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Yexiang Xue
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2020 – today
- 2024
- [j8]Nan Jiang, Jinzhao Li, Yexiang Xue:
A Tighter Convergence Proof of Reverse Experience Replay. RLJ 1: 470-480 (2024) - [c60]Nan Jiang, Yexiang Xue:
Racing Control Variable Genetic Programming for Symbolic Regression. AAAI 2024: 12901-12909 - [c59]Md. Nasim, Yexiang Xue:
Efficient Learning of PDEs via Taylor Expansion and Sparse Decomposition into Value and Fourier Domains. AAAI 2024: 14422-14430 - [c58]Jinzhao Li, Nan Jiang, Yexiang Xue:
Solving Satisfiability Modulo Counting for Symbolic and Statistical AI Integration with Provable Guarantees. AAAI 2024: 20481-20490 - [c57]Md. Nasim, Xinghang Zhang, Anter El-Azab
, Yexiang Xue:
End-to-End Phase Field Model Discovery Combining Experimentation, Crowdsourcing, Simulation and Learning. AAAI 2024: 23005-23011 - [c56]Nan Jiang, Md. Nasim, Yexiang Xue:
Vertical Symbolic Regression via Deep Policy Gradient. IJCAI 2024: 5891-5899 - [c55]Md Masudur Rahman, Yexiang Xue:
Natural Language-based State Representation in Deep Reinforcement Learning. NAACL-HLT (Findings) 2024: 1310-1319 - [i36]Nan Jiang, Md. Nasim, Yexiang Xue:
Vertical Symbolic Regression via Deep Policy Gradient. CoRR abs/2402.00254 (2024) - [i35]Nan Jiang, Jinzhao Li, Yexiang Xue:
A Tighter Convergence Proof of Reverse Experience Replay. CoRR abs/2408.16999 (2024) - [i34]Nan Jiang, Md. Nasim, Yexiang Xue:
Active Symbolic Discovery of Ordinary Differential Equations via Phase Portrait Sketching. CoRR abs/2409.01416 (2024) - 2023
- [c54]Nan Jiang, Yi Gu, Yexiang Xue:
Learning Markov Random Fields for Combinatorial Structures via Sampling through Lovász Local Lemma. AAAI 2023: 4016-4024 - [c53]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: 756-765 - [c52]Nan Jiang, Yexiang Xue
Symbolic Regression via Control Variable Genetic Programming. ECML/PKDD (4) 2023: 178-195 - [i33]Md. Masudur Rahman, Yexiang Xue:
Accelerating Policy Gradient by Estimating Value Function from Prior Computation in Deep Reinforcement Learning. CoRR abs/2302.01399 (2023) - [i32]Md. Masudur Rahman, Yexiang Xue:
Adversarial Policy Optimization in Deep Reinforcement Learning. CoRR abs/2304.14533 (2023) - [i31]Nan Jiang, Yexiang Xue:
Symbolic Regression via Control Variable Genetic Programming. CoRR abs/2306.08057 (2023) - [i30]Md. Masudur Rahman, Yexiang Xue:
Adversarial Style Transfer for Robust Policy Optimization in Deep Reinforcement Learning. CoRR abs/2308.15550 (2023) - [i29]Md. Nasim, Yexiang Xue:
Efficient Learning of PDEs via Taylor Expansion and Sparse Decomposition into Value and Fourier Domains. CoRR abs/2309.07344 (2023) - [i28]Nan Jiang, Yexiang Xue:
Racing Control Variable Genetic Programming for Symbolic Regression. CoRR abs/2309.07934 (2023) - [i27]Jinzhao Li, Nan Jiang, Yexiang Xue:
Solving Satisfiability Modulo Counting for Symbolic and Statistical AI Integration With Provable Guarantees. CoRR abs/2309.08883 (2023) - [i26]Maxwell Joseph Jacobson, Yexiang Xue:
Integrating Symbolic Reasoning into Neural Generative Models for Design Generation. CoRR abs/2310.09383 (2023) - [i25]Maxwell Joseph Jacobson, Yexiang Xue:
Hypothesis Network Planned Exploration for Rapid Meta-Reinforcement Learning Adaptation. CoRR abs/2311.03701 (2023) - [i24]Md. Nasim, Anter El-Azab
End-to-end Phase Field Model Discovery Combining Experimentation, Crowdsourcing, Simulation and Learning. CoRR abs/2311.12801 (2023) - [i23]Nan Jiang, Md. Nasim, Yexiang Xue:
Vertical Symbolic Regression. CoRR abs/2312.11955 (2023) - 2022
- [j7]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) - [j6]Nan Jiang, Maosen Zhang, Willem-Jan van Hoeve, Yexiang Xue:
