Yexiang Xue

Publication Activity (10 Years)

Years Active: 2012-2024
Publications (10 Years): 85

Top Topics

Pareto Frontier

Symbolic Regression

Reinforcement Learning

Variable Elimination

Top Venues

Publications

Jinzhao Li, Nan Jiang, Yexiang Xue
Solving Satisfiability Modulo Counting for Symbolic and Statistical AI Integration with Provable Guarantees. AAAI (2024)
Md. Nasim, Yexiang Xue
Efficient Learning of PDEs via Taylor Expansion and Sparse Decomposition into Value and Fourier Domains. AAAI (2024)
Nan Jiang, Md. Nasim, Yexiang Xue
Vertical Symbolic Regression via Deep Policy Gradient. CoRR (2024)
Nan Jiang, Yexiang Xue
Racing Control Variable Genetic Programming for Symbolic Regression. AAAI (2024)
Md. Nasim, Xinghang Zhang, Anter El-Azab, Yexiang Xue
End-to-End Phase Field Model Discovery Combining Experimentation, Crowdsourcing, Simulation and Learning. AAAI (2024)
Maxwell Joseph Jacobson, Yexiang Xue
Hypothesis Network Planned Exploration for Rapid Meta-Reinforcement Learning Adaptation. CoRR (2023)
Jinzhao Li, Nan Jiang, Yexiang Xue
Solving Satisfiability Modulo Counting for Symbolic and Statistical AI Integration With Provable Guarantees. CoRR (2023)
Nan Jiang, Yexiang Xue
Symbolic Regression via Control Variable Genetic Programming. CoRR (2023)
Md. Masudur Rahman, Yexiang Xue
Adversarial Style Transfer for Robust Policy Optimization in Deep Reinforcement Learning. CoRR (2023)
Nan Jiang, Yexiang Xue
Symbolic Regression via Control Variable Genetic Programming. ECML/PKDD (4) (2023)
Maxwell Joseph Jacobson, Yexiang Xue
Integrating Symbolic Reasoning into Neural Generative Models for Design Generation. CoRR (2023)
Md. Nasim, Anter El-Azab, Xinghang Zhang, Yexiang Xue
End-to-end Phase Field Model Discovery Combining Experimentation, Crowdsourcing, Simulation and Learning. CoRR (2023)
Jinzhao Li, Daniel Fink, Christopher Wood, Carla P. Gomes, Yexiang Xue
Provable Optimization of Quantal Response Leader-Follower Games with Exponentially Large Action Spaces. AAMAS (2023)
Nan Jiang, Yexiang Xue
Racing Control Variable Genetic Programming for Symbolic Regression. CoRR (2023)
Md. Masudur Rahman, Yexiang Xue
Adversarial Policy Optimization in Deep Reinforcement Learning. CoRR (2023)
Nan Jiang, Md. Nasim, Yexiang Xue
Vertical Symbolic Regression. CoRR (2023)
Md. Masudur Rahman, Yexiang Xue
Accelerating Policy Gradient by Estimating Value Function from Prior Computation in Deep Reinforcement Learning. CoRR (2023)
Md. Nasim, Yexiang Xue
Efficient Learning of PDEs via Taylor Expansion and Sparse Decomposition into Value and Fourier Domains. CoRR (2023)
Nan Jiang, Yi Gu, Yexiang Xue
Learning Markov Random Fields for Combinatorial Structures via Sampling through Lovász Local Lemma. AAAI (2023)
Md Masudur Rahman, Yexiang Xue
Robust Policy Optimization in Deep Reinforcement Learning. CoRR (2022)
Hantao Shu, Fan Ding, Jingtian Zhou, Yexiang Xue, Dan Zhao, Jianyang Zeng, Jianzhu Ma
Boosting single-cell gene regulatory network reconstruction via bulk-cell transcriptomic data. Briefings Bioinform. 23 (5) (2022)
Nan Jiang, Yi Gu, Yexiang Xue
Learning Combinatorial Structures via Markov Random Fields with Sampling through Lovász Local Lemma. CoRR (2022)
Md. Masudur Rahman, Yexiang Xue
Bootstrap Advantage Estimation for Policy Optimization in Reinforcement Learning. ICMLA (2022)
