Liwei Wang

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University of Illinois at Urbana-Champaign ∙ Tencent ∙ Peking University

Assistant Professor at University of British Columbia, Okanagan Campus, BC, Canada, Senior Scientist at ABB Sweden Corporate Research from 2012-2014, Scientist at ABB Sweden Corporate Research from 2010-2012, Post Doctoral Research Fellow at The University of British Columbia 2010

Featured Co-authors

Luc Van Gool
208 publications
Jiashi Feng
151 publications
Yi Yang
149 publications
Wei Chen
141 publications
Jiebo Luo
120 publications
Ting Liu
108 publications
Dong Wang
107 publications
Li Zhang
102 publications
Tie-Yan Liu
101 publications
Zheng Zhang
89 publications
Cho-Jui Hsieh
84 publications

LID 2020: The Learning from Imperfect Data Challenge Results

Learning from imperfect data becomes an issue in many industrial applica...
10/17/2020 ∙ by Yunchao Wei, et al. ∙ 3 ∙ share

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Improved Analysis of Clipping Algorithms for Non-convex Optimization

Gradient clipping is commonly used in training deep neural networks part...
10/05/2020 ∙ by Bohang Zhang, et al. ∙ 0 ∙ share

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Sanity-Checking Pruning Methods: Random Tickets can Win the Jackpot

Network pruning is a method for reducing test-time computational resourc...
09/22/2020 ∙ by Jingtong Su, et al. ∙ 17 ∙ share

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GraphNorm: A Principled Approach to Accelerating Graph Neural Network Training

Normalization plays an important role in the optimization of deep neural...
09/07/2020 ∙ by Tianle Cai, et al. ∙ 0 ∙ share

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Efficient Reinforcement Learning in Factored MDPs with Application to Constrained RL

Reinforcement learning (RL) in episodic, factored Markov decision proces...
08/31/2020 ∙ by Xiaoyu Chen, et al. ∙ 9 ∙ share

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Improving One-stage Visual Grounding by Recursive Sub-query Construction

We improve one-stage visual grounding by addressing current limitations ...
08/03/2020 ∙ by Zhengyuan Yang, et al. ∙ 2 ∙ share

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RANDOM MASK: Towards Robust Convolutional Neural Networks

Robustness of neural networks has recently been highlighted by the adver...
07/27/2020 ∙ by Tiange Luo, et al. ∙ 19 ∙ share

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Transferred Discrepancy: Quantifying the Difference Between Representations

Understanding what information neural networks capture is an essential p...
07/24/2020 ∙ by Yunzhen Feng, et al. ∙ 0 ∙ share

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Comprehensive Image Captioning via Scene Graph Decomposition

We address the challenging problem of image captioning by revisiting the...
07/23/2020 ∙ by Yiwu Zhong, et al. ∙ 3 ∙ share

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RepPoints V2: Verification Meets Regression for Object Detection

Verification and regression are two general methodologies for prediction...
07/16/2020 ∙ by Yihong Chen, et al. ∙ 10 ∙ share

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Improving Weakly Supervised Visual Grounding by Contrastive Knowledge Distillation

Weakly supervised phrase grounding aims at learning region-phrase corres...
07/03/2020 ∙ by Liwei Wang, et al. ∙ 0 ∙ share

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Deep Generative Modeling for Mechanistic-based Learning and Design of Metamaterial Systems

Metamaterials are emerging as a new paradigmatic material system to rend...
06/27/2020 ∙ by Liwei Wang, et al. ∙ 10 ∙ share

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Data-Driven Topology Optimization with Multiclass Microstructures using Latent Variable Gaussian Process

The data-driven approach is emerging as a promising method for the topol...
06/27/2020 ∙ by Liwei Wang, et al. ∙ 8 ∙ share

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MC-BERT: Efficient Language Pre-Training via a Meta Controller

Pre-trained contextual representations (e.g., BERT) have become the foun...
06/10/2020 ∙ by Zhenhui Xu, et al. ∙ 0 ∙ share

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Multi-modal Feature Fusion with Feature Attention for VATEX Captioning Challenge 2020

