
FedCV: A Federated Learning Framework for Diverse Computer Vision Tasks
Federated Learning (FL) is a distributed learning paradigm that can lear...
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Offpolicy Imitation Learning from Visual Inputs
Recently, various successful applications utilizing expert states in imi...
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Learning Meta Representations for Agents in MultiAgent Reinforcement Learning
In multiagent reinforcement learning, the behaviors that agents learn i...
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TCCT: TightlyCoupled Convolutional Transformer on Time Series Forecasting
Time series forecasting is essential for a wide range of realworld appl...
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EndtoEnd Adaptive Monte Carlo Denoising and SuperResolution
The classic Monte Carlo path tracing can achieve high quality rendering ...
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UniFaceGAN: A Unified Framework for Temporally Consistent Facial Video Editing
Recent research has witnessed advances in facial image editing tasks inc...
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S2Looking: A Satellite SideLooking Dataset for Building Change Detection
Collecting largescale annotated satellite imagery datasets is essential...
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MIMO Transmission Under Discrete Input Signal Constraints
In this paper, we propose a multipleinput multipleoutput (MIMO) transmi...
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Sparse Training via Boosting Pruning Plasticity with Neuroregeneration
Works on lottery ticket hypothesis (LTH) and singleshot network pruning...
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Local AdaGradType Algorithm for Stochastic ConvexConcave Minimax Problems
Large scale convexconcave minimax problems arise in numerous applicatio...
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StructureRegularized Attention for Deformable Object Representation
Capturing contextual dependencies has proven useful to improve the repre...
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Attacking Adversarial Attacks as A Defense
It is well known that adversarial attacks can fool deep neural networks ...
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Lightweight Image SuperResolution with Hierarchical and Differentiable Neural Architecture Search
Single Image SuperResolution (SISR) tasks have achieved significant per...
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Robust Registration of Multimodal Remote Sensing Images Based on Structural Similarity
Automatic registration of multimodal remote sensing data (e.g., optical,...
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Towards Practical Adam: NonConvexity, Convergence Theory, and MiniBatch Acceleration
Adam is one of the most influential adaptive stochastic algorithms for t...
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Adaptive Compact Attention For Fewshot Videotovideo Translation
This paper proposes an adaptive compact attention model for fewshot vid...
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A Distributed Training Algorithm of Generative Adversarial Networks with Quantized Gradients
Training generative adversarial networks (GAN) in a distributed fashion ...
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Grouping effects of sparse CCA models in variable selection
The sparse canonical correlation analysis (SCCA) is a bimultivariate as...
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Taskagnostic Temporally Consistent Facial Video Editing
Recent research has witnessed the advances in facial image editing tasks...
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AlphaGAN: Fully Differentiable Architecture Search for Generative Adversarial Networks
Generative Adversarial Networks (GANs) are formulated as minimax game pr...
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Realtime Universal Style Transfer on Highresolution Images via Zerochannel Pruning
Extracting effective deep features to represent content and style inform...
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CPOT: Channel Pruning via Optimal Transport
Recent advances in deep neural networks (DNNs) lead to tremendously grow...
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CommunicationEfficient Distributed Stochastic AUC Maximization with Deep Neural Networks
In this paper, we study distributed algorithms for largescale AUC maxim...
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Quantized Adam with Error Feedback
In this paper, we present a distributed variant of adaptive stochastic g...
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Generalized Embedding Machines for Recommender Systems
Factorization machine (FM) is an effective model for featurebased recom...
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Adaptive Activation Network and Functional Regularization for Efficient and Flexible Deep MultiTask Learning
Multitask learning (MTL) is a common paradigm that seeks to improve the...
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A Block Decomposition Algorithm for Sparse Optimization
Sparse optimization is a central problem in machine learning and compute...
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MAP Inference via L2Sphere Linear Program Reformulation
Maximum a posteriori (MAP) inference is an important task for graphical ...
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Drugdrug interaction prediction based on comedication patterns and graph matching
Background: The problem of predicting whether a drug combination of arbi...
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A Sufficient Condition for Convergences of Adam and RMSProp
Adam and RMSProp, as two of the most influential adaptive stochastic alg...
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GatherExcite: Exploiting Feature Context in Convolutional Neural Networks
While the use of bottomup local operators in convolutional neural netwo...
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Image Registration and Predictive Modeling: Learning the Metric on the Space of Diffeomorphisms
We present a method for metric optimization in the Large Deformation Dif...
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Weighted AdaGrad with Unified Momentum
Integrating adaptive learning rate and momentum techniques into SGD lead...
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On the Convergence of Weighted AdaGrad with Momentum for Training Deep Neural Networks
Adaptive stochastic gradient descent methods, such as AdaGrad, RMSProp, ...
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On the Convergence of AdaGrad with Momentum for Training Deep Neural Networks
Adaptive stochastic gradient descent methods, such as AdaGrad, Adam, Ada...
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Comparator Networks
The objective of this work is setbased verification, e.g. to decide if ...
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A Generalized Matrix Splitting Algorithm
Composite function minimization captures a wide spectrum of applications...
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Drug Recommendation toward Safe Polypharmacy
Adverse drug reactions (ADRs) induced from highorder drugdrug interact...
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A Decomposition Algorithm for Sparse Generalized Eigenvalue Problem
Sparse generalized eigenvalue problem arises in a number of standard and...
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Endtoend Training for Whole Image Breast Cancer Diagnosis using An All Convolutional Design
We develop an endtoend training algorithm for wholeimage breast cance...
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VGGFace2: A dataset for recognising faces across pose and age
In this paper, we introduce a new largescale face dataset named VGGFace...
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SqueezeandExcitation Networks
Convolutional neural networks are built upon the convolution operation, ...
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Contour Detection from Deep Patchlevel Boundary Prediction
In this paper, we present a novel approach for contour detection with Co...
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Cooccurrence Feature Learning for Skeleton based Action Recognition using Regularized Deep LSTM Networks
Skeleton based action recognition distinguishes human actions using the ...
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Relay Backpropagation for Effective Learning of Deep Convolutional Neural Networks
Learning deeper convolutional neural networks becomes a tendency in rece...
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Shadow Optimization from Structured Deep Edge Detection
Local structures of shadow boundaries as well as complex interactions of...
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Li Shen
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