and deep learning further pushed forward the state-of-the-art, making end-to-end architectures unrivaled when enough data is available for training. However, deep networks suffer from significant drops in accuracy when dealing with new environments.... | 1905.10107 | https://arxiv.org/abs/1905.10107v1 | https://arxiv.org/pdf/1905.10107v1.pdf | [
"Stereo Matching",
"Stereo Matching Hand"
] | [] | [] |
_2ljQq7YEb | https://paperswithcode.com/paper/learning-physical-intuition-of-block-towers | Learning Physical Intuition of Block Towers by Example | Wooden blocks are a common toy for infants, allowing them to develop motor
skills and gain intuition about the physical behavior of the world. In this
paper, we explore the ability of deep feed-forward models to learn such
intuitive physics. Using a 3D game engine, we create small towers of wooden
blocks whose stabilit... | 1603.01312 | http://arxiv.org/abs/1603.01312v1 | http://arxiv.org/pdf/1603.01312v1.pdf | [] | [] | [] |
7HTdD4Wl8_ | https://paperswithcode.com/paper/audio-visual-olfactory-resource-allocation | Audio-Visual-Olfactory Resource Allocation for Tri-modal Virtual Environments | Virtual Environments (VEs) provide the opportunity to simulate a wide range of applications, from training to entertainment, in a safe and controlled manner. For applications which require realistic representations of real world environments, the VEs need to provide multiple, physically accurate sensory stimuli. Howeve... | 2002.02671 | https://arxiv.org/abs/2002.02671v1 | https://arxiv.org/pdf/2002.02671v1.pdf | [] | [] | [] |
xeJi-WhMmM | https://paperswithcode.com/paper/david-dual-attentional-video-deblurring | DAVID: Dual-Attentional Video Deblurring | Blind video deblurring restores sharp frames from a blurry sequence without any prior. It is a challenging task because the blur due to camera shake, object movement and defocusing is heterogeneous in both temporal and spatial dimensions. Traditional methods train on datasets synthesized with a single level of blur, an... | 1912.03445 | https://arxiv.org/abs/1912.03445v1 | https://arxiv.org/pdf/1912.03445v1.pdf | [
"Deblurring"
] | [] | [] |
MApq3NnxKg | https://paperswithcode.com/paper/adversarial-machine-learning-an | Adversarial Attacks and Defenses: An Interpretation Perspective | Despite the recent advances in a wide spectrum of applications, machine learning models, especially deep neural networks, have been shown to be vulnerable to adversarial attacks. Attackers add carefully-crafted perturbations to input, where the perturbations are almost imperceptible to humans, but can cause models to m... | 2004.11488 | https://arxiv.org/abs/2004.11488v2 | https://arxiv.org/pdf/2004.11488v2.pdf | [
"Adversarial Attack",
"Adversarial Defense",
"Interpretable Machine Learning"
] | [] | [] |
c9wMXjAWKi | https://paperswithcode.com/paper/headless-horseman-adversarial-attacks-on | Headless Horseman: Adversarial Attacks on Transfer Learning Models | Transfer learning facilitates the training of task-specific classifiers using pre-trained models as feature extractors. We present a family of transferable adversarial attacks against such classifiers, generated without access to the classification head; we call these \emph{headless attacks}. We first demonstrate succe... | 2004.09007 | https://arxiv.org/abs/2004.09007v1 | https://arxiv.org/pdf/2004.09007v1.pdf | [
"Adversarial Attack",
"Transfer Learning"
] | [] | [] |
l-E3TWSB2x | https://paperswithcode.com/paper/on-the-performance-of-a-canonical-labeling | Analysis of a Canonical Labeling Algorithm for the Alignment of Correlated Erdős-Rényi Graphs | Graph alignment in two correlated random graphs refers to the task of identifying the correspondence between vertex sets of the graphs. Recent results have characterized the exact information-theoretic threshold for graph alignment in correlated Erd\H{o}s-R\'enyi graphs. However, very little is known about the existenc... | 1804.09758 | https://arxiv.org/abs/1804.09758v2 | https://arxiv.org/pdf/1804.09758v2.pdf | [
"Graph Matching"
] | [] | [] |
gW-cPCmFMj | https://paperswithcode.com/paper/a-privacy-preserving-dnn-pruning-and-mobile | A Privacy-Preserving-Oriented DNN Pruning and Mobile Acceleration Framework | Weight pruning of deep neural networks (DNNs) has been proposed to satisfy the limited storage and computing capability of mobile edge devices. However, previous pruning methods mainly focus on reducing the model size and/or improving performance without considering the privacy of user data. To mitigate this concern, w... | 2003.06513 | https://arxiv.org/abs/2003.06513v2 | https://arxiv.org/pdf/2003.06513v2.pdf | [
"Model Compression"
] | [
"ADMM"
] | [] |
DRh5XlkOBI | https://paperswithcode.com/paper/an-alternative-cross-entropy-loss-for | An Alternative Cross Entropy Loss for Learning-to-Rank | Listwise learning-to-rank methods form a powerful class of ranking algorithms that are widely adopted in applications such as information retrieval. These algorithms learn to rank a set of items by optimizing a loss that is a function of the entire set---as a surrogate to a typically non-differentiable ranking metric. ... | 1911.09798 | https://arxiv.org/abs/1911.09798v4 | https://arxiv.org/pdf/1911.09798v4.pdf | [
"Information Retrieval",
"Learning-To-Rank"
] | [] | [] |
-sSCd2zCEx | https://paperswithcode.com/paper/coercive-functions-from-a-topological | Coercive functions from a topological viewpoint and properties of minimizing sets of convex functions appearing in image restoration | Many tasks in image processing can be tackled by modeling an appropriate data
fidelity term $\Phi: \mathbb{R}^n \rightarrow \mathbb{R} \cup \{+\infty\}$ and
then solve one of the regularized minimization problems \begin{align*}
&{}(P_{1,\tau}) \qquad \mathop{\rm argmin}_{x \in \mathbb R^n} \big\{ \Phi(x)
\;{\rm s.t.}... | 1506.08615 | http://arxiv.org/abs/1506.08615v1 | http://arxiv.org/pdf/1506.08615v1.pdf | [
"Image Restoration"
] | [] | [] |
w54mOkXDrR | https://paperswithcode.com/paper/reasoning-about-human-object-interactions | Reasoning About Human-Object Interactions Through Dual Attention Networks | Objects are entities we act upon, where the functionality of an object is determined by how we interact with it. In this work we propose a Dual Attention Network model which reasons about human-object interactions. The dual-attentional framework weights the important features for objects and actions respectively. As a ... | 1909.04743 | https://arxiv.org/abs/1909.04743v1 | https://arxiv.org/pdf/1909.04743v1.pdf | [
"Human-Object Interaction Detection"
] | [] | [] |
Hitgt7mynu | https://paperswithcode.com/paper/the-practicality-of-stochastic-optimization | The Practicality of Stochastic Optimization in Imaging Inverse Problems | In this work we investigate the practicality of stochastic gradient descent and recently introduced variants with variance-reduction techniques in imaging inverse problems. Such algorithms have been shown in the machine learning literature to have optimal complexities in theory, and provide great improvement empiricall... | 1910.10100 | https://arxiv.org/abs/1910.10100v2 | https://arxiv.org/pdf/1910.10100v2.pdf | [
"Deblurring",
"Stochastic Optimization"
] | [
"SGD"
] | [] |