This report describes our model for VATEX Captioning Challenge 2020. Fir...
06/05/2020 ∙ by Ke Lin, et al. ∙ 0 ∙ share

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(Locally) Differentially Private Combinatorial Semi-Bandits

In this paper, we study Combinatorial Semi-Bandits (CSB) that is an exte...
06/01/2020 ∙ by Xiaoyu Chen, et al. ∙ 15 ∙ share

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Locally Differentially Private (Contextual) Bandits Learning

We study locally differentially private (LDP) bandits learning in this p...
06/01/2020 ∙ by Kai Zheng, et al. ∙ 4 ∙ share

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METASET: Exploring Shape and Property Spaces for Data-Driven Metamaterials Design

Data-driven design of mechanical metamaterials is an increasingly popula...
06/01/2020 ∙ by Yu-Chin Chan, et al. ∙ 4 ∙ share

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Boosting Few-Shot Learning With Adaptive Margin Loss

Few-shot learning (FSL) has attracted increasing attention in recent yea...
05/28/2020 ∙ by Aoxue Li, et al. ∙ 5 ∙ share

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Improve bone age assessment by learning from anatomical local regions

Skeletal bone age assessment (BAA), as an essential imaging examination,...
05/27/2020 ∙ by Dong Wang, et al. ∙ 16 ∙ share

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MART: Memory-Augmented Recurrent Transformer for Coherent Video Paragraph Captioning

Generating multi-sentence descriptions for videos is one of the most cha...
05/11/2020 ∙ by Jie Lei, et al. ∙ 1 ∙ share

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Memory Enhanced Global-Local Aggregation for Video Object Detection

How do humans recognize an object in a piece of video? Due to the deteri...
03/26/2020 ∙ by Yihong Chen, et al. ∙ 4 ∙ share

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Learning to Group: A Bottom-Up Framework for 3D Part Discovery in Unseen Categories

We address the problem of discovering 3D parts for objects in unseen cat...
02/16/2020 ∙ by Tiange Luo, et al. ∙ 11 ∙ share

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On Layer Normalization in the Transformer Architecture

The Transformer is widely used in natural language processing tasks. To ...
02/12/2020 ∙ by Ruibin Xiong, et al. ∙ 0 ∙ share

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Combinatorial Semi-Bandit in the Non-Stationary Environment

In this paper, we investigate the non-stationary combinatorial semi-band...
02/10/2020 ∙ by Wei Chen, et al. ∙ 13 ∙ share

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MACER: Attack-free and Scalable Robust Training via Maximizing Certified Radius

Adversarial training is one of the most popular ways to learn robust mod...
01/08/2020 ∙ by Runtian Zhai, et al. ∙ 4 ∙ share

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Dense RepPoints: Representing Visual Objects with Dense Point Sets

We present an object representation, called Dense RepPoints, for flexibl...
12/24/2019 ∙ by Ze Yang, et al. ∙ 8 ∙ share

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Defective Convolutional Layers Learn Robust CNNs

Robustness of convolutional neural networks has recently been highlighte...
11/19/2019 ∙ by Tiange Luo, et al. ∙ 19 ∙ share

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Development of Clinical Concept Extraction Applications: A Methodology Review

Our study provided a review of the development of clinical concept extra...
10/24/2019 ∙ by Sunyang Fu, et al. ∙ 0 ∙ share

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A Review of the End-to-End Methodologies for Clinical Concept Extraction

Our study provided a review of the concept extraction literature from Ja...
10/24/2019 ∙ by Sunyang Fu, et al. ∙ 0 ∙ share

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On the Anomalous Generalization of GANs

Generative models, especially Generative Adversarial Networks (GANs), ha...
09/27/2019 ∙ by Jinchen Xuan, et al. ∙ 46 ∙ share

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Robust Local Features for Improving the Generalization of Adversarial Training

Adversarial training has been demonstrated as one of the most effective ...
09/23/2019 ∙ by Chubiao Song, et al. ∙ 11 ∙ share

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Hint-Based Training for Non-Autoregressive Machine Translation

