Shiyu Chang

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ibm ∙ University of Illinois at Urbana-Champaign

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
207 publications
Xin Wang
200 publications
Yang Yang
135 publications
Li Zhang
131 publications
Zhangyang Wang
114 publications
Meng Wang
114 publications
Yang Zhang
110 publications
Pin-Yu Chen
100 publications
Cho-Jui Hsieh
99 publications
Yu Cheng
99 publications
William Yang Wang
99 publications

Complementary Evidence Identification in Open-Domain Question Answering

This paper proposes a new problem of complementary evidence identificati...
03/22/2021 ∙ by Xiangyang Mou, et al. ∙ 4 ∙ share

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Generating Adversarial Computer Programs using Optimized Obfuscations

Machine learning (ML) models that learn and predict properties of comput...
03/18/2021 ∙ by Shashank Srikant, et al. ∙ 12 ∙ share

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TransGAN: Two Transformers Can Make One Strong GAN

The recent explosive interest on transformers has suggested their potent...
02/14/2021 ∙ by Yifan Jiang, et al. ∙ 0 ∙ share

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Self-Progressing Robust Training

Enhancing model robustness under new and even adversarial environments i...
12/22/2020 ∙ by Minhao Cheng, et al. ∙ 9 ∙ share

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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-...
12/12/2020 ∙ by Tianlong Chen, et al. ∙ 9 ∙ share

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Training Stronger Baselines for Learning to Optimize

Learning to optimize (L2O) has gained increasing attention since classic...
10/18/2020 ∙ by Tianlong Chen, et al. ∙ 8 ∙ share

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

Interactive Fiction (IF) games with real human-written natural language ...
10/05/2020 ∙ by Xiaoxiao Guo, et al. ∙ 4 ∙ share

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Lifelong Object Detection

Recent advances in object detection have benefited significantly from ra...
09/02/2020 ∙ by Wang Zhou, et al. ∙ 3 ∙ share

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The Lottery Ticket Hypothesis for Pre-trained BERT Networks

In natural language processing (NLP), enormous pre-trained models like B...
07/23/2020 ∙ by Tianlong Chen, et al. ∙ 7 ∙ share

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Proper Network Interpretability Helps Adversarial Robustness in Classification

Recent works have empirically shown that there exist adversarial example...
06/26/2020 ∙ by Akhilan Boopathy, et al. ∙ 11 ∙ share

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Can 3D Adversarial Logos Cloak Humans?

With the trend of adversarial attacks, researchers attempt to fool train...
06/25/2020 ∙ by Tianlong Chen, et al. ∙ 5 ∙ share

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Unsupervised Speech Decomposition via Triple Information Bottleneck

Speech information can be roughly decomposed into four components: langu...
04/23/2020 ∙ by Kaizhi Qian, et al. ∙ 0 ∙ share

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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 ...
04/06/2020 ∙ by Yufei Feng, et al. ∙ 0 ∙ share

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

Pretrained models from self-supervision are prevalently used in fine-tun...
03/28/2020 ∙ by Tianlong Chen, et al. ∙ 11 ∙ share

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Invariant Rationalization

Selective rationalization improves neural network interpretability by id...
03/22/2020 ∙ by Shiyu Chang, et al. ∙ 5 ∙ share

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Rethinking Cooperative Rationalization: Introspective Extraction and Complement Control

Selective rationalization has become a common mechanism to ensure that p...
10/29/2019 ∙ by Mo Yu, et al. ∙ 0 ∙ share

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A Game Theoretic Approach to Class-wise Selective Rationalization

Selection of input features such as relevant pieces of text has become a...
10/28/2019 ∙ by Shiyu Chang, et al. ∙ 13 ∙ share

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An Efficient and Margin-Approaching Zero-Confidence Adversarial Attack

There are two major paradigms of white-box adversarial attacks that atte...
10/01/2019 ∙ by Yang Zhang, et al. ∙ 11 ∙ share

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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 ...
09/17/2019 ∙ by Wenhan Xiong, et al. ∙ 0 ∙ share

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Few-shot Text Classification with Distributional Signatures

In this paper, we explore meta-learning for few-shot text classification...
08/16/2019 ∙ by Yujia Bao, et al. ∙ 0 ∙ share

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Meta Reasoning over Knowledge Graphs

The ability to reason over learned knowledge is an innate ability for hu...
08/13/2019 ∙ by Hong Wang, et al. ∙ 0 ∙ share

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AutoGAN: Neural Architecture Search for Generative Adversarial Networks

Neural architecture search (NAS) has witnessed prevailing success in ima...
08/11/2019 ∙ by Xinyu Gong, et al. ∙ 10 ∙ share

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TWEETQA: A Social Media Focused Question Answering Dataset

With social media becoming increasingly pop-ular on which lots of news a...
07/14/2019 ∙ by Wenhan Xiong, et al. ∙ 0 ∙ share

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A Stratified Approach to Robustness for Randomly Smoothed Classifiers

Strong theoretical guarantees of robustness can be given for ensembles o...
06/12/2019 ∙ by Guang-He Lee, et al. ∙ 1 ∙ share

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Self-Supervised Learning for Contextualized Extractive Summarization

Existing models for extractive summarization are usually trained from sc...
06/11/2019 ∙ by Hong Wang, et al. ∙ 0 ∙ share

