
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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