Constraint Reasoning Embedded Structured Prediction. J. Mach. Learn. Res. 23: 345:1-345:40 (2022) - [c51]Md. Masudur Rahman, Yexiang Xue:
Bootstrap Advantage Estimation for Policy Optimization in Reinforcement Learning. ICMLA 2022: 234-239 - [c50]Md. Masudur Rahman, Yexiang Xue:
Bootstrap State Representation Using Style Transfer for Better Generalization in Deep Reinforcement Learning. ECML/PKDD (4) 2022: 100-115 - [c49]Maxwell J. Jacobson, Case Q. Wright, Nan Jiang, Gustavo Rodriguez-Rivera, Yexiang Xue:
Task Detection in Continual Learning via Familiarity Autoencoders. SMC 2022: 1-8 - [c48]Fan Ding, Yexiang Xue:
X-MEN: guaranteed XOR-maximum entropy constrained inverse reinforcement learning. UAI 2022: 589-598 - [c47]Md. Nasim, Xinghang Zhang, Anter El-Azab, Yexiang Xue:
Efficient learning of sparse and decomposable PDEs using random projection. UAI 2022: 1466-1476 - [c46]Nan Jiang, Chen Luo, Vihan Lakshman, Yesh Dattatreya, Yexiang Xue:
Massive Text Normalization via an Efficient Randomized Algorithm. WWW 2022: 2946-2956 - [i22]Fan Ding, Yijie Wang, Jianzhu Ma, Yexiang Xue:
Provable Constrained Stochastic Convex Optimization with XOR-Projected Gradient Descent. CoRR abs/2203.11829 (2022) - [i21]Fan Ding, Yexiang Xue:
X-MEN: Guaranteed XOR-Maximum Entropy Constrained Inverse Reinforcement Learning. CoRR abs/2203.11842 (2022) - [i20]Md. Masudur Rahman, Yexiang Xue:
Bootstrap State Representation using Style Transfer for Better Generalization in Deep Reinforcement Learning. CoRR abs/2207.07749 (2022) - [i19]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 abs/2208.05663 (2022) - [i18]Md. Masudur Rahman, Yexiang Xue:
Bootstrap Advantage Estimation for Policy Optimization in Reinforcement Learning. CoRR abs/2210.07312 (2022) - [i17]Maxwell J. Jacobson, Daniela Chanci Arrubla
Human-centered XAI for Burn Depth Characterization. CoRR abs/2210.13535 (2022) - [i16]Nan Jiang, Yi Gu, Yexiang Xue:
Learning Combinatorial Structures via Markov Random Fields with Sampling through Lovász Local Lemma. CoRR abs/2212.00296 (2022) - [i15]Md. Masudur Rahman, Yexiang Xue:
Robust Policy Optimization in Deep Reinforcement Learning. CoRR abs/2212.07536 (2022) - 2021
- [j5]Md. Masudur Rahman
SARTRES: a semi-autonomous robot teleoperation environment for surgery. Comput. methods Biomech. Biomed. Eng. Imaging Vis. 9(4): 376-383 (2021) - [c45]Fan Ding, Jianzhu Ma, Jinbo Xu, Yexiang Xue:
XOR-CD: Linearly Convergent Constrained Structure Generation. ICML 2021: 2728-2738 - [c44]Glebys T. 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: 12693-12700 - [c43]Chonghao Sima, Yexiang Xue:
LSH-SMILE: Locality Sensitive Hashing Accelerated Simulation and Learning. NeurIPS 2021: 7484-7496 - [c42]Yexiang Xue, Md. Nasim, Maosen Zhang, Cuncai Fan
Physics Knowledge Discovery via Neural Differential Equation Embedding. ECML/PKDD (5) 2021: 118-134 - [c41]Md. Masudur Rahman, Richard M. Voyles, Juan P. Wachs, Yexiang Xue:
Sequential Prediction with Logic Constraints for Surgical Robotic Activity Recognition. RO-MAN 2021: 468-475 - [c40]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: 1236-1242 - [c39]Fan Ding, Yexiang Xue:
XOR-SGD: provable convex stochastic optimization for decision-making under uncertainty. UAI 2021: 151-160 - [c38]Fan Ding, Nan Jiang, Jianzhu Ma, Jian Peng, Jinbo Xu, Yexiang Xue:
PALM: Probabilistic area loss Minimization for Protein Sequence Alignment. UAI 2021: 1100-1109 - [i14]Nan Jiang, Chen Luo, Vihan Lakshman, Yesh Dattatreya, Yexiang Xue:
A Fast Randomized Algorithm for Massive Text Normalization. CoRR abs/2110.03024 (2021) - 2020
- [c37]Fan Ding, Hanjing Wang, Ashish Sabharwal, Yexiang Xue:
Towards Efficient Discrete Integration via Adaptive Quantile Queries. ECAI 2020: 2577-2584 - [c36]Maosen Zhang, Nan Jiang, Lei Li, Yexiang Xue:
Constraint Satisfaction Driven Natural Language Generation: A Tree Search Embedded MCMC Approach. EMNLP (Findings) 2020: 1286-1298 - [c35]Pramith Devulapalli, Bistra Dilkina, Yexiang Xue:
Embedding Conjugate Gradient in Learning Random Walks for Landscape Connectivity Modeling in Conservation. IJCAI 2020: 4338-4344 - [c34]Fan Ding, Yexiang Xue:
Contrastive Divergence Learning with Chained Belief Propagation. PGM 2020: 161-172 - [i13]Maosen Zhang, Nan Jiang, Lei Li, Yexiang Xue:
Language Generation via Combinatorial Constraint Satisfaction: A Tree Search Enhanced Monte-Carlo Approach. CoRR abs/2011.12334 (2020) - [i12]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 abs/2011.15100 (2020)
2010 – 2019
- 2019
- [j4]Carla P. Gomes, Thomas G. Dietterich, Christopher Barrett, Jon Conrad, Bistra Dilkina
Computational sustainability: computing for a better world and a sustainable future. Commun. ACM 62(9): 56-65 (2019) - [c33]Yexiang Xue, Willem-Jan van Hoeve:
Embedding Decision Diagrams into Generative Adversarial Networks. CPAIOR 2019: 616-632 - [c32]Anmol Kabra, Yexiang Xue, Carla P. Gomes:
CPU-accelerated principal-agent game for scalable citizen science. COMPASS 2019: 165-173 - [c31]Junwen Bai
Imitation Refinement for X-ray Diffraction Signal Processing. ICASSP 2019: 3337-3341 - [c30]Jinning Li, Yexiang Xue:
Scribble-to-Painting Transformation with Multi-Task Generative Adversarial Networks. IJCAI 2019: 5916-5922 - [c29]Naveen Madapana, Thomas Low, Richard M. Voyles
DESK: A Robotic Activity Dataset for Dexterous Surgical Skills Transfer to Medical Robots. IROS 2019: 6928-6934 - [c28]Md. Masudur Rahman, Natalia Sanchez-Tamayo, Glebys T. Gonzalez
Transferring Dexterous Surgical Skill Knowledge between Robots for Semi-autonomous Teleoperation. RO-MAN 2019: 1-6 - [i11]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 abs/1903.00959 (2019) - [i10]Fan Ding, Hanjing Wang, Ashish Sabharwal, Yexiang Xue:
AdaWISH: Faster Discrete Integration via Adaptive Quantiles. CoRR abs/1910.05811 (2019) - 2018
- [b1]Yexiang Xue:
Combining Reasoning and Learning for Multi-stage Inference in Computational Sustainability and Scientific Discovery. Cornell University, USA, 2018 - [j3]Junwen Bai, Yexiang Xue, Johan Bjorck, Ronan Le Bras, Brendan Rappazzo, Richard Bernstein
Phase Mapper: Accelerating Materials Discovery with AI. AI Mag. 39(1): 15-26 (2018) - [c27]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: 748-756 - [c26]Luming Tang, Yexiang Xue, Di Chen, Carla P. Gomes:
Multi-Entity Dependence Learning With Rich Context via Conditional Variational Auto-Encoder. AAAI 2018: 824-832 - [c25]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: 849-859 - [c24]Jonathan Michael Gomes Selman, Qinru Shi, Yexiang Xue, Roosevelt García-Villacorta, Alexander S. Flecker
Boosting Efficiency for Computing the Pareto Frontier on Tree Structured Networks. CPAIOR 2018: 263-279 - [c23]Di Chen, Yexiang Xue, Carla P. Gomes:
End-to-End Learning for the Deep Multivariate Probit Model. ICML 2018: 931-940 - [c22]Yexiang Xue, Yang Yuan, Zhitian Xu, Ashish Sabharwal:
Expanding Holographic Embeddings for Knowledge Completion. NeurIPS 2018: 4496-4506 - [c21]Ashish Sabharwal, Yexiang Xue:
Adaptive Stratified Sampling for Precision-Recall Estimation. UAI 2018: 825-834 - [i9]Di Chen, Yexiang Xue, Carla P. Gomes:
End-to-End Learning for the Deep Multivariate Probit Model. CoRR abs/1803.08591 (2018) - [i8]Junwen Bai, Runzhe Yang
Imitation Refinement. CoRR abs/1805.08698 (2018) - 2017
- [c20]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: 4552-4558 - [c19]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: 4635-4643 - [c18]Junwen Bai