1wfEKvtXlg | https://paperswithcode.com/paper/personrank-detecting-important-people-in | PersonRank: Detecting Important People in Images | Always, some individuals in images are more important/attractive than others
in some events such as presentation, basketball game or speech. However, it is
challenging to find important people among all individuals in images directly
based on their spatial or appearance information due to the existence of
diverse varia... | 1711.01984 | http://arxiv.org/abs/1711.01984v1 | http://arxiv.org/pdf/1711.01984v1.pdf | [] | [] | [] |
5PT8XF_ubk | https://paperswithcode.com/paper/rain-code-forecasting-spatiotemporal | Rain Code: Multi-Frame Based Forecasting Spatiotemporal Precipitation Using ConvLSTM | Recently, flood damage has become a social problem owing to unexperienced weather conditions arising from climate change. An immediate response to heavy rain and high water levels is important for the mitigation of casualties and economic losses and also for rapid recovery. Spatiotemporal precipitation forecasts may en... | 2009.14573 | https://arxiv.org/abs/2009.14573v4 | https://arxiv.org/pdf/2009.14573v4.pdf | [] | [
"Sigmoid Activation",
"Convolution",
"Tanh Activation",
"ConvLSTM"
] | [] |
ZHTGFi4qnT | https://paperswithcode.com/paper/educe-explaining-model-decisions-through | EDUCE: Explaining model Decisions through Unsupervised Concepts Extraction | Providing explanations along with predictions is crucial in some text processing tasks. Therefore, we propose a new self-interpretable model that performs output prediction and simultaneously provides an explanation in terms of the presence of particular concepts in the input. To do so, our model's prediction relies so... | 1905.11852 | https://arxiv.org/abs/1905.11852v2 | https://arxiv.org/pdf/1905.11852v2.pdf | [
"Sentiment Analysis",
"Text Classification"
] | [] | [] |
mKNlGtMien | https://paperswithcode.com/paper/computed-tomography-image-enhancement-using | Computed Tomography Image Enhancement using 3D Convolutional Neural Network | Computed tomography (CT) is increasingly being used for cancer screening,
such as early detection of lung cancer. However, CT studies have varying pixel
spacing due to differences in acquisition parameters. Thick slice CTs have
lower resolution, hindering tasks such as nodule characterization during
computer-aided dete... | 1807.06821 | http://arxiv.org/abs/1807.06821v1 | http://arxiv.org/pdf/1807.06821v1.pdf | [
"Computed Tomography (CT)",
"Image Enhancement",
"SSIM"
] | [] | [] |
Fc7B0QREM- | https://paperswithcode.com/paper/finite-time-analysis-of-stochastic-gradient | Finite-Time Analysis of Stochastic Gradient Descent under Markov Randomness | Motivated by broad applications in reinforcement learning and machine learning, this paper considers the popular stochastic gradient descent (SGD) when the gradients of the underlying objective function are sampled from Markov processes. This Markov sampling leads to the gradient samples being biased and not independen... | 2003.10973 | https://arxiv.org/abs/2003.10973v2 | https://arxiv.org/pdf/2003.10973v2.pdf | [] | [
"SGD"
] | [] |
Sd4BJb4o3L | https://paperswithcode.com/paper/video-rainsnow-removal-by-transformed-online | Video Rain/Snow Removal by Transformed Online Multiscale Convolutional Sparse Coding | Video rain/snow removal from surveillance videos is an important task in the computer vision community since rain/snow existed in videos can severely degenerate the performance of many surveillance system. Various methods have been investigated extensively, but most only consider consistent rain/snow under stable backg... | 1909.06148 | https://arxiv.org/abs/1909.06148v1 | https://arxiv.org/pdf/1909.06148v1.pdf | [] | [
"ADMM"
] | [] |
lIG1ZLJY12 | https://paperswithcode.com/paper/towards-generalizable-neuro-symbolic-systems | Towards Generalizable Neuro-Symbolic Systems for Commonsense Question Answering | Non-extractive commonsense QA remains a challenging AI task, as it requires systems to reason about, synthesize, and gather disparate pieces of information, in order to generate responses to queries. Recent approaches on such tasks show increased performance, only when models are either pre-trained with additional info... | 1910.14087 | https://arxiv.org/abs/1910.14087v1 | https://arxiv.org/pdf/1910.14087v1.pdf | [
"Question Answering"
] | [] | [] |
CV9ag41Hh2 | https://paperswithcode.com/paper/visualizing-group-dynamics-based-on | Visualizing Group Dynamics based on Multiparty Meeting Understanding | Group discussions are usually aimed at sharing opinions, reaching consensus and making good decisions based on group knowledge. During a discussion, participants might adjust their own opinions as well as tune their attitudes towards others{'} opinions, based on the unfolding interactions. In this paper, we demonstrate... | null | https://www.aclweb.org/anthology/D18-2017/ | https://www.aclweb.org/anthology/D18-2017 | [
"Decision Making",
"Opinion Mining",
"Speech Recognition"
] | [] | [] |
Awl7-xmHGl | https://paperswithcode.com/paper/reconstructing-the-world-in-six-days-as | Reconstructing the World* in Six Days *(As Captured by the Yahoo 100 Million Image Dataset) | We propose a novel, large-scale, structure-from-motion framework that advances the state of the art in data scalability from city-scale modeling (millions of images) to world-scale modeling (several tens of millions of images) using just a single computer. The main enabling technology is the use of a streaming-based fr... | null | http://openaccess.thecvf.com/content_cvpr_2015/html/Heinly_Reconstructing_the_World_2015_CVPR_paper.html | http://openaccess.thecvf.com/content_cvpr_2015/papers/Heinly_Reconstructing_the_World_2015_CVPR_paper.pdf | [
"Image Clustering"
] | [] | [] |
--FwyMzdrd | https://paperswithcode.com/paper/is-a-data-driven-approach-still-better-than | Is a Data-Driven Approach still Better than Random Choice with Naive Bayes classifiers? | We study the performance of data-driven, a priori and random approaches to
label space partitioning for multi-label classification with a Gaussian Naive
Bayes classifier. Experiments were performed on 12 benchmark data sets and
evaluated on 5 established measures of classification quality: micro and macro
averaged F1 s... | 1702.04013 | http://arxiv.org/abs/1702.04013v1 | http://arxiv.org/pdf/1702.04013v1.pdf | [
"Multi-Label Classification"
] | [] | [] |
93YLlz8KjX | https://paperswithcode.com/paper/multi-scale-structure-aware-network-for-human | Multi-Scale Structure-Aware Network for Human Pose Estimation | We develop a robust multi-scale structure-aware neural network for human pose
estimation. This method improves the recent deep conv-deconv hourglass models
with four key improvements: (1) multi-scale supervision to strengthen
contextual feature learning in matching body keypoints by combining feature
heatmaps across sc... | 1803.09894 | http://arxiv.org/abs/1803.09894v3 | http://arxiv.org/pdf/1803.09894v3.pdf | [
"Pose Estimation"
] | [] | [
"MPII Human Pose"
] |
5M1BetUzB8 | https://paperswithcode.com/paper/incorporating-pragmatic-reasoning | Incorporating Pragmatic Reasoning Communication into Emergent Language | Emergentism and pragmatics are two research fields that study the dynamics of linguistic communication along substantially different timescales and intelligence levels. From the perspective of multi-agent reinforcement learning, they correspond to stochastic games with reinforcement training and stage games with oppone... | 2006.04109 | https://arxiv.org/abs/2006.04109v1 | https://arxiv.org/pdf/2006.04109v1.pdf | [