Due to the unparallelizable nature of the autoregressive factorization, ...
09/15/2019 ∙ by Zhuohan Li, et al. ∙ 0 ∙ share

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McDiarmid-Type Inequalities for Graph-Dependent Variables and Stability Bounds

A crucial assumption in most statistical learning theory is that samples...
09/05/2019 ∙ by Zhang, et al. ∙ 0 ∙ share

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A Fast and Accurate One-Stage Approach to Visual Grounding

We propose a simple, fast, and accurate one-stage approach to visual gro...
08/18/2019 ∙ by Zhengyuan Yang, et al. ∙ 1 ∙ share

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Nesterov Accelerated Gradient and Scale Invariance for Improving Transferability of Adversarial Examples

Recent evidence suggests that deep neural networks (DNNs) are vulnerable...
08/17/2019 ∙ by Jiadong Lin, et al. ∙ 3 ∙ share

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Few-Shot Learning with Global Class Representations

In this paper, we propose to tackle the challenging few-shot learning (F...
08/14/2019 ∙ by Tiange Luo, et al. ∙ 0 ∙ share

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Representation Degeneration Problem in Training Natural Language Generation Models

We study an interesting problem in training neural network-based models ...
07/28/2019 ∙ by Jun Gao, et al. ∙ 0 ∙ share

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Cross-lingual Data Transformation and Combination for Text Classification

Text classification is a fundamental task for text data mining. In order...
06/23/2019 ∙ by Jun Jiang, et al. ∙ 0 ∙ share

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Convergence of Adversarial Training in Overparametrized Networks

Neural networks are vulnerable to adversarial examples, i.e. inputs that...
06/19/2019 ∙ by Ruiqi Gao, et al. ∙ 0 ∙ share

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Understanding and Improving Transformer From a Multi-Particle Dynamic System Point of View

The Transformer architecture is widely used in natural language processi...
06/06/2019 ∙ by Yiping Lu, et al. ∙ 0 ∙ share

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Adversarially Robust Generalization Just Requires More Unlabeled Data

Neural network robustness has recently been highlighted by the existence...
06/03/2019 ∙ by Runtian Zhai, et al. ∙ 0 ∙ share

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Equipping Experts/Bandits with Long-term Memory

We propose the first reduction-based approach to obtaining long-term mem...
05/30/2019 ∙ by Kai Zheng, et al. ∙ 0 ∙ share

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A Gram-Gauss-Newton Method Learning Overparameterized Deep Neural Networks for Regression Problems

First-order methods such as stochastic gradient descent (SGD) are curren...
05/28/2019 ∙ by Tianle Cai, et al. ∙ 0 ∙ share

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Cross-lingual Knowledge Graph Alignment via Graph Matching Neural Network

Previous cross-lingual knowledge graph (KG) alignment studies rely on en...
05/28/2019 ∙ by Kun Xu, et al. ∙ 0 ∙ share

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RepPoints: Point Set Representation for Object Detection

Modern object detectors rely heavily on rectangular bounding boxes, such...
04/25/2019 ∙ by Ze Yang, et al. ∙ 0 ∙ share

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Distributed Bandit Learning: How Much Communication is Needed to Achieve (Near) Optimal Regret

We study the communication complexity of distributed multi-armed bandits...
04/12/2019 ∙ by Yuanhao Wang, et al. ∙ 0 ∙ share

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Mimicking the In-Camera Color Pipeline for Camera-Aware Object Compositing

We present a method for compositing virtual objects into a photograph su...
03/27/2019 ∙ by Jun Gao, et al. ∙ 0 ∙ share

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Q-learning with UCB Exploration is Sample Efficient for Infinite-Horizon MDP

A fundamental question in reinforcement learning is whether model-free a...
01/27/2019 ∙ by Kefan Dong, et al. ∙ 0 ∙ share

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CREATE: Cohort Retrieval Enhanced by Analysis of Text from Electronic Health Records using OMOP Common Data Model

Background: Widespread adoption of electronic health records (EHRs) has ...
01/22/2019 ∙ by Sijia Liu, et al. ∙ 0 ∙ share

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