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

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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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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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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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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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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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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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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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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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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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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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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Jointly Attentive Spatial-Temporal Pooling Networks for Video-based Person Re-Identification

Person Re-Identification (person re-id) is a crucial task as its applica...
08/03/2017 ∙ by Shuangjie Xu, et al. ∙ 0 ∙ share

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Fast Generation for Convolutional Autoregressive Models

Convolutional autoregressive models have recently demonstrated state-of-...
04/20/2017 ∙ by Prajit Ramachandran, et al. ∙ 0 ∙ share

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Stacked Approximated Regression Machine: A Simple Deep Learning Approach

With the agreement of my coauthors, I Zhangyang Wang would like to withd...
08/14/2016 ∙ by Zhangyang Wang, et al. ∙ 0 ∙ share

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Learning A Deep ℓ_∞ Encoder for Hashing

We investigate the ℓ_∞-constrained representation which demonstrates rob...
04/06/2016 ∙ by Zhangyang Wang, et al. ∙ 0 ∙ share

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Brain-Inspired Deep Networks for Image Aesthetics Assessment

Image aesthetics assessment has been challenging due to its subjective n...
01/16/2016 ∙ by Zhangyang Wang, et al. ∙ 0 ∙ share

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Studying Very Low Resolution Recognition Using Deep Networks

Visual recognition research often assumes a sufficient resolution of the...
01/16/2016 ∙ by Zhangyang Wang, et al. ∙ 0 ∙ share

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D^3: Deep Dual-Domain Based Fast Restoration of JPEG-Compressed Images

In this paper, we design a Deep Dual-Domain (D^3) based fast restoration...
01/16/2016 ∙ by Zhangyang Wang, et al. ∙ 0 ∙ share

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Learning A Task-Specific Deep Architecture For Clustering

While sparse coding-based clustering methods have shown to be successful...
09/01/2015 ∙ by Zhangyang Wang, et al. ∙ 0 ∙ share

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Self-Tuned Deep Super Resolution

Deep learning has been successfully applied to image super resolution (S...
04/22/2015 ∙ by Zhangyang Wang, et al. ∙ 0 ∙ share

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Learning Super-Resolution Jointly from External and Internal Examples

Single image super-resolution (SR) aims to estimate a high-resolution (H...
03/03/2015 ∙ by Zhangyang Wang, et al. ∙ 0 ∙ share

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Scalable Similarity Learning using Large Margin Neighborhood Embedding

Classifying large-scale image data into object categories is an importan...
04/24/2014 ∙ by Zhaowen Wang, et al. ∙ 0 ∙ share

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Blind Image Deblurring by Spectral Properties of Convolution Operators

In this paper, we study the problem of recovering a sharp version of a g...
09/10/2012 ∙ by Guangcan Liu, 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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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Shiyu Chang

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