"Multi-agent Reinforcement Learning",
"Starcraft",
"Starcraft II"
] | [] | [] |
ULXkCXfnf7 | https://paperswithcode.com/paper/two-phase-object-based-deep-learning-for | Two-Phase Object-Based Deep Learning for Multi-temporal SAR Image Change Detection | Change detection is one of the fundamental applications of synthetic aperture radar (SAR) images. However, speckle noise presented in SAR images has a much negative effect on change detection. In this research, a novel two-phase object-based deep learning approach is proposed for multi-temporal SAR image change detecti... | 2001.06252 | https://arxiv.org/abs/2001.06252v1 | https://arxiv.org/pdf/2001.06252v1.pdf | [] | [] | [] |
Qh7EgPiJFX | https://paperswithcode.com/paper/calibrated-surrogate-losses-for-adversarially | Calibrated Surrogate Losses for Adversarially Robust Classification | Adversarially robust classification seeks a classifier that is insensitive to adversarial perturbations of test patterns. This problem is often formulated via a minimax objective, where the target loss is the worst-case value of the 0-1 loss subject to a bound on the size of perturbation. Recent work has proposed conve... | 2005.13748 | https://arxiv.org/abs/2005.13748v1 | https://arxiv.org/pdf/2005.13748v1.pdf | [] | [] | [] |
Rj85mABmSX | https://paperswithcode.com/paper/deep-learning-for-plasma-tomography-using-the | Deep learning for plasma tomography using the bolometer system at JET | Deep learning is having a profound impact in many fields, especially those
that involve some form of image processing. Deep neural networks excel in
turning an input image into a set of high-level features. On the other hand,
tomography deals with the inverse problem of recreating an image from a number
of projections.... | 1701.00322 | http://arxiv.org/abs/1701.00322v1 | http://arxiv.org/pdf/1701.00322v1.pdf | [] | [] | [] |
NJSwt5K8ru | https://paperswithcode.com/paper/a-multiple-radar-approach-for-automatic | A Multiple Radar Approach for Automatic Target Recognition of Aircraft using Inverse Synthetic Aperture Radar | Along with the improvement of radar technologies, Automatic Target
Recognition (ATR) using Synthetic Aperture Radar (SAR) and Inverse SAR (ISAR)
has come to be an active research area. SAR/ISAR are radar techniques to
generate a two-dimensional high-resolution image of a target. Unlike other
similar experiments using C... | 1711.04901 | http://arxiv.org/abs/1711.04901v2 | http://arxiv.org/pdf/1711.04901v2.pdf | [] | [] | [] |
5bRPe2qvaY | https://paperswithcode.com/paper/deep-learning-based-anticipatory-multi | Deep Learning Based Anticipatory Multi-Objective Eco-Routing Strategies for Connected and Automated Vehicles | This study exploits the advancements in information and communication technology (ICT), connected and automated vehicles (CAVs), and sensing, to develop anticipatory multi-objective eco-routing strategies. For a robust application, several GHG costing approaches are examined. The predictive models for the link level tr... | 2006.16472 | https://arxiv.org/abs/2006.16472v1 | https://arxiv.org/pdf/2006.16472v1.pdf | [] | [] | [] |
jtdhhVlMeC | https://paperswithcode.com/paper/stylometric-analysis-of-parliamentary | Stylometric Analysis of Parliamentary Speeches: Gender Dimension | Relation between gender and language has been studied by many authors, however, there is still some uncertainty left regarding gender influence on language usage in the professional environment. Often, the studied data sets are too small or texts of individual authors are too short in order to capture differences of la... | null | https://www.aclweb.org/anthology/W17-1416/ | https://www.aclweb.org/anthology/W17-1416 | [] | [] | [] |
nhS3mL86_h | https://paperswithcode.com/paper/modeling-electromagnetic-navigation-systems | Modeling Electromagnetic Navigation Systems for Medical Applications using Random Forests and Artificial Neural Networks | Electromagnetic Navigation Systems (eMNS) can be used to control a variety of multiscale devices within the human body for remote surgery. Accurate modeling of the magnetic fields generated by the electromagnets of an eMNS is crucial for the precise control of these devices. Existing methods assume a linear behavior of... | 1909.12028 | https://arxiv.org/abs/1909.12028v1 | https://arxiv.org/pdf/1909.12028v1.pdf | [] | [] | [] |
VHHEFloBeg | https://paperswithcode.com/paper/non-parametric-bayesian-modeling-of-complex | Non-parametric Bayesian modeling of complex networks | Modeling structure in complex networks using Bayesian non-parametrics makes
it possible to specify flexible model structures and infer the adequate model
complexity from the observed data. This paper provides a gentle introduction to
non-parametric Bayesian modeling of complex networks: Using an infinite mixture
model ... | 1312.5889 | http://arxiv.org/abs/1312.5889v1 | http://arxiv.org/pdf/1312.5889v1.pdf | [] | [] | [] |
Jd_Ceu_dSP | https://paperswithcode.com/paper/ordered-tree-decomposition-for-hrg-rule | Ordered Tree Decomposition for HRG Rule Extraction | We present algorithms for extracting Hyperedge Replacement Grammar (HRG) rules from a graph along with a vertex order. Our algorithms are based on finding a tree decomposition of smallest width, relative to the vertex order, and then extracting one rule for each node in this structure. The assumption of a fixed order f... | null | https://www.aclweb.org/anthology/J19-2005/ | https://www.aclweb.org/anthology/J19-2005 | [] | [] | [] |
XHAoZ20bJ7 | https://paperswithcode.com/paper/enhancing-the-robustness-of-deep-neural | Enhancing the Robustness of Deep Neural Networks by Boundary Conditional GAN | Deep neural networks have been widely deployed in various machine learning
tasks. However, recent works have demonstrated that they are vulnerable to
adversarial examples: carefully crafted small perturbations to cause
misclassification by the network. In this work, we propose a novel defense
mechanism called Boundary ... | 1902.11029 | http://arxiv.org/abs/1902.11029v1 | http://arxiv.org/pdf/1902.11029v1.pdf | [
"Data Augmentation"
] | [
"Convolution",
"GAN"
] | [] |
seqTST7IOd | https://paperswithcode.com/paper/a-classification-point-of-view-about | A classification point-of-view about conditional Kendall's tau | We show how the problem of estimating conditional Kendall's tau can be
rewritten as a classification task. Conditional Kendall's tau is a conditional
dependence parameter that is a characteristic of a given pair of random
variables. The goal is to predict whether the pair is concordant (value of $1$)
or discordant (val... | 1806.09048 | http://arxiv.org/abs/1806.09048v3 | http://arxiv.org/pdf/1806.09048v3.pdf | [] | [] | [] |
5dOopSyS6U | https://paperswithcode.com/paper/measuring-human-perception-to-improve | Measuring Human Perception to Improve Handwritten Document Transcription | The subtleties of human perception, as measured by vision scientists through the use of psychophysics, are important clues to the internal workings of visual recognition. For instance, measured reaction time can indicate whether a visual stimulus is easy for a subject to recognize, or whether it is hard. In this paper,... | 1904.03734 | https://arxiv.org/abs/1904.03734v4 | https://arxiv.org/pdf/1904.03734v4.pdf | [] | [] | [] |