Relaxation Methods for Constrained Matrix Factorization Problems: Solving the Phase Mapping Problem in Materials Discovery. CPAIOR 2017: 104-112 - [c17]Di Chen, Yexiang Xue, Daniel Fink, Shuo Chen, Carla P. Gomes:
Deep Multi-species Embedding. IJCAI 2017: 3639-3646 - [c16]Xiaojian Wu, Yexiang Xue, Bart Selman, Carla P. Gomes:
XOR-Sampling for Network Design with Correlated Stochastic Events. IJCAI 2017: 4640-4647 - [i7]Xiaojian Wu, Yexiang Xue, Bart Selman, Carla P. Gomes:
XOR-Sampling for Network Design with Correlated Stochastic Events. CoRR abs/1705.08218 (2017) - [i6]Luming Tang, Yexiang Xue, Di Chen, Carla P. Gomes:
Multi-Entity Dependence Learning with Rich Context via Conditional Variational Auto-encoder. CoRR abs/1709.05612 (2017) - [i5]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 abs/1711.06800 (2017) - 2016
- [c15]Yexiang Xue, Ian Davies, Daniel Fink, Christopher Wood, Carla P. Gomes:
Avicaching: A Two Stage Game for Bias Reduction in Citizen Science. AAMAS 2016: 776-785 - [c14]Yexiang Xue, Ian Davies, Daniel Fink, Christopher Wood, Carla P. Gomes:
Behavior Identification in Two-Stage Games for Incentivizing Citizen Science Exploration. CP 2016: 701-717 - [c13]Yexiang Xue, Stefano Ermon, Ronan Le Bras, Carla P. Gomes, Bart Selman:
Variable Elimination in the Fourier Domain. ICML 2016: 285-294 - [c12]Yexiang Xue, Zhiyuan Li
Solving Marginal MAP Problems with NP Oracles and Parity Constraints. NIPS 2016: 1127-1135 - [i4]Di Chen, Yexiang Xue, Shuo Chen, Daniel Fink, Carla P. Gomes:
Deep Multi-Species Embedding. CoRR abs/1609.09353 (2016) - [i3]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 abs/1610.00689 (2016) - [i2]Yexiang Xue, Zhiyuan Li, Stefano Ermon, Carla P. Gomes, Bart Selman:
Solving Marginal MAP Problems with NP Oracles and Parity Constraints. CoRR abs/1610.02591 (2016) - 2015
- [c11]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: 644-650 - [c10]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 - [c9]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: 146-155 - [i1]Yexiang Xue, Stefano Ermon, Ronan Le Bras, Carla P. Gomes, Bart Selman:
Variable Elimination in Fourier Domain. CoRR abs/1508.04032 (2015) - 2014
- [c8]Yexiang Xue, Stefano Ermon, Carla P. Gomes, Bart Selman:
Uncovering Hidden Structure through Parallel Problem Decomposition. AAAI 2014: 3144-3145 - [c7]Ronan Le Bras, Yexiang Xue, Richard Bernstein, Carla P. Gomes, Bart Selman:
A Human Computation Framework for Boosting Combinatorial Solvers. HCOMP 2014: 121-132 - [c6]Yilun Wang, Yu Zheng, Yexiang Xue:
Travel time estimation of a path using sparse trajectories. KDD 2014: 25-34 - 2013
- [j2]Stefano Ermon, Yexiang Xue, Carla P. Gomes, Bart Selman:
Learning policies for battery usage optimization in electric vehicles. Mach. Learn. 92(1): 177-194 (2013) - [c5]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: 1305-1312 - [c4]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: 1369-1372 - [c3]Yexiang Xue, Bistra Dilkina, Theodoros Damoulas, Daniel Fink, Carla P. Gomes, Steve Kelling:
Improving Your Chances: Boosting Citizen Science Discovery. HCOMP 2013: 198-206 - 2012
- [j1]Arthur Choi, Yexiang Xue, Adnan Darwiche:
Same-decision probability: A confidence measure for threshold-based decisions. Int. J. Approx. Reason. 53(9): 1415-1428 (2012) - [c2]Yexiang Xue, Arthur Choi, Adnan Darwiche:
Basing Decisions on Sentences in Decision Diagrams. AAAI 2012: 842-849 - [c1]Stefano Ermon, Yexiang Xue, Carla P. Gomes, Bart Selman:
Learning Policies for Battery Usage Optimization in Electric Vehicles. ECML/PKDD (2) 2012: 195-210
Coauthor Index
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