Lijun Zhang

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University of Massachusetts Amherst

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Nanjing University

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Michigan State University

Assistant Professor at Penn State Milton S. Hershey Medical Center since 2014, Postdoctoral Fellow at Penn State University from 2013-2014, Data Informatics at Emory University from 2009-2013, Research Assistant at University of Louisville from 2005-2009, Software Engineer at SynTest Technologies, Inc. 2005, R&D Intern at PHILIPS Research East Asia 2003-2004, Project Manager at Qingdao Automation Research Institute from 1999-2002, PhD Computer Science at University of Louisville from 2005-2009

Featured Co-authors

Dacheng Tao
373 publications
Tie-Yan Liu
166 publications
Kai Chen
135 publications
Xiao Liu
125 publications
Yi Li
115 publications
Yan Yan
108 publications
Yong Li
90 publications
Tianbao Yang
77 publications
Wei Jiang
77 publications
Jun Sun
73 publications
Yi Xu
72 publications

∙ 07/18/2022

Multi-block-Single-probe Variance Reduced Estimator for Coupled Compositional Optimization

Variance reduction techniques such as SPIDER/SARAH/STORM have been exten...

Wei Jiang, et al. ∙

∙ 06/01/2022

Defensive Design of Saturating Counters Based on Differential Privacy

The saturating counter is the basic module of the dynamic branch predict...

Depeng Liu, et al. ∙

∙ 05/02/2022

Smoothed Online Convex Optimization Based on Discounted-Normal-Predictor

In this paper, we investigate an online prediction strategy named as Dis...

Lijun Zhang, et al. ∙

∙ 04/11/2022

Online Frank-Wolfe with Unknown Delays

The online Frank-Wolfe (OFW) method has gained much popularity for onlin...

Yuanyu Wan, et al. ∙

∙ 03/10/2022

A Tree-Structured Multi-Task Model Recommender

Tree-structured multi-task architectures have been employed to jointly t...

Lijun Zhang, et al. ∙

∙ 02/24/2022

Provable Stochastic Optimization for Global Contrastive Learning: Small Batch Does Not Harm Performance

In this paper, we study contrastive learning from an optimization perspe...

Zhuoning Yuan, et al. ∙

∙ 02/24/2022

Large-scale Stochastic Optimization of NDCG Surrogates for Deep Learning with Provable Convergence

NDCG, namely Normalized Discounted Cumulative Gain, is a widely used ran...

Zi-Hao Qiu, et al. ∙

∙ 02/15/2022

Optimal Algorithms for Stochastic Multi-Level Compositional Optimization

In this paper, we investigate the problem of stochastic multi-level comp...

Wei Jiang, et al. ∙

∙ 01/23/2022

Weight Expansion: A New Perspective on Dropout and Generalization

While dropout is known to be a successful regularization technique, insi...

Gaojie Jin, et al. ∙

∙ 12/29/2021

Adaptivity and Non-stationarity: Problem-dependent Dynamic Regret for Online Convex Optimization

We investigate online convex optimization in non-stationary environments...

Peng Zhao, et al. ∙

∙ 11/19/2021

Toward Compact Parameter Representations for Architecture-Agnostic Neural Network Compression

This paper investigates deep neural network (DNN) compression from the p...

Yuezhou Sun, et al. ∙

∙ 10/25/2021

AutoMTL: A Programming Framework for Automated Multi-Task Learning

Multi-task learning (MTL) jointly learns a set of tasks. It is a promisi...

Lijun Zhang, et al. ∙

∙ 07/26/2021

HRegNet: A Hierarchical Network for Large-scale Outdoor LiDAR Point Cloud Registration

Point cloud registration is a fundamental problem in 3D computer vision....

Fan Lu, et al. ∙

∙ 07/23/2021

Rethinking Hard-Parameter Sharing in Multi-Task Learning

Hard parameter sharing in multi-task learning (MTL) allows tasks to shar...

Lijun Zhang, et al. ∙

∙ 07/18/2021

Probabilistic Verification of Neural Networks Against Group Fairness

Fairness is crucial for neural networks which are used in applications w...

Bing Sun, et al. ∙

∙ 07/02/2021

Momentum Accelerates the Convergence of Stochastic AUPRC Maximization

In this paper, we study stochastic optimization of areas under precision...

Guanghui Wang, et al. ∙

∙ 06/05/2021

Ensemble Defense with Data Diversity: Weak Correlation Implies Strong Robustness

In this paper, we propose a framework of filter-based ensemble of deep n...

Renjue Li, et al. ∙

∙ 05/08/2021

A Simple yet Universal Strategy for Online Convex Optimization

Recently, several universal methods have been proposed for online convex...

Lijun Zhang, et al. ∙

∙ 05/07/2021

What do all these Buttons do? Statically Mining Android User Interfaces at Scale

We introduce FRONTMATTER: a tool to automatically mine both user interfa...

Konstantin Kuznetsov, et al. ∙

∙ 04/07/2021

ACM-Net: Action Context Modeling Network for Weakly-Supervised Temporal Action Localization

Weakly-supervised temporal action localization aims to localize action i...

Sanqing Qu, et al. ∙

∙ 03/21/2021

Online Convex Optimization with Continuous Switching Constraint

In many sequential decision making applications, the change of decision ...

Guanghui Wang, et al. ∙

∙ 03/21/2021

Online Strongly Convex Optimization with Unknown Delays

We investigate the problem of online convex optimization with unknown de...

