b'Lijun Zhang'

research

∙ 09/16/2023

Efficient Methods for Non-stationary Online Learning

Non-stationary online learning has drawn much attention in recent years....

0 Peng Zhao, et al. ∙

research

∙ 08/11/2023

TrajPAC: Towards Robustness Verification of Pedestrian Trajectory Prediction Models

Robust pedestrian trajectory forecasting is crucial to developing safe a...

0 Liang Zhang, et al. ∙

research

∙ 08/08/2023

Cooperative Multi-agent Bandits: Distributed Algorithms with Optimal Individual Regret and Constant Communication Costs

Recently, there has been extensive study of cooperative multi-agent mult...

0 Lin Yang, et al. ∙

research

∙ 07/07/2023

Hyperspectral and Multispectral Image Fusion Using the Conditional Denoising Diffusion Probabilistic Model

Hyperspectral images (HSI) have a large amount of spectral information r...

0 Shuaikai Shi, et al. ∙

research

∙ 07/07/2023

Unsupervised Hyperspectral and Multispectral Images Fusion Based on the Cycle Consistency

Hyperspectral images (HSI) with abundant spectral information reflected ...

0 Shuaikai Shi, et al. ∙

research

∙ 06/13/2023

Learning Unnormalized Statistical Models via Compositional Optimization

Learning unnormalized statistical models (e.g., energy-based models) is ...

0 Wei Jiang, et al. ∙

research

∙ 05/30/2023

Blockwise Stochastic Variance-Reduced Methods with Parallel Speedup for Multi-Block Bilevel Optimization

In this paper, we consider non-convex multi-block bilevel optimization (...

0 Quanqi Hu, et al. ∙

research

∙ 05/20/2023

Non-stationary Online Convex Optimization with Arbitrary Delays

Online convex optimization (OCO) with arbitrary delays, in which gradien...

0 Yuanyu Wan, et al. ∙

research

∙ 05/20/2023

Dynamic Gradient Balancing for Enhanced Adversarial Attacks on Multi-Task Models

Multi-task learning (MTL) creates a single machine learning model called...

0 Lijun Zhang, et al. ∙

research

∙ 05/19/2023

Not All Semantics are Created Equal: Contrastive Self-supervised Learning with Automatic Temperature Individualization

In this paper, we aim to optimize a contrastive loss with individualized...

0 Zi-Hao Qiu, et al. ∙

research

∙ 05/19/2023

Non-stationary Projection-free Online Learning with Dynamic and Adaptive Regret Guarantees

Projection-free online learning has drawn increasing interest due to its...

0 Yibo Wang, et al. ∙

research

∙ 04/17/2023

Scenario Approach for Parametric Markov Models

In this paper, we propose an approximating framework for analyzing param...

0 Ying Liu, et al. ∙

research

∙ 04/13/2023

Structured Pruning for Multi-Task Deep Neural Networks

Although multi-task deep neural network (DNN) models have computation an...

0 Siddhant Garg, et al. ∙

research

∙ 02/18/2023

Stochastic Approximation Approaches to Group Distributionally Robust Optimization

This paper investigates group distributionally robust optimization (GDRO...

0 Lijun Zhang, et al. ∙

research

∙ 02/11/2023

Improved Dynamic Regret for Online Frank-Wolfe

To deal with non-stationary online problems with complex constraints, we...

0 Yuanyu Wan, et al. ∙

research

∙ 02/10/2023

Incremental Satisfiability Modulo Theory for Verification of Deep Neural Networks

Constraint solving is an elementary way for verification of deep neural ...

0 Pengfei Yang, et al. ∙

research

∙ 02/09/2023

Optimistic Online Mirror Descent for Bridging Stochastic and Adversarial Online Convex Optimization

Stochastically Extended Adversarial (SEA) model is introduced by Sachs e...

0 Sijia Chen, et al. ∙

research

∙ 11/23/2022

Safety Analysis of Autonomous Driving Systems Based on Model Learning

We present a practical verification method for safety analysis of the au...

