b'Lin Xiao'

research

∙ 03/22/2023

Noisy recovery from random linear observations: Sharp minimax rates under elliptical constraints

Estimation problems with constrained parameter spaces arise in various s...

0 Reese Pathak, et al. ∙

research

∙ 01/17/2023

Sparse and Integrative Principal Component Analysis for Multiview Data

We consider dimension reduction of multiview data, which are emerging in...

0 Lin Xiao, et al. ∙

research

∙ 11/19/2022

Pairwise Instance Relation Augmentation for Long-tailed Multi-label Text Classification

Multi-label text classification (MLTC) is one of the key tasks in natura...

0 Lin Xiao, et al. ∙

research

∙ 10/04/2022

Linear Convergence of Natural Policy Gradient Methods with Log-Linear Policies

We consider infinite-horizon discounted Markov decision processes and st...

0 Rui Yuan, et al. ∙

research

∙ 10/03/2022

Faster Last-iterate Convergence of Policy Optimization in Zero-Sum Markov Games

Multi-Agent Reinforcement Learning (MARL) – where multiple agents learn ...

0 Shicong Cen, et al. ∙

research

∙ 05/25/2022

BiT: Robustly Binarized Multi-distilled Transformer

Modern pre-trained transformers have rapidly advanced the state-of-the-a...

0 Zechun Liu, et al. ∙

research

∙ 04/27/2022

FedShuffle: Recipes for Better Use of Local Work in Federated Learning

The practice of applying several local updates before aggregation across...

1 Samuel Horvath, et al. ∙

research

∙ 04/08/2022

Federated Learning with Partial Model Personalization

We consider two federated learning algorithms for training partially per...

0 Krishna Pillutla, et al. ∙

research

∙ 01/19/2022

On the Convergence Rates of Policy Gradient Methods

We consider infinite-horizon discounted Markov decision problems with fi...

0 Lin Xiao, et al. ∙

research

∙ 10/19/2021

Importance Estimation from Multiple Perspectives for Keyphrase Extraction

Keyphrase extraction is a fundamental task in Natural Language Processin...

0 Mingyang Song, et al. ∙

research

∙ 01/24/2021

Does Head Label Help for Long-Tailed Multi-Label Text Classification

Multi-label text classification (MLTC) aims to annotate documents with t...

0 Lin Xiao, et al. ∙

research

∙ 10/12/2020

Improving Self-supervised Pre-training via a Fully-Explored Masked Language Model

Masked Language Model (MLM) framework has been widely adopted for self-s...

0 Mingzhi Zheng, et al. ∙

research

∙ 05/30/2020

Jointly Modeling Intra- and Inter-transaction Dependencies with Hierarchical Attentive Transaction Embeddings for Next-item Recommendation

A transaction-based recommender system (TBRS) aims to predict the next i...

0 Shoujin Wang, et al. ∙

research

∙ 02/25/2020

Statistically Preconditioned Accelerated Gradient Method for Distributed Optimization

We consider the setting of distributed empirical risk minimization where...

0 Hadrien Hendrikx, et al. ∙

research

∙ 02/25/2020

Statistical Adaptive Stochastic Gradient Methods

We propose a statistical adaptive procedure called SALSA for automatical...

0 Pengchuan Zhang, et al. ∙

research

∙ 10/30/2019

Understanding the Role of Momentum in Stochastic Gradient Methods

The use of momentum in stochastic gradient methods has become a widespre...

0 Igor Gitman, et al. ∙

research

∙ 10/18/2019

Joint Computation and Communication Design for UAV-Assisted Mobile Edge Computing in IoT

Unmanned aerial vehicle (UAV)-assisted mobile edge computing (MEC) syste...

0 Tiankui Zhang, et al. ∙

research

∙ 09/21/2019

Using Statistics to Automate Stochastic Optimization

Despite the development of numerous adaptive optimizers, tuning the lear...

0 Hunter Lang, et al. ∙

research

∙ 08/29/2019

Multi-Level Composite Stochastic Optimization via Nested Variance Reduction

We consider multi-level composite optimization problems where each mappi...

0 Junyu Zhang, et al. ∙

research

∙ 06/24/2019

A Stochastic Composite Gradient Method with Incremental Variance Reduction

We consider the problem of minimizing the composition of a smooth (nonco...

6 Junyu Zhang, et al. ∙

research

∙ 05/26/2019

Hyperbolic Interaction Model For Hierarchical Multi-Label Classification

Different from the traditional classification tasks which assume mutual ...

0 Boli Chen, et al. ∙

research

∙ 05/24/2019

Label-aware Document Representation via Hybrid Attention for Extreme Multi-Label Text Classification

Extreme multi-label text classification (XMTC) aims at tagging a documen...

0 Xin Huang, et al. ∙

research

∙ 07/12/2018

Secrecy Energy Efficiency Maximization for UAV-Enabled Mobile Relaying

This paper investigates the secrecy energy efficiency (SEE) maximization...

0 Lin Xiao, et al. ∙

research

∙ 03/06/2018

Learning SMaLL Predictors

We present a new machine learning technique for training small resource-...

0 Vikas K. Garg, et al. ∙

research

∙ 12/29/2017

Smoothed Dual Embedding Control

We revisit the Bellman optimality equation with Nesterov's smoothing tec...

0 Bo Dai, et al. ∙

research

∙ 10/13/2017

DSCOVR: Randomized Primal-Dual Block Coordinate Algorithms for Asynchronous Distributed Optimization

Machine learning with big data often involves large optimization models....

0 Lin Xiao, et al. ∙

research

∙ 03/07/2017

Exploiting Strong Convexity from Data with Primal-Dual First-Order Algorithms

We consider empirical risk minimization of linear predictors with convex...

0 Jialei Wang, et al. ∙

research

∙ 02/25/2017

Stochastic Variance Reduction Methods for Policy Evaluation

Policy evaluation is a crucial step in many reinforcement-learning proce...

0 Simon S. Du, et al. ∙

research

∙ 01/01/2015

Communication-Efficient Distributed Optimization of Self-Concordant Empirical Loss

We consider distributed convex optimization problems originated from sam...

0 Yuchen Zhang, et al. ∙

research

∙ 03/19/2014

A Proximal Stochastic Gradient Method with Progressive Variance Reduction

We consider the problem of minimizing the sum of two convex functions: o...

0 Lin Xiao, et al. ∙

research

∙ 06/25/2013

A Randomized Nonmonotone Block Proximal Gradient Method for a Class of Structured Nonlinear Programming

We propose a randomized nonmonotone block proximal gradient (RNBPG) meth...

0 Zhaosong Lu, et al. ∙

research

∙ 05/21/2013

On the Complexity Analysis of Randomized Block-Coordinate Descent Methods

In this paper we analyze the randomized block-coordinate descent (RBCD) ...

0 Zhaosong Lu, et al. ∙

research

∙ 03/14/2012

A Proximal-Gradient Homotopy Method for the Sparse Least-Squares Problem

We consider solving the ℓ_1-regularized least-squares (ℓ_1-LS) problem i...

0 Lin Xiao, et al. ∙

Lin Xiao

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