79KLqw-hbC | https://paperswithcode.com/paper/a-unified-framework-for-lifelong-learning-in | A Conceptual Framework for Lifelong Learning | Humans can learn a variety of concepts and skills incrementally over the course of their lives while exhibiting many desirable properties, such as continual learning without forgetting, forward transfer and backward transfer of knowledge, and learning a new concept or task with only a few examples. Several lines of mac... | 1911.09704 | https://arxiv.org/abs/1911.09704v4 | https://arxiv.org/pdf/1911.09704v4.pdf | [
"Continual Learning",
"Few-Shot Learning",
"Multi-Task Learning",
"Transfer Learning"
] | [] | [] |
kIMUgDxbiQ | https://paperswithcode.com/paper/conditional-sparse-linear-regression | Conditional Sparse Linear Regression | Machine learning and statistics typically focus on building models that
capture the vast majority of the data, possibly ignoring a small subset of data
as "noise" or "outliers." By contrast, here we consider the problem of jointly
identifying a significant (but perhaps small) segment of a population in which
there is a... | 1608.05152 | http://arxiv.org/abs/1608.05152v1 | http://arxiv.org/pdf/1608.05152v1.pdf | [] | [
"Linear Regression"
] | [] |
slMLk236o8 | https://paperswithcode.com/paper/investigating-task-driven-latent-feasibility | Investigating Task-driven Latent Feasibility for Nonconvex Image Modeling | Properly modeling latent image distributions plays an important role in a variety of image-related vision problems. Most exiting approaches aim to formulate this problem as optimization models (e.g., Maximum A Posterior, MAP) with handcrafted priors. In recent years, different CNN modules are also considered as deep pr... | 1910.08242 | https://arxiv.org/abs/1910.08242v3 | https://arxiv.org/pdf/1910.08242v3.pdf | [
"Deblurring"
] | [] | [] |
cQPubv4dPD | https://paperswithcode.com/paper/serialrank-spectral-ranking-using-seriation | SerialRank: Spectral Ranking using Seriation | We describe a seriation algorithm for ranking a set of n items given pairwise comparisons between these items. Intuitively, the algorithm assigns similar rankings to items that compare similarly with all others. It does so by constructing a similarity matrix from pairwise comparisons, using seriation methods to reorder... | null | http://papers.nips.cc/paper/5223-serialrank-spectral-ranking-using-seriation | http://papers.nips.cc/paper/5223-serialrank-spectral-ranking-using-seriation.pdf | [] | [] | [] |
HI3g66v63s | https://paperswithcode.com/paper/assessing-the-quality-of-scientific-papers | Assessing the Quality of Scientific Papers | A multitude of factors are responsible for the overall quality of scientific papers, including readability, linguistic quality, fluency,semantic complexity, and of course domain-specific technical factors. These factors vary from one field of study to another. In this paper, we propose a measure and method for assessin... | 1908.04200 | https://arxiv.org/abs/1908.04200v1 | https://arxiv.org/pdf/1908.04200v1.pdf | [] | [] | [] |
B3MUkQzXiv | https://paperswithcode.com/paper/multi-scale-fcn-with-cascaded-instance-aware | Multi-Scale FCN With Cascaded Instance Aware Segmentation for Arbitrary Oriented Word Spotting in the Wild | Scene text detection has attracted great attention these years. Text potentially exist in a wide variety of images or videos and play an important role in understanding the scene. In this paper, we present a novel text detection algorithm which is composed of two cascaded steps: (1) a multi-scale fully convolutio... | null | http://openaccess.thecvf.com/content_cvpr_2017/html/He_Multi-Scale_FCN_With_CVPR_2017_paper.html | http://openaccess.thecvf.com/content_cvpr_2017/papers/He_Multi-Scale_FCN_With_CVPR_2017_paper.pdf | [
"Scene Text",
"Scene Text Detection"
] | [
"LINE"
] | [] |
QtaBAsUcXi | https://paperswithcode.com/paper/lrcn-retailnet-a-recurrent-neural-network | LRCN-RetailNet: A recurrent neural network architecture for accurate people counting | Measuring and analyzing the flow of customers in retail stores is essential for a retailer to better comprehend customers' behavior and support decision-making. Nevertheless, not much attention has been given to the development of novel technologies for automatic people counting. We introduce LRCN-RetailNet: a recurren... | 2004.09672 | https://arxiv.org/abs/2004.09672v2 | https://arxiv.org/pdf/2004.09672v2.pdf | [
"Decision Making",
"Object Detection"
] | [] | [] |
zLE0kUDaml | https://paperswithcode.com/paper/intervention-harvesting-for-context-dependent | Intervention Harvesting for Context-Dependent Examination-Bias Estimation | Accurate estimates of examination bias are crucial for unbiased learning-to-rank from implicit feedback in search engines and recommender systems, since they enable the use of Inverse Propensity Score (IPS) weighting techniques to address selection biases and missing data. Unfortunately, existing examination-bias estim... | 1811.01802 | https://arxiv.org/abs/1811.01802v3 | https://arxiv.org/pdf/1811.01802v3.pdf | [
"Learning-To-Rank",
"Recommendation Systems"
] | [] | [] |
npwvy5DOXX | https://paperswithcode.com/paper/powerful-transferable-representations-for | Powerful, transferable representations for molecules through intelligent task selection in deep multitask networks | Chemical representations derived from deep learning are emerging as a
powerful tool in areas such as drug discovery and materials innovation.
Currently, this methodology has three major limitations - the cost of
representation generation, risk of inherited bias, and the requirement for
large amounts of data. We propose... | 1809.06334 | http://arxiv.org/abs/1809.06334v1 | http://arxiv.org/pdf/1809.06334v1.pdf | [
"Drug Discovery",
"Multi-Task Learning",
"Transfer Learning"
] | [] | [] |
TeWWKlmaFv | https://paperswithcode.com/paper/using-machine-learning-to-develop-a-novel | Using Machine Learning to Develop a Novel COVID-19 Vulnerability Index (C19VI) | COVID19 is now one of the most leading causes of death in the United States. Systemic health, social and economic disparities have put the minorities and economically poor communities at a higher risk than others. There is an immediate requirement to develop a reliable measure of county-level vulnerabilities that can c... | 2009.10808 | https://arxiv.org/abs/2009.10808v1 | https://arxiv.org/pdf/2009.10808v1.pdf | [] | [] | [] |
_12LRw1xc3 | https://paperswithcode.com/paper/effective-cloud-detection-and-segmentation | Effective Cloud Detection and Segmentation using a Gradient-Based Algorithm for Satellite Imagery; Application to improve PERSIANN-CCS | Being able to effectively identify clouds and monitor their evolution is one
important step toward more accurate quantitative precipitation estimation and
forecast. In this study, a new gradient-based cloud-image segmentation
technique is developed using tools from image processing techniques. This
method integrates mo... | 1809.10801 | http://arxiv.org/abs/1809.10801v1 | http://arxiv.org/pdf/1809.10801v1.pdf | [
"Cloud Detection",
"Semantic Segmentation"
] | [] | [] |
