Shiyu Chang

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ibm

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University of Illinois at Urbana-Champaign

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The Regents of the University of California

Research Staff Member at IBM T.J. Watson Research Center since 2016, Research Assistant at University of Illinois at Urbana-Champaign from 2011-2016, Algorithmic Trader Intern at Jump Trading LLC 2016, Research Intern at Yahoo Labs 2015, Research Intern at IBM T.J. Watson Research Center 2014, Research Intern at Samsung Research America 2014, Research Intern at IBM TJ Watson Research Center 2013, Research Intern at Microsoft Research Asia 2012, Software Engineering Intern at Wolfram Research 2011

Featured Co-authors

Wei Zhang
282 publications
Xin Wang
282 publications
Yang Yang
176 publications
Li Zhang
167 publications
Zhangyang Wang
164 publications
Meng Wang
147 publications
Yang Zhang
141 publications
Pin-Yu Chen
135 publications
Cho-Jui Hsieh
122 publications
William Yang Wang
122 publications
Yu Cheng
116 publications

∙ 04/15/2022

Incremental Prompting: Episodic Memory Prompt for Lifelong Event Detection

Lifelong event detection aims to incrementally update a model with new e...

Minqian Liu, et al. ∙

∙ 03/27/2022

How to Robustify Black-Box ML Models? A Zeroth-Order Optimization Perspective

The lack of adversarial robustness has been recognized as an important i...

Yimeng Zhang, et al. ∙

∙ 03/12/2022

Optimizer Amalgamation

Selecting an appropriate optimizer for a given problem is of major inter...

Tianshu Huang, et al. ∙

∙ 12/23/2021

Revisiting and Advancing Fast Adversarial Training Through The Lens of Bi-Level Optimization

Adversarial training (AT) has become a widely recognized defense mechani...

Yihua Zhang, et al. ∙

∙ 10/26/2021

Understanding Interlocking Dynamics of Cooperative Rationalization

Selective rationalization explains the prediction of complex neural netw...

Mo Yu, et al. ∙

∙ 10/14/2021

Query and Extract: Refining Event Extraction as Type-oriented Binary Decoding

Event extraction is typically modeled as a multi-class classification pr...

Sijia Wang, et al. ∙

∙ 10/04/2021

On the Interplay Between Sparsity, Naturalness, Intelligibility, and Prosody in Speech Synthesis

Are end-to-end text-to-speech (TTS) models over-parametrized? To what ex...

Cheng-I Jeff Lai, et al. ∙

∙ 06/16/2021

Global Rhythm Style Transfer Without Text Transcriptions

Prosody plays an important role in characterizing the style of a speaker...

Kaizhi Qian, et al. ∙

∙ 06/15/2021

Learning Stable Classifiers by Transferring Unstable Features

We study transfer learning in the presence of spurious correlations. We ...

Yujia Bao, et al. ∙

∙ 06/10/2021

PARP: Prune, Adjust and Re-Prune for Self-Supervised Speech Recognition

Recent work on speech self-supervised learning (speech SSL) demonstrated...

Cheng-I Jeff Lai, et al. ∙

∙ 05/26/2021

Predict then Interpolate: A Simple Algorithm to Learn Stable Classifiers

We propose Predict then Interpolate (PI), a simple algorithm for learnin...

Yujia Bao, et al. ∙

∙ 03/22/2021

Complementary Evidence Identification in Open-Domain Question Answering

This paper proposes a new problem of complementary evidence identificati...

Xiangyang Mou, et al. ∙

∙ 03/18/2021

Generating Adversarial Computer Programs using Optimized Obfuscations

Machine learning (ML) models that learn and predict properties of comput...

Shashank Srikant, et al. ∙

∙ 02/14/2021

TransGAN: Two Transformers Can Make One Strong GAN

The recent explosive interest on transformers has suggested their potent...

Yifan Jiang, et al. ∙

∙ 12/22/2020

Self-Progressing Robust Training

Enhancing model robustness under new and even adversarial environments i...

Minhao Cheng, et al. ∙

∙ 12/12/2020

The Lottery Tickets Hypothesis for Supervised and Self-supervised Pre-training in Computer Vision Models

The computer vision world has been re-gaining enthusiasm in various pre-...

Tianlong Chen, et al. ∙

∙ 10/18/2020

Training Stronger Baselines for Learning to Optimize

Learning to optimize (L2O) has gained increasing attention since classic...

Tianlong Chen, et al. ∙

∙ 10/05/2020

Interactive Fiction Game Playing as Multi-Paragraph Reading Comprehension with Reinforcement Learning

Interactive Fiction (IF) games with real human-written natural language ...

Xiaoxiao Guo, et al. ∙

∙ 09/02/2020

Lifelong Object Detection

Recent advances in object detection have benefited significantly from ra...

Wang Zhou, et al. ∙

∙ 07/23/2020

The Lottery Ticket Hypothesis for Pre-trained BERT Networks

In natural language processing (NLP), enormous pre-trained models like B...

Tianlong Chen, et al. ∙

∙ 06/26/2020

Proper Network Interpretability Helps Adversarial Robustness in Classification

Recent works have empirically shown that there exist adversarial example...

Akhilan Boopathy, et al. ∙

∙ 06/25/2020

Can 3D Adversarial Logos Cloak Humans?

With the trend of adversarial attacks, researchers attempt to fool train...

Tianlong Chen, et al. ∙

∙ 04/23/2020

Unsupervised Speech Decomposition via Triple Information Bottleneck

Speech information can be roughly decomposed into four components: langu...