Nan Jiang, Dhivya Eswaran, Choon Hui Teo, Yexiang Xue, Yesh Dattatreya, Sujay Sanghavi, Vishy Vishwanathan
On the Value of Behavioral Representations for Dense Retrieval. CoRR (2022)
Maxwell J. Jacobson, Case Q. Wright, Nan Jiang, Gustavo Rodriguez-Rivera, Yexiang Xue
Task Detection in Continual Learning via Familiarity Autoencoders. SMC (2022)
Nan Jiang, Maosen Zhang, Willem-Jan van Hoeve, Yexiang Xue
Constraint Reasoning Embedded Structured Prediction. J. Mach. Learn. Res. 23 (2022)
Fan Ding, Yexiang Xue
X-MEN: guaranteed XOR-maximum entropy constrained inverse reinforcement learning. UAI (2022)
Md. Nasim, Xinghang Zhang, Anter El-Azab, Yexiang Xue
Efficient learning of sparse and decomposable PDEs using random projection. UAI (2022)
Nan Jiang, Chen Luo, Vihan Lakshman, Yesh Dattatreya, Yexiang Xue
Massive Text Normalization via an Efficient Randomized Algorithm. WWW (2022)
Fan Ding, Yijie Wang, Jianzhu Ma, Yexiang Xue
Provable Constrained Stochastic Convex Optimization with XOR-Projected Gradient Descent. CoRR (2022)
Md. Masudur Rahman, Yexiang Xue
Bootstrap State Representation using Style Transfer for Better Generalization in Deep Reinforcement Learning. CoRR (2022)
Md. Masudur Rahman, Yexiang Xue
Bootstrap Advantage Estimation for Policy Optimization in Reinforcement Learning. CoRR (2022)
Maxwell J. Jacobson, Daniela Chanci Arrubla, Maria Romeo Tricas, Gayle Gordillo, Yexiang Xue, Chandan K. Sen, Juan Wachs
Human-centered XAI for Burn Depth Characterization. CoRR (2022)
Fan Ding, Yexiang Xue
X-MEN: Guaranteed XOR-Maximum Entropy Constrained Inverse Reinforcement Learning. CoRR (2022)
Md. Masudur Rahman, Yexiang Xue
Bootstrap State Representation Using Style Transfer for Better Generalization in Deep Reinforcement Learning. ECML/PKDD (4) (2022)
Glebys Gonzalez, Mridul Agarwal, Mythra V. Balakuntala, Md. Masudur Rahman, Upinder Kaur, Richard M. Voyles, Vaneet Aggarwal, Yexiang Xue, Juan P. Wachs
DESERTS: DElay-tolerant SEmi-autonomous Robot Teleoperation for Surgery. ICRA (2021)
Nan Jiang, Chen Luo, Vihan Lakshman, Yesh Dattatreya, Yexiang Xue
A Fast Randomized Algorithm for Massive Text Normalization. CoRR (2021)
Fan Ding, Nan Jiang, Jianzhu Ma, Jian Peng, Jinbo Xu, Yexiang Xue
PALM: Probabilistic area loss Minimization for Protein Sequence Alignment. UAI (2021)
Fan Ding, Jianzhu Ma, Jinbo Xu, Yexiang Xue
XOR-CD: Linearly Convergent Constrained Structure Generation. ICML (2021)
Md. Masudur Rahman, Richard M. Voyles, Juan P. Wachs, Yexiang Xue
Sequential Prediction with Logic Constraints for Surgical Robotic Activity Recognition. RO-MAN (2021)
Mridul Agarwal, Glebys T. Gonzalez, Mythra V. Balakuntala, Md. Masudur Rahman, Vaneet Aggarwal, Richard M. Voyles, Yexiang Xue, Juan P. Wachs
Dexterous Skill Transfer between Surgical Procedures for Teleoperated Robotic Surgery. RO-MAN (2021)
Chonghao Sima, Yexiang Xue
LSH-SMILE: Locality Sensitive Hashing Accelerated Simulation and Learning. NeurIPS (2021)
Md. Masudur Rahman, Mythra V. Balakuntala, Glebys T. Gonzalez, Mridul Agarwal, Upinder Kaur, Vishnunandan L. N. Venkatesh, Natalia Sanchez-Tamayo, Yexiang Xue, Richard M. Voyles, Vaneet Aggarwal, Juan P. Wachs
SARTRES: a semi-autonomous robot teleoperation environment for surgery. Comput. methods Biomech. Biomed. Eng. Imaging Vis. 9 (4) (2021)
Fan Ding, Yexiang Xue
XOR-SGD: provable convex stochastic optimization for decision-making under uncertainty. UAI (2021)