dsuv7boVNM | https://paperswithcode.com/paper/how-to-organize-your-deep-reinforcement | How to Organize your Deep Reinforcement Learning Agents: The Importance of Communication Topology | In this empirical paper, we investigate how learning agents can be arranged
in more efficient communication topologies for improved learning. This is an
important problem because a common technique to improve speed and robustness of
learning in deep reinforcement learning and many other machine learning
algorithms is t... | 1811.12556 | http://arxiv.org/abs/1811.12556v2 | http://arxiv.org/pdf/1811.12556v2.pdf | [] | [] | [] |
KwXhL56cMl | https://paperswithcode.com/paper/binary-to-bushy-bayesian-hierarchical | Binary to Bushy: Bayesian Hierarchical Clustering with the Beta Coalescent | Discovering hierarchical regularities in data is a key problem in interacting with large datasets, modeling cognition, and encoding knowledge. A previous Bayesian solution---Kingman's coalescent---provides a convenient probabilistic model for data represented as a binary tree. Unfortunately, this is inappropria... | null | http://papers.nips.cc/paper/5161-binary-to-bushy-bayesian-hierarchical-clustering-with-the-beta-coalescent | http://papers.nips.cc/paper/5161-binary-to-bushy-bayesian-hierarchical-clustering-with-the-beta-coalescent.pdf | [] | [] | [] |
kgUCdfW3y2 | https://paperswithcode.com/paper/tfw-damngina-juvie-and-hotsie-totsie-on-the | TFW, DamnGina, Juvie, and Hotsie-Totsie: On the Linguistic and Social Aspects of Internet Slang | Slang is ubiquitous on the Internet. The emergence of new social contexts
like micro-blogs, question-answering forums, and social networks has enabled
slang and non-standard expressions to abound on the web. Despite this, slang
has been traditionally viewed as a form of non-standard language -- a form of
language that ... | 1712.08291 | http://arxiv.org/abs/1712.08291v1 | http://arxiv.org/pdf/1712.08291v1.pdf | [
"Question Answering"
] | [] | [] |
jIubXJAqsv | https://paperswithcode.com/paper/graph-representation-for-face-analysis-in | Graph Representation for Face Analysis in Image Collections | Given an image collection of a social event with a huge number of pictures, it is very useful to have tools that can be used to analyze how the individuals --that are present in the collection-- interact with each other. In this paper, we propose an optimal graph representation that is based on the `connectivity' of th... | 1911.11970 | https://arxiv.org/abs/1911.11970v1 | https://arxiv.org/pdf/1911.11970v1.pdf | [] | [] | [] |
Ygz6wiZA5w | https://paperswithcode.com/paper/interpretable-sequence-classification-via-1 | Interpretable Sequence Classification via Discrete Optimization | Sequence classification is the task of predicting a class label given a sequence of observations. In many applications such as healthcare monitoring or intrusion detection, early classification is crucial to prompt intervention. In this work, we learn sequence classifiers that favour early classification from an evolvi... | 2010.02819 | https://arxiv.org/abs/2010.02819v1 | https://arxiv.org/pdf/2010.02819v1.pdf | [
"Intrusion Detection"
] | [] | [] |
fWZS9WcF6H | https://paperswithcode.com/paper/geometrical-morphology | Geometrical morphology | We explore inflectional morphology as an example of the relationship of the
discrete and the continuous in linguistics. The grammar requests a form of a
lexeme by specifying a set of feature values, which corresponds to a corner M
of a hypercube in feature value space. The morphology responds to that request
by providi... | 1703.04481 | http://arxiv.org/abs/1703.04481v1 | http://arxiv.org/pdf/1703.04481v1.pdf | [] | [] | [] |
fknxeYWN8R | https://paperswithcode.com/paper/team-kermit-the-frog-at-semeval-2019-task-4 | Team Kermit-the-frog at SemEval-2019 Task 4: Bias Detection Through Sentiment Analysis and Simple Linguistic Features | In this paper we describe our participation in the SemEval 2019 shared task on hyperpartisan news detection. We present the system that we submitted for final evaluation and the three approaches that we used: sentiment, bias-laden words and filtered n-gram features. Our submitted model is a Linear SVM that solely relie... | null | https://www.aclweb.org/anthology/S19-2177/ | https://www.aclweb.org/anthology/S19-2177 | [
"Bias Detection",
"Sentiment Analysis"
] | [
"SVM"
] | [] |
P6UNsMG0OI | https://paperswithcode.com/paper/geometrization-of-deep-networks-for-the | Geometrization of deep networks for the interpretability of deep learning systems | How to understand deep learning systems remains an open problem. In this
paper we propose that the answer may lie in the geometrization of deep
networks. Geometrization is a bridge to connect physics, geometry, deep network
and quantum computation and this may result in a new scheme to reveal the rule
of the physical w... | 1901.02354 | http://arxiv.org/abs/1901.02354v2 | http://arxiv.org/pdf/1901.02354v2.pdf | [] | [] | [] |
wFoeR5Qbrq | https://paperswithcode.com/paper/semantics-modelling-and-the-problem-of | Semantics, Modelling, and the Problem of Representation of Meaning -- a Brief Survey of Recent Literature | Over the past 50 years many have debated what representation should be used
to capture the meaning of natural language utterances. Recently new needs of
such representations have been raised in research. Here I survey some of the
interesting representations suggested to answer for these new needs. | 1402.7265 | http://arxiv.org/abs/1402.7265v1 | http://arxiv.org/pdf/1402.7265v1.pdf | [] | [] | [] |
V9yaFJy03j | https://paperswithcode.com/paper/data-augmentation-for-low-resource-sentiment | Data augmentation for low resource sentiment analysis using generative adversarial networks | Sentiment analysis is a task that may suffer from a lack of data in certain
cases, as the datasets are often generated and annotated by humans. In cases
where data is inadequate for training discriminative models, generate models
may aid training via data augmentation. Generative Adversarial Networks (GANs)
are one suc... | 1902.06818 | http://arxiv.org/abs/1902.06818v1 | http://arxiv.org/pdf/1902.06818v1.pdf | [
"Data Augmentation",
"Sentiment Analysis",
"Text Generation"
] | [
"Convolution",
"GAN"
] | [] |
ZU8mltEoIW | https://paperswithcode.com/paper/deep-quality-a-deep-no-reference-quality | Deep Quality: A Deep No-reference Quality Assessment System | Image quality assessment (IQA) continues to garner great interest in the
research community, particularly given the tremendous rise in consumer video
capture and streaming. Despite significant research effort in IQA in the past
few decades, the area of no-reference image quality assessment remains a great
challenge and... | 1609.07170 | http://arxiv.org/abs/1609.07170v1 | http://arxiv.org/pdf/1609.07170v1.pdf | [
"Image Quality Assessment",
"No-Reference Image Quality Assessment"
] | [] | [] |
Wn3weo5FHg | https://paperswithcode.com/paper/unconstrained-motion-deblurring-for-dual-lens | Unconstrained Motion Deblurring for Dual-Lens Cameras | Recently, there has been a renewed interest in leveraging multiple cameras, but under unconstrained settings. They have been quite successfully deployed in smartphones, which have become de facto choice for many photographic applications. However, akin to normal cameras, the functionality of multi-camera systems can be... | null | http://openaccess.thecvf.com/content_ICCV_2019/html/Mohan_Unconstrained_Motion_Deblurring_for_Dual-Lens_Cameras_ICCV_2019_paper.html | http://openaccess.thecvf.com/content_ICCV_2019/papers/Mohan_Unconstrained_Motion_Deblurring_for_Dual-Lens_Cameras_ICCV_2019_paper.pdf | [
