
Trend estimation and shortterm forecasting of COVID19 cases and deaths worldwide
Since the beginning of the COVID19 pandemic, many dashboards have emerg...
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Decentralized Federated Averaging
Federated averaging (FedAvg) is a communication efficient algorithm for ...
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Stability and Generalization of the Decentralized Stochastic Gradient Descent
The stability and generalization of stochastic gradientbased methods pr...
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Inertial Proximal Deep Learning Alternating Minimization for Efficient Neutral Network Training
In recent years, the Deep Learning Alternating Minimization (DLAM), whic...
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Threequarter Sibling Regression for Denoising Observational Data
Many ecological studies and conservation policies are based on field obs...
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REPAINT: Knowledge Transfer in Deep ActorCritic Reinforcement Learning
Accelerating the learning processes for complex tasks by leveraging prev...
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Endtoend Full Projector Compensation
Full projector compensation aims to modify a projector input image to co...
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FedGAN: Federated Generative Adversarial Networks for Distributed Data
We propose Federated Generative Adversarial Network (FedGAN) for trainin...
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FedGAN: Federated Generative AdversarialNetworks for Distributed Data
We propose Federated Generative Adversarial Network (FedGAN) for trainin...
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Adaptive Temporal Difference Learning with Linear Function Approximation
This paper revisits the celebrated temporal difference (TD) learning alg...
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ZeroShot Reinforcement Learning with Deep Attention Convolutional Neural Networks
Simulationtosimulation and simulationtoreal world transfer of neural...
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DeepRacer: Educational Autonomous Racing Platform for Experimentation with Sim2Real Reinforcement Learning
DeepRacer is a platform for endtoend experimentation with RL and can b...
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General Proximal Incremental Aggregated Gradient Algorithms: Better and Novel Results under General Scheme
The incremental aggregated gradient algorithm is popular in network opti...
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Decentralized Markov Chain Gradient Descent
Decentralized stochastic gradient method emerges as a promising solution...
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Dilated FCN: Listening Longer to Hear Better
Deep neural network solutions have emerged as a new and powerful paradig...
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Inertial nonconvex alternating minimizations for the image deblurring
In image processing, Total Variation (TV) regularization models are comm...
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Heavyball Algorithms Always Escape Saddle Points
Nonconvex optimization algorithms with random initialization have attrac...
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Leveraging Crowdsourced GPS Data for Road Extraction from Aerial Imagery
Deep learning is revolutionizing the mapping industry. Under lightweight...
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Iteratively reweighted penalty alternating minimization methods with continuation for image deblurring
In this paper, we consider a class of nonconvex problems with linear con...
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Traceback Along Capsules and Its Application on Semantic Segmentation
In this paper, we propose a capsulebased neural network model to solve ...
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Copulabased semiparametric transformation model for bivariate data under general interval censoring
This research is motivated by discovering and underpinning genetic cause...
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QualityAware Multimodal Saliency Detection via Deep Reinforcement Learning
Incorporating various modes of information into the machine learning pro...
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Markov Chain Block Coordinate Descent
The method of block coordinate gradient descent (BCD) has been a powerfu...
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Nonergodic Convergence Analysis of HeavyBall Algorithms
In this paper, we revisit the convergence of the Heavyball method, and ...
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On Markov Chain Gradient Descent
Stochastic gradient methods are the workhorse (algorithms) of largescal...
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An Efficient ADMMBased Algorithm to Nonconvex Penalized Support Vector Machines
Support vector machines (SVMs) with sparsityinducing nonconvex penaltie...
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LAG: Lazily Aggregated Gradient for CommunicationEfficient Distributed Learning
This paper presents a new class of gradient methods for distributed mach...
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On the complexity of convex inertial proximal algorithms
The inertial proximal gradient algorithm is efficient for the composite ...
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A convergence frame for inexact nonconvex and nonsmooth algorithms and its applications to several iterations
In this paper, we consider the convergence of an abstract inexact noncon...
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Iteratively Linearized Reweighted Alternating Direction Method of Multipliers for a Class of Nonconvex Problems
In this paper, we consider solving a class of nonconvex and nonsmooth pr...
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Differentially Private Learning of Undirected Graphical Models using Collective Graphical Models
We investigate the problem of learning discrete, undirected graphical mo...
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Tao Sun
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