Yexiang Xue, Md. Nasim, Maosen Zhang, Cuncai Fan, Xinghang Zhang, Anter El-Azab
Physics Knowledge Discovery via Neural Differential Equation Embedding. ECML/PKDD (5) (2021)
Pramith Devulapalli, Bistra Dilkina, Yexiang Xue
Embedding Conjugate Gradient in Learning Random Walks for Landscape Connectivity Modeling in Conservation. IJCAI (2020)
Glebys T. Gonzalez, Upinder Kaur, Masudur Rahma, Vishnunandan Venkatesh, Natalia Sanchez, Gregory D. Hager, Yexiang Xue, Richard M. Voyles, Juan P. Wachs
From the DESK (Dexterous Surgical Skill) to the Battlefield - A Robotics Exploratory Study. CoRR (2020)
Fan Ding, Hanjing Wang, Ashish Sabharwal, Yexiang Xue
Towards Efficient Discrete Integration via Adaptive Quantile Queries. ECAI (2020)
Maosen Zhang, Nan Jiang, Lei Li, Yexiang Xue
Language Generation via Combinatorial Constraint Satisfaction: A Tree Search Enhanced Monte-Carlo Approach. CoRR (2020)
Fan Ding, Yexiang Xue
Contrastive Divergence Learning with Chained Belief Propagation. PGM (2020)
Maosen Zhang, Nan Jiang, Lei Li, Yexiang Xue
Constraint Satisfaction Driven Natural Language Generation: A Tree Search Embedded MCMC Approach. EMNLP (Findings) (2020)
Anmol Kabra, Yexiang Xue, Carla P. Gomes
CPU-accelerated principal-agent game for scalable citizen science. COMPASS (2019)
Md. Masudur Rahman, Natalia Sanchez-Tamayo, Glebys T. Gonzalez, Mridul Agarwal, Vaneet Aggarwal, Richard M. Voyles, Yexiang Xue, Juan P. Wachs
Transferring Dexterous Surgical Skill Knowledge between Robots for Semi-autonomous Teleoperation. RO-MAN (2019)
Carla P. Gomes, Thomas G. Dietterich, Christopher Barrett, Jon Conrad, Bistra Dilkina, Stefano Ermon, Fei Fang, Andrew Farnsworth, Alan Fern, Xiaoli Z. Fern, Daniel Fink, Douglas H. Fisher, Alexander Flecker, Daniel Freund, Angela Fuller, John M. Gregoire, John E. Hopcroft, Steve Kelling, J. Zico Kolter, Warren B. Powell, Nicole D. Sintov, John S. Selker, Bart Selman, Daniel Sheldon, David B. Shmoys, Milind Tambe, Weng-Keen Wong, Christopher Wood, Xiaojian Wu, Yexiang Xue, Amulya Yadav, Abdul-Aziz Yakubu, Mary Lou Zeeman
Computational sustainability: computing for a better world and a sustainable future. Commun. ACM 62 (9) (2019)
Naveen Madapana, Thomas Low, Richard M. Voyles, Yexiang Xue, Juan P. Wachs, Md. Masudur Rahman, Natalia Sanchez-Tamayo, Mythra V. Balakuntala, Glebys T. Gonzalez, Jyothsna Padmakumar Bindu, L. N. Vishnunandan Venkatesh, Xingguang Zhang, Juan Barragan Noguera
DESK: A Robotic Activity Dataset for Dexterous Surgical Skills Transfer to Medical Robots. IROS (2019)
Fan Ding, Hanjing Wang, Ashish Sabharwal, Yexiang Xue
AdaWISH: Faster Discrete Integration via Adaptive Quantiles. CoRR (2019)
Yexiang Xue, Willem-Jan van Hoeve
Embedding Decision Diagrams into Generative Adversarial Networks. CPAIOR (2019)
Junwen Bai, Zihang Lai, Runzhe Yang, Yexiang Xue, John M. Gregoire, Carla P. Gomes
Imitation Refinement for X-ray Diffraction Signal Processing. ICASSP (2019)
Naveen Madapana, Md. Masudur Rahman, Natalia Sanchez-Tamayo, Mythra V. Balakuntala, Glebys T. Gonzalez, Jyothsna Padmakumar Bindu, L. N. Vishnunandan Venkatesh, Xingguang Zhang, Juan Barragan Noguera, Thomas Low, Richard M. Voyles, Yexiang Xue, Juan P. Wachs
DESK: A Robotic Activity Dataset for Dexterous Surgical Skills Transfer to Medical Robots. CoRR (2019)
Jinning Li, Yexiang Xue