Kaizhi Qian, et al. ∙

∙ 04/06/2020

Learning to Recover Reasoning Chains for Multi-Hop Question Answering via Cooperative Games

We propose the new problem of learning to recover reasoning chains from ...

Yufei Feng, et al. ∙

∙ 03/28/2020

Adversarial Robustness: From Self-Supervised Pre-Training to Fine-Tuning

Pretrained models from self-supervision are prevalently used in fine-tun...

Tianlong Chen, et al. ∙

∙ 03/22/2020

Invariant Rationalization

Selective rationalization improves neural network interpretability by id...

Shiyu Chang, et al. ∙

∙ 10/29/2019

Rethinking Cooperative Rationalization: Introspective Extraction and Complement Control

Selective rationalization has become a common mechanism to ensure that p...

Mo Yu, et al. ∙

∙ 10/28/2019

A Game Theoretic Approach to Class-wise Selective Rationalization

Selection of input features such as relevant pieces of text has become a...

Shiyu Chang, et al. ∙

∙ 10/01/2019

An Efficient and Margin-Approaching Zero-Confidence Adversarial Attack

There are two major paradigms of white-box adversarial attacks that atte...

Yang Zhang, et al. ∙

∙ 09/17/2019

Simple yet Effective Bridge Reasoning for Open-Domain Multi-Hop Question Answering

A key challenge of multi-hop question answering (QA) in the open-domain ...

Wenhan Xiong, et al. ∙

∙ 08/16/2019

Few-shot Text Classification with Distributional Signatures

In this paper, we explore meta-learning for few-shot text classification...

Yujia Bao, et al. ∙

∙ 08/13/2019

Meta Reasoning over Knowledge Graphs

The ability to reason over learned knowledge is an innate ability for hu...

Hong Wang, et al. ∙

∙ 08/11/2019

AutoGAN: Neural Architecture Search for Generative Adversarial Networks

Neural architecture search (NAS) has witnessed prevailing success in ima...

Xinyu Gong, et al. ∙

∙ 07/14/2019

TWEETQA: A Social Media Focused Question Answering Dataset

With social media becoming increasingly pop-ular on which lots of news a...

Wenhan Xiong, et al. ∙

∙ 06/12/2019

A Stratified Approach to Robustness for Randomly Smoothed Classifiers

Strong theoretical guarantees of robustness can be given for ensembles o...

Guang-He Lee, et al. ∙

∙ 06/11/2019

Self-Supervised Learning for Contextualized Extractive Summarization

Existing models for extractive summarization are usually trained from sc...

Hong Wang, et al. ∙

∙ 06/11/2019

Coupled Variational Recurrent Collaborative Filtering

We focus on the problem of streaming recommender system and explore nove...

Qingquan Song, et al. ∙

∙ 05/17/2019

Improving Question Answering over Incomplete KBs with Knowledge-Aware Reader

We propose a new end-to-end question answering model, which learns to ag...

Wenhan Xiong, et al. ∙

∙ 05/16/2019

Additive Adversarial Learning for Unbiased Authentication

Authentication is a task aiming to confirm the truth between data instan...

Jian Liang, et al. ∙

∙ 05/15/2019

Selection Bias Explorations and Debias Methods for Natural Language Sentence Matching Datasets

Natural Language Sentence Matching (NLSM) has gained substantial attenti...

Guanhua Zhang, et al. ∙

∙ 05/14/2019

Zero-Shot Voice Style Transfer with Only Autoencoder Loss

Non-parallel many-to-many voice conversion, as well as zero-shot voice c...

Kaizhi Qian, et al. ∙

∙ 05/14/2019

AUTOVC: Zero-Shot Voice Style Transfer with Only Autoencoder Loss

Non-parallel many-to-many voice conversion, as well as zero-shot voice c...

Kaizhi Qian, et al. ∙

∙ 03/11/2019

Hybrid Reinforcement Learning with Expert State Sequences

Existing imitation learning approaches often require that the complete d...

Xiaoxiao Guo, et al. ∙

∙ 03/06/2019

Imposing Label-Relational Inductive Bias for Extremely Fine-Grained Entity Typing

Existing entity typing systems usually exploit the type hierarchy provid...

Wenhan Xiong, et al. ∙

∙ 03/06/2019

Sentence Embedding Alignment for Lifelong Relation Extraction

Conventional approaches to relation extraction usually require a fixed s...

Hong Wang, et al. ∙

∙ 02/04/2019

Extracting Multiple-Relations in One-Pass with Pre-Trained Transformers

Most approaches to extraction multiple relations from a paragraph requir...

Haoyu Wang, et al. ∙

∙ 11/23/2018

Revisiting Pre-training: An Efficient Training Method for Image Classification

The training method of repetitively feeding all samples into a pre-defin...

Bowen Cheng, et al. ∙

∙ 09/13/2018

Improving Reinforcement Learning Based Image Captioning with Natural Language Prior

Recently, Reinforcement Learning (RL) approaches have demonstrated advan...

Tszhang Guo, et al. ∙

∙ 08/28/2018

Deriving Machine Attention from Human Rationales

Attention-based models are successful when trained on large amounts of d...

Yujia Bao, et al. ∙

∙ 08/27/2018

One-Shot Relational Learning for Knowledge Graphs

Knowledge graphs (KGs) are the key components of various natural languag...

Wenhan Xiong, et al. ∙