Yuanyu Wan, et al. ∙

∙ 03/20/2021

Projection-free Distributed Online Learning with Strongly Convex Losses

To efficiently solve distributed online learning problems with complicat...

Yuanyu Wan, et al. ∙

∙ 03/09/2021

Non-stationary Linear Bandits Revisited

In this note, we revisit non-stationary linear bandits, a variant of sto...

Peng Zhao, et al. ∙

∙ 02/13/2021

Revisiting Smoothed Online Learning

In this paper, we revisit the problem of smoothed online learning, in wh...

Lijun Zhang, et al. ∙

∙ 02/10/2021

NAST: Non-Autoregressive Spatial-Temporal Transformer for Time Series Forecasting

Although Transformer has made breakthrough success in widespread domains...

Kai Chen, et al. ∙

∙ 01/25/2021

Probabilistic Robustness Analysis for DNNs based on PAC Learning

This paper proposes a black box based approach for analysing deep neural...

Renjue Li, et al. ∙

∙ 12/16/2020

SID-NISM: A Self-supervised Low-light Image Enhancement Framework

When capturing images in low-light conditions, the images often suffer f...

Lijun Zhang, et al. ∙

∙ 10/16/2020

Projection-free Online Learning over Strongly Convex Sets

To efficiently solve online problems with complicated constraints, proje...

Yuanyu Wan, et al. ∙

∙ 10/15/2020

Improving Neural Network Verification through Spurious Region Guided Refinement

We propose a spurious region guided refinement approach for robustness v...

Pengfei Yang, et al. ∙

∙ 10/12/2020

How does Weight Correlation Affect the Generalisation Ability of Deep Neural Networks

This paper studies the novel concept of weight correlation in deep neura...

Gaojie Jin, et al. ∙

∙ 09/08/2020

Approximate Multiplication of Sparse Matrices with Limited Space

Approximate matrix multiplication with limited space has received ever-i...

Yuanyu Wan, et al. ∙

∙ 08/04/2020

Verifying Pufferfish Privacy in Hidden Markov Models

Pufferfish is a Bayesian privacy framework for designing and analyzing p...

Depeng Liu, et al. ∙

∙ 07/07/2020

Dynamic Regret of Convex and Smooth Functions

We investigate online convex optimization in non-stationary environments...

Peng Zhao, et al. ∙

∙ 07/05/2020

Proving Non-Inclusion of Büchi Automata based on Monte Carlo Sampling

The search for a proof of correctness and the search for counterexamples...

Yong Li, et al. ∙

∙ 06/10/2020

Improved Analysis for Dynamic Regret of Strongly Convex and Smooth Functions

In this paper, we present an improved analysis for dynamic regret of str...

Peng Zhao, et al. ∙

∙ 05/18/2020

On the Power of Unambiguity in Büchi Complementation

In this work, we exploit the power of unambiguity for the complementatio...

Yong Li, et al. ∙

∙ 04/28/2020

Nearly Optimal Regret for Stochastic Linear Bandits with Heavy-Tailed Payoffs

In this paper, we study the problem of stochastic linear bandits with fi...

Bo Xue, et al. ∙

∙ 02/06/2020

Minimizing Dynamic Regret and Adaptive Regret Simultaneously

Regret minimization is treated as the golden rule in the traditional stu...

Lijun Zhang, et al. ∙

∙ 11/15/2019

Multi-attention Networks for Temporal Localization of Video-level Labels

Temporal localization remains an important challenge in video understand...

Lijun Zhang, et al. ∙

∙ 09/05/2019

More Adaptive Algorithms for Tracking the Best Expert

In this paper, we consider the problem of prediction with expert advice ...

Shiyin Lu, et al. ∙

∙ 08/26/2019

Stochastic Optimization for Non-convex Inf-Projection Problems

In this paper, we study a family of non-convex and possibly non-smooth i...

Yan Yan, et al. ∙

∙ 07/29/2019

Bandit Convex Optimization in Non-stationary Environments

Bandit Convex Optimization (BCO) is a fundamental framework for modeling...

Peng Zhao, et al. ∙

∙ 06/26/2019

Dual Adaptivity: A Universal Algorithm for Minimizing the Adaptive Regret of Convex Functions

To deal with changing environments, a new performance measure---adaptive...

Lijun Zhang, et al. ∙

∙ 05/30/2019

Multi-Objective Generalized Linear Bandits

In this paper, we study the multi-objective bandits (MOB) problem, where...

Shiyin Lu, et al. ∙

∙ 05/28/2019

Improving the Robustness of Deep Neural Networks via Adversarial Training with Triplet Loss

Recent studies have highlighted that deep neural networks (DNNs) are vul...

Pengcheng Li, et al. ∙

∙ 05/15/2019

Adaptivity and Optimality: A Universal Algorithm for Online Convex Optimization

In this paper, we study adaptive online convex optimization, and aim to ...

Guanghui Wang, et al. ∙

∙ 05/08/2019

SAdam: A Variant of Adam for Strongly Convex Functions

The Adam algorithm has become extremely popular for large-scale machine ...

Guanghui Wang, et al. ∙

∙ 04/27/2019

Prediction with Unpredictable Feature Evolution

Feature space can change or evolve when learning with streaming data. Se...

Bo-Jian Hou, et al. ∙

∙ 04/26/2019

Adaptive Regret of Convex and Smooth Functions

We investigate online convex optimization in changing environments, and ...

Lijun Zhang, et al. ∙