
Asynchronous Advantage Actor Critic: Nonasymptotic Analysis and Linear Speedup
Asynchronous and parallel implementation of standard reinforcement learn...
read it

CADA: CommunicationAdaptive Distributed Adam
Stochastic gradient descent (SGD) has taken the stage as the primary wor...
read it

Hybrid Federated Learning: Algorithms and Implementation
Federated learning (FL) is a recently proposed distributed machine learn...
read it

Automatic Clustering for Unsupervised Risk Diagnosis of Vehicle Driving for Smart Road
Early risk diagnosis and driving anomaly detection from vehicle stream a...
read it

Neural Network Compression Via Sparse Optimization
The compression of deep neural networks (DNNs) to reduce inference cost ...
read it

A Simple Spectral Failure Mode for Graph Convolutional Networks
We present a simple generative model in which spectral graph embedding f...
read it

Solving Stochastic Compositional Optimization is Nearly as Easy as Solving Stochastic Optimization
Stochastic compositional optimization generalizes classic (noncompositi...
read it

Recurrent Exposure Generation for LowLight Face Detection
Face detection from lowlight images is challenging due to limited photo...
read it

VAFL: a Method of Vertical Asynchronous Federated Learning
Horizontal Federated learning (FL) handles multiclient data that share ...
read it

CommunicationEfficient Robust Federated Learning Over Heterogeneous Datasets
This work investigates faultresilient federated learning when the data ...
read it

Orthant Based Proximal Stochastic Gradient Method for ℓ_1Regularized Optimization
Sparsityinducing regularization problems are ubiquitous in machine lear...
read it

LASG: Lazily Aggregated Stochastic Gradients for CommunicationEfficient Distributed Learning
This paper targets solving distributed machine learning problems such as...
read it

Adaptive Temporal Difference Learning with Linear Function Approximation
This paper revisits the celebrated temporal difference (TD) learning alg...
read it

Federated VarianceReduced Stochastic Gradient Descent with Robustness to Byzantine Attacks
This paper deals with distributed finitesum optimization for learning o...
read it

Decentralized Markov Chain Gradient Descent
Decentralized stochastic gradient method emerges as a promising solution...
read it

CommunicationEfficient Distributed Learning via Lazily Aggregated Quantized Gradients
The present paper develops a novel aggregated gradient approach for dist...
read it

CommunicationCensored Distributed Stochastic Gradient Descent
This paper develops a communicationefficient algorithm to solve the sto...
read it

Generative Adversarial Network for Handwritten Text
Generative adversarial networks (GANs) has proven hugely successful in v...
read it

Novel Dense Subgraph Discovery Primitives: Risk Aversion and Exclusion Queries
In the densest subgraph problem, given a weighted undirected graph G(V,E...
read it

CommunicationEfficient Distributed Reinforcement Learning
This paper studies the distributed reinforcement learning (DRL) problem ...
read it

RSA: ByzantineRobust Stochastic Aggregation Methods for Distributed Learning from Heterogeneous Datasets
In this paper, we propose a class of robust stochastic subgradient metho...
read it

Learning and Management for InternetofThings: Accounting for Adaptivity and Scalability
InternetofThings (IoT) envisions an intelligent infrastructure of netw...
read it

Delayed Bandit Online Learning with Unknown Delays
This paper studies bandit learning problems with delayed feedback, which...
read it

LAG: Lazily Aggregated Gradient for CommunicationEfficient Distributed Learning
This paper presents a new class of gradient methods for distributed mach...
read it

Secure Mobile Edge Computing in IoT via Collaborative Online Learning
To accommodate heterogeneous tasks in Internet of Things (IoT), a new co...
read it

MultiTimescale Online Optimization of Network Function Virtualization for Service Chaining
Network Function Virtualization (NFV) can costefficiently provide netwo...
read it

Random Featurebased Online Multikernel Learning in Environments with Unknown Dynamics
Kernelbased methods exhibit welldocumented performance in various nonl...
read it

Online Ensemble Multikernel Learning Adaptive to Nonstationary and Adversarial Environments
Kernelbased methods exhibit welldocumented performance in various nonl...
read it

An Online Convex Optimization Approach to Dynamic Network Resource Allocation
Existing approaches to online convex optimization (OCO) make sequential ...
read it

Stochastic Averaging for Constrained Optimization with Application to Online Resource Allocation
Existing approaches to resource allocation for nowadays stochastic netwo...
read it
Tianyi Chen
is this you? claim profile