0 Renjue Li, et al. ∙

research

∙ 10/08/2022

Break the Wall Between Homophily and Heterophily for Graph Representation Learning

Homophily and heterophily are intrinsic properties of graphs that descri...

11 Xiao Liu, et al. ∙

research

∙ 09/21/2022

ECSAS: Exploring Critical Scenarios from Action Sequence in Autonomous Driving

Critical scenario generation requires the ability of sampling critical c...

0 Shuting Kang, et al. ∙

research

∙ 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...

0 Wei Jiang, et al. ∙

research

∙ 06/01/2022

Defensive Design of Saturating Counters Based on Differential Privacy

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

0 Depeng Liu, et al. ∙

research

∙ 05/02/2022

Smoothed Online Convex Optimization Based on Discounted-Normal-Predictor

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

0 Lijun Zhang, et al. ∙

research

∙ 04/11/2022

Online Frank-Wolfe with Unknown Delays

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

0 Yuanyu Wan, et al. ∙

research

∙ 03/10/2022

A Tree-Structured Multi-Task Model Recommender

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

0 Lijun Zhang, et al. ∙

research

∙ 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...

0 Zhuoning Yuan, et al. ∙

research

∙ 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...

0 Zi-Hao Qiu, et al. ∙

research

∙ 02/15/2022

Optimal Algorithms for Stochastic Multi-Level Compositional Optimization

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

0 Wei Jiang, et al. ∙

research

∙ 01/23/2022

Weight Expansion: A New Perspective on Dropout and Generalization

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

0 Gaojie Jin, et al. ∙

research

∙ 12/29/2021

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

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

7 Peng Zhao, et al. ∙

research

∙ 11/19/2021

Toward Compact Parameter Representations for Architecture-Agnostic Neural Network Compression

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

11 Yuezhou Sun, et al. ∙

research

∙ 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...

0 Lijun Zhang, et al. ∙

research

∙ 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....

0 Fan Lu, et al. ∙

research

∙ 07/23/2021

Rethinking Hard-Parameter Sharing in Multi-Task Learning

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

0 Lijun Zhang, et al. ∙

research

∙ 07/18/2021

Probabilistic Verification of Neural Networks Against Group Fairness

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

0 Bing Sun, et al. ∙

research

∙ 07/02/2021

Momentum Accelerates the Convergence of Stochastic AUPRC Maximization

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

0 Guanghui Wang, et al. ∙

research

∙ 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...

0 Renjue Li, et al. ∙

research

∙ 05/08/2021

A Simple yet Universal Strategy for Online Convex Optimization

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

0 Lijun Zhang, et al. ∙

research

∙ 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...

0 Konstantin Kuznetsov, et al. ∙

research

∙ 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...

0 Sanqing Qu, et al. ∙

research

∙ 03/21/2021

Online Convex Optimization with Continuous Switching Constraint

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

0 Guanghui Wang, et al. ∙

research

∙ 03/21/2021

Online Strongly Convex Optimization with Unknown Delays

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

21 Yuanyu Wan, et al. ∙

research

∙ 03/20/2021

Projection-free Distributed Online Learning with Strongly Convex Losses

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

0 Yuanyu Wan, et al. ∙

research

∙ 03/09/2021

Non-stationary Linear Bandits Revisited

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

0 Peng Zhao, et al. ∙

research

∙ 02/13/2021

Revisiting Smoothed Online Learning

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

0 Lijun Zhang, et al. ∙

research

∙ 02/10/2021

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

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

20 Kai Chen, et al. ∙

research

∙ 01/25/2021

Probabilistic Robustness Analysis for DNNs based on PAC Learning

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

3 Renjue Li, et al. ∙

research

∙ 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...

0 Lijun Zhang, et al. ∙

research

∙ 10/16/2020

Projection-free Online Learning over Strongly Convex Sets

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

0 Yuanyu Wan, et al. ∙

research

∙ 10/15/2020

Improving Neural Network Verification through Spurious Region Guided Refinement

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

0 Pengfei Yang, et al. ∙

Lijun Zhang

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