Lin Xiao

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

Masked Language Model (MLM) framework has been widely adopted for self-s...
10/12/2020 ∙ by Mingzhi Zheng, et al. ∙ 0 ∙ share

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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...
05/30/2020 ∙ by Shoujin Wang, et al. ∙ 0 ∙ share

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Statistically Preconditioned Accelerated Gradient Method for Distributed Optimization

We consider the setting of distributed empirical risk minimization where...
02/25/2020 ∙ by Hadrien Hendrikx, et al. ∙ 0 ∙ share

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Statistical Adaptive Stochastic Gradient Methods

We propose a statistical adaptive procedure called SALSA for automatical...
02/25/2020 ∙ by Pengchuan Zhang, et al. ∙ 0 ∙ share

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Understanding the Role of Momentum in Stochastic Gradient Methods

The use of momentum in stochastic gradient methods has become a widespre...
10/30/2019 ∙ by Igor Gitman, et al. ∙ 0 ∙ share

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

Unmanned aerial vehicle (UAV)-assisted mobile edge computing (MEC) syste...
10/18/2019 ∙ by Tiankui Zhang, et al. ∙ 0 ∙ share

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Using Statistics to Automate Stochastic Optimization

Despite the development of numerous adaptive optimizers, tuning the lear...
09/21/2019 ∙ by Hunter Lang, et al. ∙ 0 ∙ share

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Multi-Level Composite Stochastic Optimization via Nested Variance Reduction

We consider multi-level composite optimization problems where each mappi...
08/29/2019 ∙ by Junyu Zhang, et al. ∙ 0 ∙ share

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A Stochastic Composite Gradient Method with Incremental Variance Reduction

We consider the problem of minimizing the composition of a smooth (nonco...
06/24/2019 ∙ by Junyu Zhang, et al. ∙ 6 ∙ share

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Hyperbolic Interaction Model For Hierarchical Multi-Label Classification

Different from the traditional classification tasks which assume mutual ...
05/26/2019 ∙ by Boli Chen, et al. ∙ 0 ∙ share

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

Extreme multi-label text classification (XMTC) aims at tagging a documen...
05/24/2019 ∙ by Xin Huang, et al. ∙ 0 ∙ share

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Secrecy Energy Efficiency Maximization for UAV-Enabled Mobile Relaying

This paper investigates the secrecy energy efficiency (SEE) maximization...
07/12/2018 ∙ by Lin Xiao, et al. ∙ 0 ∙ share

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Learning SMaLL Predictors

We present a new machine learning technique for training small resource-...
03/06/2018 ∙ by Vikas K. Garg, et al. ∙ 0 ∙ share

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Smoothed Dual Embedding Control

We revisit the Bellman optimality equation with Nesterov's smoothing tec...
12/29/2017 ∙ by Bo Dai, et al. ∙ 0 ∙ share

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

Machine learning with big data often involves large optimization models....
10/13/2017 ∙ by Lin Xiao, et al. ∙ 0 ∙ share

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

We consider empirical risk minimization of linear predictors with convex...
03/07/2017 ∙ by Jialei Wang, et al. ∙ 0 ∙ share

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Stochastic Variance Reduction Methods for Policy Evaluation

Policy evaluation is a crucial step in many reinforcement-learning proce...
02/25/2017 ∙ by Simon S. Du, et al. ∙ 0 ∙ share

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Communication-Efficient Distributed Optimization of Self-Concordant Empirical Loss

We consider distributed convex optimization problems originated from sam...
01/01/2015 ∙ by Yuchen Zhang, et al. ∙ 0 ∙ share

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A Proximal Stochastic Gradient Method with Progressive Variance Reduction

We consider the problem of minimizing the sum of two convex functions: o...
03/19/2014 ∙ by Lin Xiao, et al. ∙ 0 ∙ share

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

We propose a randomized nonmonotone block proximal gradient (RNBPG) meth...
06/25/2013 ∙ by Zhaosong Lu, et al. ∙ 0 ∙ share

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On the Complexity Analysis of Randomized Block-Coordinate Descent Methods

In this paper we analyze the randomized block-coordinate descent (RBCD) ...
05/21/2013 ∙ by Zhaosong Lu, et al. ∙ 0 ∙ share

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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...
03/14/2012 ∙ by Lin Xiao, et al. ∙ 0 ∙ share

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Lin Xiao

Featured Co-authors

Francis Bach

Tong Zhang

Qiang Liu

Le Song

Lihong Li

Bo Dai

Simon S. Du

Sébastien Bubeck

Xin Huang

Dinghan Shen

Jianshu Chen

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

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

Statistically Preconditioned Accelerated Gradient Method for Distributed Optimization

Statistical Adaptive Stochastic Gradient Methods

Understanding the Role of Momentum in Stochastic Gradient Methods

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

Using Statistics to Automate Stochastic Optimization

Multi-Level Composite Stochastic Optimization via Nested Variance Reduction

A Stochastic Composite Gradient Method with Incremental Variance Reduction

Hyperbolic Interaction Model For Hierarchical Multi-Label Classification

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

Secrecy Energy Efficiency Maximization for UAV-Enabled Mobile Relaying

Learning SMaLL Predictors

Smoothed Dual Embedding Control

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

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

Stochastic Variance Reduction Methods for Policy Evaluation

Communication-Efficient Distributed Optimization of Self-Concordant Empirical Loss

A Proximal Stochastic Gradient Method with Progressive Variance Reduction

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

On the Complexity Analysis of Randomized Block-Coordinate Descent Methods

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