"Deblurring"
] | [] | [] |
2r9t-QH2rM | https://paperswithcode.com/paper/feature-selection-and-extraction-for-graph | Feature Selection and Extraction for Graph Neural Networks | Graph Neural Networks (GNNs) have been a latest hot research topic in data science, due to the fact that they use the ubiquitous data structure graphs as the underlying elements for constructing and training neural networks. In a GNN, each node has numerous features associated with it. The entire task (for example, cla... | 1910.10682 | https://arxiv.org/abs/1910.10682v2 | https://arxiv.org/pdf/1910.10682v2.pdf | [
"Feature Selection"
] | [
"Gumbel Softmax",
"Softmax"
] | [] |
kLwD13kEUV | https://paperswithcode.com/paper/evaluating-and-rewarding-teamwork-using | Evaluating and Rewarding Teamwork Using Cooperative Game Abstractions | Can we predict how well a team of individuals will perform together? How should individuals be rewarded for their contributions to the team performance? Cooperative game theory gives us a powerful set of tools for answering these questions: the Characteristic Function (CF) and solution concepts like the Shapley Value (... | 2006.09538 | https://arxiv.org/abs/2006.09538v1 | https://arxiv.org/pdf/2006.09538v1.pdf | [] | [] | [] |
wlo-DHOrBy | https://paperswithcode.com/paper/driver-distraction-detection-and-recognition | Driver distraction detection and recognition using RGB-D sensor | Driver inattention assessment has become a very active field in intelligent
transportation systems. Based on active sensor Kinect and computer vision
tools, we have built an efficient module for detecting driver distraction and
recognizing the type of distraction. Based on color and depth map data from the
Kinect, our ... | 1502.00250 | http://arxiv.org/abs/1502.00250v1 | http://arxiv.org/pdf/1502.00250v1.pdf | [] | [] | [] |
srh3Rn440W | https://paperswithcode.com/paper/similarity-based-approach-for-outlier | Similarity- based approach for outlier detection | This paper presents a new approach for detecting outliers by introducing the
notion of object's proximity. The main idea is that normal point has similar
characteristics with several neighbors. So the point in not an outlier if it
has a high degree of proximity and its neighbors are several. The performance
of this app... | 1411.6850 | http://arxiv.org/abs/1411.6850v1 | http://arxiv.org/pdf/1411.6850v1.pdf | [
"Outlier Detection"
] | [] | [] |
uEilrQvvgG | https://paperswithcode.com/paper/f2a2-flexible-fully-decentralized-approximate | F2A2: Flexible Fully-decentralized Approximate Actor-critic for Cooperative Multi-agent Reinforcement Learning | Traditional centralized multi-agent reinforcement learning (MARL) algorithms are sometimes unpractical in complicated applications, due to non-interactivity between agents, curse of dimensionality and computation complexity. Hence, several decentralized MARL algorithms are motivated. However, existing decentralized met... | 2004.11145 | https://arxiv.org/abs/2004.11145v1 | https://arxiv.org/pdf/2004.11145v1.pdf | [
"Multi-agent Reinforcement Learning",
"Starcraft",
"Starcraft II"
] | [] | [] |
74-q0S9hCt | https://paperswithcode.com/paper/an-analysis-of-sketched-irls-for-accelerated | An Analysis of Sketched IRLS for Accelerated Sparse Residual Regression | This paper studies the problem of sparse residual regression, i.e., learning a linear model using a norm that favors solutions in which the residuals are sparsely distributed. This is a common problem in a wide range of computer vision applications where a linear system has a lot more equations than unknowns and we wis... | null | https://www.ecva.net/papers/eccv_2020/papers_ECCV/html/1659_ECCV_2020_paper.php | https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123570596.pdf | [] | [] | [] |
NMj-9kFeBs | https://paperswithcode.com/paper/pose-estimation-for-non-cooperative-1 | Pose Estimation for Non-Cooperative Rendezvous Using Neural Networks | This work introduces the Spacecraft Pose Network (SPN) for on-board estimation of the pose, i.e., the relative position and attitude, of a known non-cooperative spacecraft using monocular vision. In contrast to other state-of-the-art pose estimation approaches for spaceborne applications, the SPN method does not requir... | 1906.09868 | https://arxiv.org/abs/1906.09868v1 | https://arxiv.org/pdf/1906.09868v1.pdf | [
"Pose Estimation",
"Spacecraft Pose Estimation"
] | [] | [] |
x8JaXUtzLu | https://paperswithcode.com/paper/neural-odes-with-stochastic-vector-field | Neural ODEs with stochastic vector field mixtures | It was recently shown that neural ordinary differential equation models cannot solve fundamental and seemingly straightforward tasks even with high-capacity vector field representations. This paper introduces two other fundamental tasks to the set that baseline methods cannot solve, and proposes mixtures of stochastic ... | 1905.09905 | https://arxiv.org/abs/1905.09905v1 | https://arxiv.org/pdf/1905.09905v1.pdf | [] | [] | [] |
-oxBRhZuaE | https://paperswithcode.com/paper/a-narration-based-reward-shaping-approach | A Narration-based Reward Shaping Approach using Grounded Natural Language Commands | While deep reinforcement learning techniques have led to agents that are successfully able to learn to perform a number of tasks that had been previously unlearnable, these techniques are still susceptible to the longstanding problem of reward sparsity. This is especially true for tasks such as training an agent to pla... | 1911.00497 | https://arxiv.org/abs/1911.00497v1 | https://arxiv.org/pdf/1911.00497v1.pdf | [
"Starcraft",
"Starcraft II"
] | [] | [] |
wQtRuhyhcH | https://paperswithcode.com/paper/weighted-nonlocal-total-variation-in-image | Weighted Nonlocal Total Variation in Image Processing | In this paper, a novel weighted nonlocal total variation (WNTV) method is
proposed. Compared to the classical nonlocal total variation methods, our
method modifies the energy functional to introduce a weight to balance between
the labeled sets and unlabeled sets. With extensive numerical examples in
semi-supervised clu... | 1801.10441 | http://arxiv.org/abs/1801.10441v1 | http://arxiv.org/pdf/1801.10441v1.pdf | [
"Colorization",
"Image Inpainting"
] | [] | [] |
CCkyLhGo9Z | https://paperswithcode.com/paper/mixture-modeling-on-related-samples-by-stick | Mixture modeling on related samples by $ψ$-stick breaking and kernel perturbation | There has been great interest recently in applying nonparametric kernel
mixtures in a hierarchical manner to model multiple related data samples
jointly. In such settings several data features are commonly present: (i) the
related samples often share some, if not all, of the mixture components but
with differing weight... | 1704.04839 | http://arxiv.org/abs/1704.04839v1 | http://arxiv.org/pdf/1704.04839v1.pdf | [
"Bayesian Inference"
] | [] | [] |
wNBECFCaZp | https://paperswithcode.com/paper/deep-direct-regression-for-multi-oriented | Deep Direct Regression for Multi-Oriented Scene Text Detection | In this paper, we first provide a new perspective to divide existing high
performance object detection methods into direct and indirect regressions.