Scribble-to-Painting Transformation with Multi-Task Generative Adversarial Networks. IJCAI (2019)
Johan Bjorck, Yiwei Bai, Xiaojian Wu, Yexiang Xue, Mark C. Whitmore, Carla P. Gomes
Scalable Relaxations of Sparse Packing Constraints: Optimal Biocontrol in Predator-Prey Networks. AAAI (2018)
Junwen Bai, Runzhe Yang, Yexiang Xue, John M. Gregoire, Carla P. Gomes
Imitation Refinement. CoRR (2018)
Xiaojian Wu, Jonathan Gomes-Selman, Qinru Shi, Yexiang Xue, Roosevelt García-Villacorta, Elizabeth Anderson, Suresh Sethi, Scott Steinschneider, Alexander Flecker, Carla P. Gomes
Efficiently Approximating the Pareto Frontier: Hydropower Dam Placement in the Amazon Basin. AAAI (2018)
Di Chen, Yexiang Xue, Carla P. Gomes
End-to-End Learning for the Deep Multivariate Probit Model. ICML (2018)
Jonathan M. Gomes-Selman, Qinru Shi, Yexiang Xue, Roosevelt García-Villacorta, Alexander S. Flecker, Carla P. Gomes
Boosting Efficiency for Computing the Pareto Frontier on Tree Structured Networks. CPAIOR (2018)
Luming Tang, Yexiang Xue, Di Chen, Carla P. Gomes
Multi-Entity Dependence Learning With Rich Context via Conditional Variational Auto-Encoder. AAAI (2018)
Yexiang Xue, Yang Yuan, Zhitian Xu, Ashish Sabharwal
Expanding Holographic Embeddings for Knowledge Completion. NeurIPS (2018)
Di Chen, Yexiang Xue, Carla P. Gomes
End-to-End Learning for the Deep Multivariate Probit Model. CoRR (2018)
Junwen Bai, Yexiang Xue, Johan Bjorck, Ronan Le Bras, Brendan Rappazzo, Richard Bernstein, Santosh K. Suram, Robert Bruce van Dover, John M. Gregoire, Carla P. Gomes
Phase Mapper: Accelerating Materials Discovery with AI. AI Mag. 39 (1) (2018)
Ashish Sabharwal, Yexiang Xue
Adaptive Stratified Sampling for Precision-Recall Estimation. UAI (2018)
Di Chen, Yexiang Xue, Daniel Fink, Shuo Chen, Carla P. Gomes
Deep Multi-species Embedding. IJCAI (2017)
Xiaojian Wu, Yexiang Xue, Bart Selman, Carla P. Gomes
XOR-Sampling for Network Design with Correlated Stochastic Events. IJCAI (2017)
Johan Bjorck, Yiwei Bai, Xiaojian Wu, Yexiang Xue, Mark C. Whitmore, Carla P. Gomes
Scalable Relaxations of Sparse Packing Constraints: Optimal Biocontrol in Predator-Prey Network. CoRR (2017)
Yexiang Xue, XiaoJian Wu, Dana Morin, Bistra Dilkina, Angela Fuller, J. Andrew Royle, Carla P. Gomes
Dynamic Optimization of Landscape Connectivity Embedding Spatial-Capture-Recapture Information. AAAI (2017)
Yexiang Xue, Junwen Bai, Ronan Le Bras, Brendan Rappazzo, Richard Bernstein, Johan Bjorck, Liane Longpre, Santosh K. Suram, Robert Bruce van Dover, John M. Gregoire, Carla P. Gomes
Phase-Mapper: An AI Platform to Accelerate High Throughput Materials Discovery. AAAI (2017)
Luming Tang, Yexiang Xue, Di Chen, Carla P. Gomes
Multi-Entity Dependence Learning with Rich Context via Conditional Variational Auto-encoder. CoRR (2017)
Junwen Bai, Johan Bjorck, Yexiang Xue, Santosh K. Suram, John M. Gregoire, Carla P. Gomes
Relaxation Methods for Constrained Matrix Factorization Problems: Solving the Phase Mapping Problem in Materials Discovery. CPAIOR (2017)
Xiaojian Wu, Yexiang Xue, Bart Selman, Carla P. Gomes
XOR-Sampling for Network Design with Correlated Stochastic Events. CoRR (2017)
Yexiang Xue, Ian Davies, Daniel Fink, Christopher Wood, Carla P. Gomes
Avicaching: A Two Stage Game for Bias Reduction in Citizen Science. AAMAS (2016)
