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Yexiang Xue
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2020 – today
- 2025
- [j9]Maxwell J. Jacobson, Yexiang Xue:
Integrating symbolic reasoning into neural generative models for design generation. Artif. Intell. 339: 104257 (2025) - 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, Xinghang Zhang, Yexiang Xue:
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, Maria Romeo Tricas, Gayle Gordillo, Yexiang Xue, Chandan K. Sen, Juan P. Wachs:
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, 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): 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, Xinghang Zhang, Anter El-Azab:
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, 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): 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, Zihang Lai, Runzhe Yang, Yexiang Xue, John M. Gregoire, Carla P. Gomes:
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, 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: 6928-6934 - [c28]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: 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, Santosh K. Suram, Robert Bruce van Dover, John M. Gregoire, Carla P. Gomes:
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, Carla P. Gomes:
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, Yexiang Xue, John M. Gregoire, Carla P. Gomes:
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, 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: 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, Stefano Ermon, Carla P. Gomes, Bart Selman:
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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