Direct regression performs boundary regression by predicting the offsets from a
given point, while indirect regression predicts the offsets from some bounding
box proposal... | 1703.08289 | http://arxiv.org/abs/1703.08289v1 | http://arxiv.org/pdf/1703.08289v1.pdf | [
"Multi-Oriented Scene Text Detection",
"Object Detection",
"Scene Text",
"Scene Text Detection"
] | [] | [] |
PrYTtVa-uW | https://paperswithcode.com/paper/understanding-car-speak-replacing-humans-in | Understanding Car-Speak: Replacing Humans in Dealerships | A large portion of the car-buying experience in the United States involves interactions at a car dealership. At the dealership, the car-buyer relays their needs to a sales representative. However, most car-buyers are only have an abstract description of the vehicle they need. Therefore, they are only able to describe t... | 2002.02070 | https://arxiv.org/abs/2002.02070v1 | https://arxiv.org/pdf/2002.02070v1.pdf | [] | [] | [] |
CqtlF_ZgEh | https://paperswithcode.com/paper/resolution-and-throughput-enhanced | Resolution- and throughput-enhanced spectroscopy using high-throughput computational slit | There exists a fundamental tradeoff between spectral resolution and the
efficiency or throughput for all optical spectrometers. The primary factors
affecting the spectral resolution and throughput of an optical spectrometer are
the size of the entrance aperture and the optical power of the focusing
element. Thus far co... | 1606.09072 | http://arxiv.org/abs/1606.09072v2 | http://arxiv.org/pdf/1606.09072v2.pdf | [] | [] | [] |
mPHSOJxTsq | https://paperswithcode.com/paper/cooperative-initialization-based-deep-neural | Cooperative Initialization based Deep Neural Network Training | Researchers have proposed various activation functions. These activation functions help the deep network to learn non-linear behavior with a significant effect on training dynamics and task performance. The performance of these activations also depends on the initial state of the weight parameters, i.e., different init... | 2001.01240 | https://arxiv.org/abs/2001.01240v1 | https://arxiv.org/pdf/2001.01240v1.pdf | [] | [
"ReLU"
] | [] |
nYTKjVNHXF | https://paperswithcode.com/paper/neural-user-simulation-for-corpus-based-1 | Neural User Simulation for Corpus-based Policy Optimisation for Spoken Dialogue Systems | User Simulators are one of the major tools that enable offline training of
task-oriented dialogue systems. For this task the Agenda-Based User Simulator
(ABUS) is often used. The ABUS is based on hand-crafted rules and its output is
in semantic form. Issues arise from both properties such as limited diversity
and the i... | 1805.06966 | http://arxiv.org/abs/1805.06966v1 | http://arxiv.org/pdf/1805.06966v1.pdf | [
"Spoken Dialogue Systems",
"Task-Oriented Dialogue Systems"
] | [] | [] |
3Via22vdQ0 | https://paperswithcode.com/paper/universal-intelligence-a-definition-of | Universal Intelligence: A Definition of Machine Intelligence | A fundamental problem in artificial intelligence is that nobody really knows what intelligence is. The problem is especially acute when we need to consider artificial systems which are significantly different to humans. In this paper we approach this problem in the following way: We take a number of well known informal... | 0712.3329 | https://arxiv.org/abs/0712.3329v1 | https://arxiv.org/pdf/0712.3329v1.pdf | [] | [] | [] |
nB44hUZyh8 | https://paperswithcode.com/paper/learning-a-behavioral-repertoire-from | Learning a Behavioral Repertoire from Demonstrations | Imitation Learning (IL) is a machine learning approach to learn a policy from a dataset of demonstrations. IL can be useful to kick-start learning before applying reinforcement learning (RL) but it can also be useful on its own, e.g. to learn to imitate human players in video games. However, a major limitation of curre... | 1907.03046 | https://arxiv.org/abs/1907.03046v1 | https://arxiv.org/pdf/1907.03046v1.pdf | [
"Imitation Learning",
"Starcraft",
"Starcraft II"
] | [] | [] |
aG2LlX_n9b | https://paperswithcode.com/paper/toward-the-engineering-of-virtuous-machines | Toward the Engineering of Virtuous Machines | While various traditions under the 'virtue ethics' umbrella have been studied
extensively and advocated by ethicists, it has not been clear that there exists
a version of virtue ethics rigorous enough to be a target for machine ethics
(which we take to include the engineering of an ethical sensibility in a
machine or r... | 1812.03868 | http://arxiv.org/abs/1812.03868v2 | http://arxiv.org/pdf/1812.03868v2.pdf | [] | [] | [] |
hKwtKTb1km | https://paperswithcode.com/paper/identifying-notable-news-stories | Identifying Notable News Stories | The volume of news content has increased significantly in recent years and systems to process and deliver this information in an automated fashion at scale are becoming increasingly prevalent. One critical component that is required in such systems is a method to automatically determine how notable a certain news story... | 2003.07461 | https://arxiv.org/abs/2003.07461v1 | https://arxiv.org/pdf/2003.07461v1.pdf | [
"Learning-To-Rank"
] | [] | [] |
2R6sUo_4c_ | https://paperswithcode.com/paper/safetynet-detecting-and-rejecting-adversarial | SafetyNet: Detecting and Rejecting Adversarial Examples Robustly | We describe a method to produce a network where current methods such as
DeepFool have great difficulty producing adversarial samples. Our construction
suggests some insights into how deep networks work. We provide a reasonable
analyses that our construction is difficult to defeat, and show experimentally
that our metho... | 1704.00103 | http://arxiv.org/abs/1704.00103v2 | http://arxiv.org/pdf/1704.00103v2.pdf | [] | [] | [] |
0aE50C1UeL | https://paperswithcode.com/paper/optimal-resampling-for-learning-small-models | Interpretability with Accurate Small Models | Models often need to be constrained to a certain size for them to be considered interpretable. For example, a decision tree of depth 5 is much easier to understand than one of depth 50. Limiting model size, however, often reduces accuracy. We suggest a practical technique that minimizes this trade-off between interpret... | 1905.01520 | https://arxiv.org/abs/1905.01520v2 | https://arxiv.org/pdf/1905.01520v2.pdf | [] | [] | [] |
-y92KByUzL | https://paperswithcode.com/paper/distributed-exploration-in-multi-armed | Distributed Exploration in Multi-Armed Bandits | We study exploration in Multi-Armed Bandits in a setting where $k$ players
collaborate in order to identify an $\epsilon$-optimal arm. Our motivation
comes from recent employment of bandit algorithms in computationally intensive,
large-scale applications. Our results demonstrate a non-trivial tradeoff
between the numbe... | 1311.0800 | http://arxiv.org/abs/1311.0800v1 | http://arxiv.org/pdf/1311.0800v1.pdf | [
"Multi-Armed Bandits"
] | [] | [] |
GORjwHFhDx | https://paperswithcode.com/paper/a-novel-scene-text-detection-algorithm-based | A Novel Scene Text Detection Algorithm Based On Convolutional Neural Network | Candidate text region extraction plays a critical role in convolutional
neural network (CNN) based text detection from natural images. In this paper,
we propose a CNN based scene text detection algorithm with a new text region
extractor. The so called candidate text region extractor I-MSER is based on
Maximally Stable ... | 1604.01894 | http://arxiv.org/abs/1604.01894v1 | http://arxiv.org/pdf/1604.01894v1.pdf | [
"Scene Text",
"Scene Text Detection"
] | [] | [] |
6Ixtrelcl4 | https://paperswithcode.com/paper/a-sparse-code-for-neuro-dynamic-programming | A sparse code increases the speed and efficiency of neuro-dynamic programming for optimal control tasks with correlated feature inputs | Sparse codes in neuroscience have been suggested to offer certain computational advantages over other neural representations of sensory data. To explore this viewpoint, a sparse code is used to represent natural images in an optimal control task solved with neuro-dynamic programming, and its computational properties ar... | 2006.11968 | https://arxiv.org/abs/2006.11968v2 | https://arxiv.org/pdf/2006.11968v2.pdf | [] | [] | [] |
pYKZHsiu_f | https://paperswithcode.com/paper/attenuation-correction-for-brain-pet-imaging | Attenuation correction for brain PET imaging using deep neural network based on dixon and ZTE MR images | Positron Emission Tomography (PET) is a functional imaging modality widely
used in neuroscience studies. To obtain meaningful quantitative results from
PET images, attenuation correction is necessary during image reconstruction.
For PET/MR hybrid systems, PET attenuation is challenging as Magnetic Resonance
(MR) images... | 1712.06203 | http://arxiv.org/abs/1712.06203v2 | http://arxiv.org/pdf/1712.06203v2.pdf | [
"Image Reconstruction"
] | [
"Concatenated Skip Connection",
"ReLU",
"Max Pooling",
"U-Net",
"Convolution"
] | [] |
zTD6GPWa7l | https://paperswithcode.com/paper/fully-convolutional-recurrent-network-for | Fully Convolutional Recurrent Network for Handwritten Chinese Text Recognition | This paper proposes an end-to-end framework, namely fully convolutional
recurrent network (FCRN) for handwritten Chinese text recognition (HCTR).