Yexiang Xue, Stefano Ermon, Ronan Le Bras, Carla P. Gomes, Bart Selman
Variable Elimination in the Fourier Domain. ICML (2016)
Yexiang Xue, Zhiyuan Li, Stefano Ermon, Carla P. Gomes, Bart Selman
Solving Marginal MAP Problems with NP Oracles and Parity Constraints. CoRR (2016)
Yexiang Xue, Junwen Bai, Ronan Le Bras, Brendan Rappazzo, Richard Bernstein, Johan Bjorck, Liane Longpre, Santosh K. Suram, Robert Bruce van Dover, John M. Gregoire, Carla P. Gomes
Phase-Mapper: An AI Platform to Accelerate High Throughput Materials Discovery. CoRR (2016)
Di Chen, Yexiang Xue, Shuo Chen, Daniel Fink, Carla P. Gomes
Deep Multi-Species Embedding. CoRR (2016)
Yexiang Xue, Zhiyuan Li, Stefano Ermon, Carla P. Gomes, Bart Selman
Solving Marginal MAP Problems with NP Oracles and Parity Constraints. NIPS (2016)
Yexiang Xue, Ian Davies, Daniel Fink, Christopher Wood, Carla P. Gomes
Behavior Identification in Two-Stage Games for Incentivizing Citizen Science Exploration. CP (2016)
Yexiang Xue, Stefano Ermon, Carla P. Gomes, Bart Selman
Uncovering Hidden Structure through Parallel Problem Decomposition for the Set Basis Problem. AAAI Workshop: Computational Sustainability (2015)
Yexiang Xue, Stefano Ermon, Carla P. Gomes, Bart Selman
Uncovering Hidden Structure through Parallel Problem Decomposition for the Set Basis Problem: Application to Materials Discovery. IJCAI (2015)
Stefano Ermon, Yexiang Xue, Russell Toth, Bistra Dilkina, Richard Bernstein, Theodoros Damoulas, Patrick E. Clark, Steve DeGloria, Andrew Mude, Christopher Barrett, Carla P. Gomes
Learning Large-Scale Dynamic Discrete Choice Models of Spatio-Temporal Preferences with Application to Migratory Pastoralism in East Africa. AAAI (2015)
Yexiang Xue, Stefano Ermon, Ronan LeBras, Carla P. Gomes, Bart Selman
Variable Elimination in Fourier Domain. CoRR (2015)
Ronan Le Bras, Yexiang Xue, Richard Bernstein, Carla P. Gomes, Bart Selman
A Human Computation Framework for Boosting Combinatorial Solvers. HCOMP (2014)
Yexiang Xue, Stefano Ermon, Carla P. Gomes, Bart Selman
Uncovering Hidden Structure through Parallel Problem Decomposition. AAAI (2014)
Yilun Wang, Yu Zheng, Yexiang Xue
Travel time estimation of a path using sparse trajectories. KDD (2014)
Stefano Ermon, Yexiang Xue, Carla P. Gomes, Bart Selman
Learning policies for battery usage optimization in electric vehicles. Mach. Learn. 92 (1) (2013)
Ronan LeBras, Bistra Dilkina, Yexiang Xue, Carla P. Gomes, Kevin S. McKelvey, Michael K. Schwartz, Claire A. Montgomery
Robust Network Design For Multispecies Conservation. AAAI (2013)
Yexiang Xue, Bistra Dilkina, Theodoros Damoulas, Daniel Fink, Carla P. Gomes, Steve Kelling
Improving Your Chances: Boosting Citizen Science Discovery. HCOMP (2013)
Bistra Dilkina, Katherine J. Lai, Ronan LeBras, Yexiang Xue, Carla P. Gomes, Ashish Sabharwal, Jordan Suter, Kevin S. McKelvey, Michael K. Schwartz, Claire A. Montgomery
Large Landscape Conservation - Synthetic and Real-World Datasets. AAAI (2013)
Stefano Ermon, Yexiang Xue, Carla P. Gomes, Bart Selman
Learning Policies for Battery Usage Optimization in Electric Vehicles. ECML/PKDD (2) (2012)
Yexiang Xue, Arthur Choi, Adnan Darwiche
Basing Decisions on Sentences in Decision Diagrams. AAAI (2012)
Arthur Choi, Yexiang Xue, Adnan Darwiche
Same-decision probability: A confidence measure for threshold-based decisions. Int. J. Approx. Reason. 53 (9) (2012)