Yexiang Xue

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Purdue University

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cornell university

PhD candidate in the Department of Computer Science at Cornell University, Research Intern at Microsoft year 2013

research

∙ 07/15/2022

Bootstrap State Representation using Style Transfer for Better Generalization in Deep Reinforcement Learning

Deep Reinforcement Learning (RL) agents often overfit the training envir...

Md Masudur Rahman, et al. ∙

research

∙ 03/22/2022

Provable Constrained Stochastic Convex Optimization with XOR-Projected Gradient Descent

Provably solving stochastic convex optimization problems with constraint...

Fan Ding, et al. ∙

research

∙ 10/06/2021

A Fast Randomized Algorithm for Massive Text Normalization

Many popular machine learning techniques in natural language processing ...

Nan Jiang, et al. ∙

research

∙ 11/30/2020

From the DESK (Dexterous Surgical Skill) to the Battlefield – A Robotics Exploratory Study

Short response time is critical for future military medical operations i...

Glebys T. Gonzalez, et al. ∙

research

∙ 11/24/2020

Language Generation via Combinatorial Constraint Satisfaction: A Tree Search Enhanced Monte-Carlo Approach

Generating natural language under complex constraints is a principled fo...

Maosen Zhang, et al. ∙

research

∙ 10/13/2019

AdaWISH: Faster Discrete Integration via Adaptive Quantiles

Discrete integration in a high dimensional space of n variables poses fu...

Fan Ding, et al. ∙

research

∙ 03/03/2019

DESK: A Robotic Activity Dataset for Dexterous Surgical Skills Transfer to Medical Robots

Datasets are an essential component for training effective machine learn...

Naveen Madapana, et al. ∙

research

∙ 05/07/2018

Imitation Refinement

Many real-world tasks involve identifying patterns from data satisfying ...

Junwen Bai, et al. ∙

research

∙ 03/22/2018

End-to-End Learning for the Deep Multivariate Probit Model

The multivariate probit model (MVP) is a popular classic model for study...

Di Chen, et al. ∙

research

∙ 11/18/2017

Scalable Relaxations of Sparse Packing Constraints: Optimal Biocontrol in Predator-Prey Network

Cascades represent rapid changes in networks. A cascading phenomenon of ...

Johan Bjorck, et al. ∙

research

∙ 09/17/2017

Multi-Entity Dependence Learning with Rich Context via Conditional Variational Auto-encoder

Multi-Entity Dependence Learning (MEDL) explores conditional correlation...

Luming Tang, et al. ∙

research

∙ 05/23/2017

XOR-Sampling for Network Design with Correlated Stochastic Events

Many network optimization problems can be formulated as stochastic netwo...

Xiaojian Wu, et al. ∙

research

∙ 10/08/2016

Solving Marginal MAP Problems with NP Oracles and Parity Constraints

Arising from many applications at the intersection of decision making an...

Yexiang Xue, et al. ∙

research

∙ 10/03/2016

Phase-Mapper: An AI Platform to Accelerate High Throughput Materials Discovery

High-Throughput materials discovery involves the rapid synthesis, measur...

Yexiang Xue, et al. ∙

research

∙ 09/28/2016

Deep Multi-Species Embedding

Understanding how species are distributed across landscapes over time is...

Di Chen, et al. ∙

research

∙ 08/17/2015

Variable Elimination in the Fourier Domain

The ability to represent complex high dimensional probability distributi...

Yexiang Xue, et al. ∙

Yexiang Xue

Featured Co-authors

Lei Li

Stefano Ermon

Nan Jiang

Ashish Sabharwal

Zhiyuan Li

Carla P. Gomes

Bart Selman

Di Chen

Ronan Le Bras

Shuo Chen

Carla Gomes

Bootstrap State Representation using Style Transfer for Better Generalization in Deep Reinforcement Learning

Provable Constrained Stochastic Convex Optimization with XOR-Projected Gradient Descent

A Fast Randomized Algorithm for Massive Text Normalization

From the DESK (Dexterous Surgical Skill) to the Battlefield – A Robotics Exploratory Study

Language Generation via Combinatorial Constraint Satisfaction: A Tree Search Enhanced Monte-Carlo Approach

AdaWISH: Faster Discrete Integration via Adaptive Quantiles

DESK: A Robotic Activity Dataset for Dexterous Surgical Skills Transfer to Medical Robots

Imitation Refinement

End-to-End Learning for the Deep Multivariate Probit Model

Scalable Relaxations of Sparse Packing Constraints: Optimal Biocontrol in Predator-Prey Network

Multi-Entity Dependence Learning with Rich Context via Conditional Variational Auto-encoder

XOR-Sampling for Network Design with Correlated Stochastic Events

Solving Marginal MAP Problems with NP Oracles and Parity Constraints

Phase-Mapper: An AI Platform to Accelerate High Throughput Materials Discovery

Deep Multi-Species Embedding

Variable Elimination in the Fourier Domain