Unlike traditional methods that rely heavily on segmentation, our FCRN is
trained with online text data directly and learns to associate the pen-tip
trajectory with a sequenc... | 1604.04953 | http://arxiv.org/abs/1604.04953v1 | http://arxiv.org/pdf/1604.04953v1.pdf | [
"Handwriting Recognition",
"Handwritten Chinese Text Recognition",
"Language Modelling"
] | [] | [] |
85U17RpJE3 | https://paperswithcode.com/paper/dinfra-a-one-stop-shop-for-computing | DINFRA: A One Stop Shop for Computing Multilingual Semantic Relatedness | This demonstration presents an infrastructure for computing multilingual
semantic relatedness and correlation for twelve natural languages by using
three distributional semantic models (DSMs). Our demonsrator - DInfra
(Distributional Infrastructure) provides researchers and developers with a
highly useful platform for ... | 1805.09644 | http://arxiv.org/abs/1805.09644v1 | http://arxiv.org/pdf/1805.09644v1.pdf | [] | [] | [] |
HOO5CbJho3 | https://paperswithcode.com/paper/new-graph-based-features-for-shape | New Graph-based Features For Shape Recognition | Shape recognition is the main challenging problem in computer vision. Different approaches and tools are used to solve this problem. Most existing approaches to object recognition are based on pixels. Pixel-based methods are dependent on the geometry and nature of the pixels, so the destruction of pixels reduces their ... | 1909.03482 | https://arxiv.org/abs/1909.03482v1 | https://arxiv.org/pdf/1909.03482v1.pdf | [
"Object Recognition"
] | [] | [] |
waqicJJPSe | https://paperswithcode.com/paper/minimal-exploration-in-structured-stochastic | Minimal Exploration in Structured Stochastic Bandits | This paper introduces and addresses a wide class of stochastic bandit
problems where the function mapping the arm to the corresponding reward
exhibits some known structural properties. Most existing structures (e.g.
linear, Lipschitz, unimodal, combinatorial, dueling, ...) are covered by our
framework. We derive an asy... | 1711.00400 | http://arxiv.org/abs/1711.00400v1 | http://arxiv.org/pdf/1711.00400v1.pdf | [] | [] | [] |
ycDaU_Ok9s | https://paperswithcode.com/paper/shading-based-shape-refinement-of-rgb-d | Shading-Based Shape Refinement of RGB-D Images | We present a shading-based shape refinement algorithm which uses a noisy, incomplete depth map from Kinect to help resolve ambiguities in shape-from-shading. In our framework, the partial depth information is used to overcome bas-relief ambiguity in normals estimation, as well as to assist in recovering relative albedo... | null | http://openaccess.thecvf.com/content_cvpr_2013/html/Yu_Shading-Based_Shape_Refinement_2013_CVPR_paper.html | http://openaccess.thecvf.com/content_cvpr_2013/papers/Yu_Shading-Based_Shape_Refinement_2013_CVPR_paper.pdf | [] | [] | [] |
GCikW5vTIB | https://paperswithcode.com/paper/ensemble-of-heterogeneous-flexible-neural | Ensemble of heterogeneous flexible neural trees using multiobjective genetic programming | Machine learning algorithms are inherently multiobjective in nature, where
approximation error minimization and model's complexity simplification are two
conflicting objectives. We proposed a multiobjective genetic programming (MOGP)
for creating a heterogeneous flexible neural tree (HFNT), tree-like flexible
feedforwa... | 1705.05592 | http://arxiv.org/abs/1705.05592v1 | http://arxiv.org/pdf/1705.05592v1.pdf | [
"Time Series"
] | [] | [] |
Trboxg8Ad1 | https://paperswithcode.com/paper/fast-immune-system-inspired-hypermutation | Fast Immune System Inspired Hypermutation Operators for Combinatorial Optimisation | Various studies have shown that immune system inspired hypermutation operators can allow artificial immune systems (AIS) to be very efficient at escaping local optima of multimodal optimisation problems. However, this efficiency comes at the expense of considerably slower runtimes during the exploitation phase compared... | 2009.00990 | https://arxiv.org/abs/2009.00990v1 | https://arxiv.org/pdf/2009.00990v1.pdf | [] | [] | [] |
RfGbQxiX1j | https://paperswithcode.com/paper/mapping-paradigm-ontologies-to-and-from-the | Mapping paradigm ontologies to and from the brain | Imaging neuroscience links brain activation maps to behavior and cognition via correlational studies. Due to the nature of the individual experiments, based on eliciting neural response from a small number of stimuli, this link is incomplete, and unidirectional from the causal point of view. To come to conclusions on t... | null | http://papers.nips.cc/paper/5168-mapping-paradigm-ontologies-to-and-from-the-brain | http://papers.nips.cc/paper/5168-mapping-paradigm-ontologies-to-and-from-the-brain.pdf | [] | [] | [] |
RZ8q6JlpBs | https://paperswithcode.com/paper/classification-of-hyperspectral-imagery-on | Classification of Hyperspectral Imagery on Embedded Grassmannians | We propose an approach for capturing the signal variability in hyperspectral
imagery using the framework of the Grassmann manifold. Labeled points from each
class are sampled and used to form abstract points on the Grassmannian. The
resulting points on the Grassmannian have representations as orthonormal
matrices and a... | 1502.00946 | http://arxiv.org/abs/1502.00946v1 | http://arxiv.org/pdf/1502.00946v1.pdf | [] | [] | [] |
3aBJKVq0Vc | https://paperswithcode.com/paper/recent-advances-on-inconsistency-indices-for | Recent advances on inconsistency indices for pairwise comparisons - a commentary | This paper recalls the definition of consistency for pairwise comparison
matrices and briefly presents the concept of inconsistency index in connection
to other aspects of the theory of pairwise comparisons. By commenting on a
recent contribution by Koczkodaj and Szwarc, it will be shown that the
discussion on inconsis... | 1503.08289 | http://arxiv.org/abs/1503.08289v3 | http://arxiv.org/pdf/1503.08289v3.pdf | [] | [] | [] |
JUCLpqhn7O | https://paperswithcode.com/paper/irit-at-trac-2020 | IRIT at TRAC 2020 | This paper describes the participation of the IRIT team in the TRAC (Trolling, Aggression and Cyberbullying) 2020 shared task (Bhattacharya et al., 2020) on Aggression Identification and more precisely to the shared task in English language. The shared task was further divided into two sub-tasks: (a) aggression identif... | null | https://www.aclweb.org/anthology/2020.trac-1.8/ | https://www.aclweb.org/anthology/2020.trac-1.8 | [
"Aggression Identification",
"Language Modelling",
"Misogynistic Aggression Identification"
] | [
"Weight Decay",
"GELU",
"Attention Dropout",
"Linear Warmup With Linear Decay",
"WordPiece",
"Residual Connection",
"Label Smoothing",
"BERT",
"Multi-Head Attention",
"Adam",
"ReLU",
"Dropout",
"BPE",
"Dense Connections",
"Layer Normalization",
"Softmax",
"Scaled Dot-Product Attentio... | [] |
HIlPEgiHPr | https://paperswithcode.com/paper/axioms-for-graph-clustering-quality-functions | Axioms for graph clustering quality functions | We investigate properties that intuitively ought to be satisfied by graph
clustering quality functions, that is, functions that assign a score to a
clustering of a graph. Graph clustering, also known as network community
detection, is often performed by optimizing such a function. Two axioms
tailored for graph clusteri... | 1308.3383 | http://arxiv.org/abs/1308.3383v2 | http://arxiv.org/pdf/1308.3383v2.pdf | [
"Community Detection",
"Graph Clustering"
] | [] | [] |
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