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Coupled Variational Recurrent Collaborative Filtering

We focus on the problem of streaming recommender system and explore nove...
06/11/2019 ∙ by Qingquan Song, et al. ∙ 0 ∙ share

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Improving Question Answering over Incomplete KBs with Knowledge-Aware Reader

We propose a new end-to-end question answering model, which learns to ag...
05/17/2019 ∙ by Wenhan Xiong, et al. ∙ 5 ∙ share

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Additive Adversarial Learning for Unbiased Authentication

Authentication is a task aiming to confirm the truth between data instan...
05/16/2019 ∙ by Jian Liang, et al. ∙ 6 ∙ share

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

Natural Language Sentence Matching (NLSM) has gained substantial attenti...
05/15/2019 ∙ by Guanhua Zhang, et al. ∙ 6 ∙ share

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Zero-Shot Voice Style Transfer with Only Autoencoder Loss

Non-parallel many-to-many voice conversion, as well as zero-shot voice c...
05/14/2019 ∙ by Kaizhi Qian, et al. ∙ 5 ∙ share

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

Non-parallel many-to-many voice conversion, as well as zero-shot voice c...
05/14/2019 ∙ by Kaizhi Qian, et al. ∙ 0 ∙ share

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Hybrid Reinforcement Learning with Expert State Sequences

Existing imitation learning approaches often require that the complete d...
03/11/2019 ∙ by Xiaoxiao Guo, et al. ∙ 8 ∙ share

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

Existing entity typing systems usually exploit the type hierarchy provid...
03/06/2019 ∙ by Wenhan Xiong, et al. ∙ 0 ∙ share

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Sentence Embedding Alignment for Lifelong Relation Extraction

Conventional approaches to relation extraction usually require a fixed s...
03/06/2019 ∙ by Hong Wang, et al. ∙ 0 ∙ share

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

Most approaches to extraction multiple relations from a paragraph requir...
02/04/2019 ∙ by Haoyu Wang, et al. ∙ 4 ∙ share

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

The training method of repetitively feeding all samples into a pre-defin...
11/23/2018 ∙ by Bowen Cheng, et al. ∙ 10 ∙ share

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Improving Reinforcement Learning Based Image Captioning with Natural Language Prior

Recently, Reinforcement Learning (RL) approaches have demonstrated advan...
09/13/2018 ∙ by Tszhang Guo, et al. ∙ 0 ∙ share

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Deriving Machine Attention from Human Rationales

Attention-based models are successful when trained on large amounts of d...
08/28/2018 ∙ by Yujia Bao, et al. ∙ 0 ∙ share

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One-Shot Relational Learning for Knowledge Graphs

Knowledge graphs (KGs) are the key components of various natural languag...
08/27/2018 ∙ by Wenhan Xiong, et al. ∙ 0 ∙ share

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Matrix Factorization on GPUs with Memory Optimization and Approximate Computing

Matrix factorization (MF) discovers latent features from observations, w...
08/11/2018 ∙ by Wei Tan, et al. ∙ 0 ∙ share

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Scheduled Policy Optimization for Natural Language Communication with Intelligent Agents

We investigate the task of learning to follow natural language instructi...
06/16/2018 ∙ by Wenhan Xiong, et al. ∙ 0 ∙ share

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A Co-Matching Model for Multi-choice Reading Comprehension

Multi-choice reading comprehension is a challenging task, which involves...
06/11/2018 ∙ by Shuohang Wang, et al. ∙ 0 ∙ share

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Zeroth-Order Stochastic Variance Reduction for Nonconvex Optimization

As application demands for zeroth-order (gradient-free) optimization acc...
05/25/2018 ∙ by Sijia Liu, et al. ∙ 0 ∙ share

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Diverse Few-Shot Text Classification with Multiple Metrics

We study few-shot learning in natural language domains. Compared to many...
05/19/2018 ∙ by Mo Yu, et al. ∙ 0 ∙ share

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Image Super-Resolution via Dual-State Recurrent Networks

Advances in image super-resolution (SR) have recently benefited signific...
05/07/2018 ∙ by Wei Han, et al. ∙ 0 ∙ share

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Deep Learning Based Speech Beamforming

Multi-channel speech enhancement with ad-hoc sensors has been a challeng...
02/15/2018 ∙ by Kaizhi Qian, et al. ∙ 0 ∙ share

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Evidence Aggregation for Answer Re-Ranking in Open-Domain Question Answering

A popular recent approach to answering open-domain questions is to first...
11/14/2017 ∙ by Shuohang Wang, et al. ∙ 0 ∙ share

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Dilated Recurrent Neural Networks

Learning with recurrent neural networks (RNNs) on long sequences is a no...
10/05/2017 ∙ by Shiyu Chang, et al. ∙ 0 ∙ share

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R^3: Reinforced Reader-Ranker for Open-Domain Question Answering

In recent years researchers have achieved considerable success applying ...
08/31/2017 ∙ by Shuohang Wang, et al. ∙ 0 ∙ share

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Robust Task Clustering for Deep Many-Task Learning

We investigate task clustering for deep-learning based multi-task and fe...
08/26/2017 ∙ by Mo Yu, et al. ∙ 0 ∙ share

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