Shusen Wang | DeepAI

AI Chat

Featured Co-authors

Michael I. Jordan
283 publications
Hai Zhao
159 publications
Jian Li
150 publications
Peng Xu
128 publications
Michael W. Mahoney
126 publications
Tong Zhang
99 publications
Xiang Li
70 publications
Peng Jiang
59 publications
Kannan Ramchandran
53 publications
Zhihua Zhang
53 publications
Jia Xu
31 publications

∙ 07/21/2023

Methodologies for Improving Modern Industrial Recommender Systems

Recommender system (RS) is an established technology with successful app...

0 Shusen Wang, et al. ∙

∙ 05/24/2023

RefGPT: Reference -> Truthful Customized Dialogues Generation by GPTs and for GPTs

General chat models, like ChatGPT, have attained impressive capability t...

0 Dongjie Yang, et al. ∙

∙ 02/09/2023

An End-to-End Framework for Marketing Effectiveness Optimization under Budget Constraint

Online platforms often incentivize consumers to improve user engagement ...

0 Ziang Yan, et al. ∙

∙ 08/04/2022

Transferable Multi-Agent Reinforcement Learning with Dynamic Participating Agents

We study multi-agent reinforcement learning (MARL) with centralized trai...

0 Xuting Tang, et al. ∙

∙ 04/06/2022

Federated Reinforcement Learning with Environment Heterogeneity

We study a Federated Reinforcement Learning (FedRL) problem in which n a...

1 Hao Jin, et al. ∙

∙ 12/21/2019

Graph Message Passing with Cross-location Attentions for Long-term ILI Prediction

Forecasting influenza-like illness (ILI) is of prime importance to epide...

13 Songgaojun Deng, et al. ∙

∙ 10/21/2019

Communication Efficient Decentralized Training with Multiple Local Updates

Communication efficiency plays a significant role in decentralized optim...

0 Xiang Li, et al. ∙

∙ 09/24/2019

Simple and Almost Assumption-Free Out-of-Sample Bound for Random Feature Mapping

Random feature mapping (RFM) is a popular method for speeding up kernel ...

0 Shusen Wang, et al. ∙

∙ 09/24/2019

Matrix Sketching for Secure Collaborative Machine Learning

Collaborative machine learning (ML), also known as federated ML, allows ...

0 Shusen Wang, et al. ∙

∙ 07/04/2019

On the Convergence of FedAvg on Non-IID Data

Federated learning enables a large amount of edge computing devices to l...

0 Xiang Li, et al. ∙

∙ 02/13/2019

Do Subsampled Newton Methods Work for High-Dimensional Data?

Subsampled Newton methods approximate Hessian matrices through subsampli...

0 Xiang Li, et al. ∙

∙ 11/06/2018

OverSketch: Approximate Matrix Multiplication for the Cloud

We propose OverSketch, an approximate algorithm for distributed matrix m...

0 Vipul Gupta, et al. ∙

∙ 06/03/2018

Alchemist: An Apache Spark <=> MPI Interface

The Apache Spark framework for distributed computation is popular in the...

0 Alex Gittens, et al. ∙

∙ 05/30/2018

Accelerating Large-Scale Data Analysis by Offloading to High-Performance Computing Libraries using Alchemist

Apache Spark is a popular system aimed at the analysis of large data set...

0 Alex Gittens, et al. ∙

∙ 03/21/2018

Error Estimation for Randomized Least-Squares Algorithms via the Bootstrap

Over the course of the past decade, a variety of randomized algorithms h...

0 Miles E. Lopes, et al. ∙

∙ 10/11/2017

Efficient Data-Driven Geologic Feature Detection from Pre-stack Seismic Measurements using Randomized Machine-Learning Algorithm

Conventional seismic techniques for detecting the subsurface geologic fe...

0 Youzuo Lin, et al. ∙

∙ 09/11/2017

GIANT: Globally Improved Approximate Newton Method for Distributed Optimization

For distributed computing environments, we consider the canonical machin...

0 Shusen Wang, et al. ∙

∙ 08/06/2017

A Bootstrap Method for Error Estimation in Randomized Matrix Multiplication

In recent years, randomized methods for numerical linear algebra have re...

0 Miles E. Lopes, et al. ∙

∙ 06/09/2017

Scalable Kernel K-Means Clustering with Nystrom Approximation: Relative-Error Bounds

Kernel k-means clustering can correctly identify and extract a far more ...

0 Shusen Wang, et al. ∙

∙ 02/16/2017

Sketched Ridge Regression: Optimization Perspective, Statistical Perspective, and Model Averaging

We address the statistical and optimization impacts of using classical s...

0 Shusen Wang, et al. ∙

∙ 12/26/2014

Adjusting Leverage Scores by Row Weighting: A Practical Approach to Coherent Matrix Completion

Low-rank matrix completion is an important problem with extensive real-w...

0 Shusen Wang, et al. ∙

∙ 03/30/2014

Sharpened Error Bounds for Random Sampling Based ℓ_2 Regression

Given a data matrix X ∈ R^n× d and a response vector y ∈ R^n, suppose n>...

0 Shusen Wang, et al. ∙

∙ 10/04/2012

A Scalable CUR Matrix Decomposition Algorithm: Lower Time Complexity and Tighter Bound

The CUR matrix decomposition is an important extension of Nyström approx...

0 Shusen Wang, et al. ∙

∙ 04/19/2012

EP-GIG Priors and Applications in Bayesian Sparse Learning

In this paper we propose a novel framework for the construction of spars...

0 Zhihua Zhang, et al. ∙

Are you a researcher?
Expose your work
to one of the largest
A.I. communities in the world