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2020 – today
- 2024
[i14]Sindhu Tipirneni, Ravinarayana Adkathimar, Nurendra Choudhary, Gaurush Hiranandani, Rana Ali Amjad, Vassilis N. Ioannidis, Changhe Yuan, Chandan K. Reddy:
Context-Aware Clustering using Large Language Models. CoRR abs/2405.00988 (2024)- 2023
- [c47]Boxin Du
, Changhe Yuan, Fei Wang, Hanghang Tong:
Geometric Matrix Completion via Sylvester Multi-Graph Neural Network. CIKM 2023: 3860-3864 - [c46]Boxin Du, Robert A. Barton, Grant Galloway, Junzhou Huang, Shioulin Sam, Ismail B. Tutar, Changhe Yuan:
Enhancing Catalog Relationship Problems with Heterogeneous Graphs and Graph Neural Networks Distillation. CIKM 2023: 4545-4551 - [c45]Kee Kiat Koo, Ashutosh Joshi, Nishaanth Reddy, Karim Bouyarmane, Ismail B. Tutar, Vaclav Petricek, Changhe Yuan:
Deep Metric Learning to Hierarchically Rank - An Application in Product Retrieval. EMNLP (Industry Track) 2023: 104-112 - 2022
- [c44]Boxin Du, Changhe Yuan, Robert A. Barton, Tal Neiman, Hanghang Tong:
Self-supervised Hypergraph Representation Learning. IEEE Big Data 2022: 505-514 - [c43]Quoc-Tuan Truong, Tong Zhao, Changhe Yuan, Jin Li, Jim Chan, Soo-Min Pantel, Hady W. Lauw:
AmpSum: Adaptive Multiple-Product Summarization towards Improving Recommendation Captions. WWW 2022: 2978-2988 - [i13]Boxin Du, Changhe Yuan, Fei Wang, Hanghang Tong:
Geometric Matrix Completion via Sylvester Multi-Graph Neural Network. CoRR abs/2206.09477 (2022) - 2021
- [j12]Robert A. Barton, Tal Neiman, Changhe Yuan:
Graph Neural Networks for Inconsistent Cluster Detection in Incremental Entity Resolution. IEEE Data Eng. Bull. 44(2): 38-50 (2021) - [j11]Shao Liu, Jiaqi Yang, Sos S. Agaian, Changhe Yuan:
Novel features for art movement classification of portrait paintings. Image Vis. Comput. 108: 104121 (2021) - [c42]Ni Y. Lu, Kun Zhang, Changhe Yuan:
Improving Causal Discovery By Optimal Bayesian Network Learning. AAAI 2021: 8741-8748 - [i12]Robert A. Barton, Tal Neiman, Changhe Yuan:
Graph Neural Networks for Inconsistent Cluster Detection in Incremental Entity Resolution. CoRR abs/2105.05957 (2021) - [i11]Boxin Du, Changhe Yuan, Robert A. Barton, Tal Neiman, Hanghang Tong:
Hypergraph Pre-training with Graph Neural Networks. CoRR abs/2105.10862 (2021) - 2020
- [c41]Wenzheng Hu, Mingyang Li, Changhe Yuan, Changshui Zhang, Jianqiang Wang:
Diversity in Neural Architecture Search. IJCNN 2020: 1-8 - [c40]Cong Chen, Jiaqi Yang, Chao Chen, Changhe Yuan:
Solving Multiple Inference by Minimizing Expected Loss. PGM 2020: 65-76 - [c39]Cong Chen, Changhe Yuan, Chao Chen:
Efficient Heuristic Search for M-Modes Inference. PGM 2020: 77-88
2010 – 2019
- 2019
- [j10]Tingting Wu, Xingchao Wang, Qiong Wu, Alfredo Spagna, Jiaqi Yang, Changhe Yuan, Yanhong Wu, Zhixian Gao, Patrick R. Hof, Jin Fan:
Anterior insular cortex is a bottleneck of cognitive control. NeuroImage 195: 490-504 (2019) - [c38]Cong Chen, Changhe Yuan:
Learning Diverse Bayesian Networks. AAAI 2019: 7793-7800 - [c37]Xudong Zhang, Pengxiang Wu, Changhe Yuan, Yusu Wang, Dimitris N. Metaxas, Chao Chen:
Heuristic Search for Homology Localization Problem and Its Application in Cardiac Trabeculae Reconstruction. IJCAI 2019: 1312-1318 - [c36]Ze Ye, Cong Chen, Changhe Yuan, Chao Chen:
Diverse Multiple Prediction on Neuron Image Reconstruction. MICCAI (1) 2019: 460-468 - [c35]Geng Ji, Dehua Cheng, Huazhong Ning, Changhe Yuan, Hanning Zhou, Liang Xiong, Erik B. Sudderth:
Variational Training for Large-Scale Noisy-OR Bayesian Networks. UAI 2019: 873-882 - 2018
- [c34]Cong Chen, Changhe Yuan, Ze Ye, Chao Chen:
Solving M-Modes in Loopy Graphs Using Tree Decompositions. PGM 2018: 145-156 - 2017
- [j9]Xiaoyuan Zhu, Changhe Yuan:
Hierarchical beam search for solving most relevant explanation in Bayesian networks. J. Appl. Log. 22: 3-13 (2017) - [c33]Pengxiang Wu, Chao Chen, Yusu Wang, Shaoting Zhang, Changhe Yuan, Zhen Qian, Dimitris N. Metaxas, Leon Axel:
Optimal Topological Cycles and Their Application in Cardiac Trabeculae Restoration. IPMI 2017: 80-92 - 2016
- [j8]Xiaoyuan Zhu, Changhe Yuan:
Exact Algorithms for MRE Inference. J. Artif. Intell. Res. 55: 653-683 (2016) - [c32]Cong Chen, Changhe Yuan, Chao Chen:
Solving M-Modes Using Heuristic Search. IJCAI 2016: 3584-3590 - 2015
- [c31]Xiannian Fan, Changhe Yuan:
An Improved Lower Bound for Bayesian Network Structure Learning. AAAI 2015: 3526-3532 - [c30]Xiaoyuan Zhu, Changhe Yuan:
An Exact Algorithm for Solving Most Relevant Explanation in Bayesian Networks. AAAI 2015: 3649-3656 - [c29]Xiaoyuan Zhu, Changhe Yuan:
Hierarchical Beam Search for Solving Most Relevant Explanation in Bayesian Networks. FLAIRS 2015: 594-599 - 2014
- [c28]Xiannian Fan, Changhe Yuan, Brandon M. Malone:
Tightening Bounds for Bayesian Network Structure Learning. AAAI 2014: 2439-2445 - [c27]Ruilin Liu, Wendy Hui Wang, Changhe Yuan:
Result Integrity Verification of Outsourced Bayesian Network Structure Learning. SDM 2014: 713-721 - [c26]Xiannian Fan, Brandon M. Malone, Changhe Yuan:
Finding Optimal Bayesian Network Structures with Constraints Learned from Data. UAI 2014: 200-209 - [i10]Changhe Yuan, Heejin Lim, Tsai-Ching Lu:
Most Relevant Explanation in Bayesian Networks. CoRR abs/1401.3893 (2014) - 2013
- [j7]Changhe Yuan, Brandon M. Malone:
Learning Optimal Bayesian Networks: A Shortest Path Perspective. J. Artif. Intell. Res. 48: 23-65 (2013) - [c25]Brandon M. Malone, Changhe Yuan:
A Depth-First Branch and Bound Algorithm for Learning Optimal Bayesian Networks. GKR 2013: 111-122 - [c24]Arindam Khaled, Eric A. Hansen, Changhe Yuan:
Solving Limited-Memory Influence Diagrams Using Branch-and-Bound Search. UAI 2013 - [c23]Brandon M. Malone, Changhe Yuan:
Evaluating Anytime Algorithms for Learning Optimal Bayesian Networks. UAI 2013 - [i9]Arindam Khaled, Eric A. Hansen, Changhe Yuan:
Solving Limited-Memory Influence Diagrams Using Branch-and-Bound Search. CoRR abs/1309.6839 (2013) - [i8]Brandon M. Malone, Changhe Yuan:
Evaluating Anytime Algorithms for Learning Optimal Bayesian Networks. CoRR abs/1309.6844 (2013) - 2012
- [j6]Zhifa Liu, Brandon M. Malone, Changhe Yuan:
Empirical evaluation of scoring functions for Bayesian network model selection. BMC Bioinform. 13(S-15): S14 (2012) - [j5]Li-Ping Long, Changhe Yuan, Zhipeng Cai, Huiping Xu, Xiu-Feng Wan:
Mixture model analysis reflecting dynamics of the population diversity of 2009 pandemic H1N1 influenza virus. Silico Biol. 11(5-6): 225-236 (2012) - [c22]Arindam Khaled, Changhe Yuan, Eric A. Hansen:
Solving Limited Memory Influence Diagrams Using Branch-and-Bound Search. ISAIM 2012 - [c21]Changhe Yuan, Brandon M. Malone:
An Improved Admissible Heuristic for Learning Optimal Bayesian Networks. UAI 2012: 924-933 - [i7]Brandon M. Malone, Changhe Yuan, Eric A. Hansen, Susan Bridges:
Improving the Scalability of Optimal Bayesian Network Learning with External-Memory Frontier Breadth-First Branch and Bound Search. CoRR abs/1202.3744 (2012) - [i6]Changhe Yuan, XiaoJian Wu, Eric A. Hansen:
Solving Multistage Influence Diagrams using Branch-and-Bound Search. CoRR abs/1203.3531 (2012) - [i5]Changhe Yuan, Xiaolu Liu, Tsai-Ching Lu, Heejin Lim:
Most Relevant Explanation: Properties, Algorithms, and Evaluations. CoRR abs/1205.2601 (2012) - [i4]Changhe Yuan, Marek J. Druzdzel:
Importance Sampling in Bayesian Networks: An Influence-Based Approximation Strategy for Importance Functions. CoRR abs/1207.1422 (2012) - [i3]Changhe Yuan, Tsai-Ching Lu, Marek J. Druzdzel:
Annealed MAP. CoRR abs/1207.4153 (2012) - [i2]Changhe Yuan, Brandon M. Malone:
An Improved Admissible Heuristic for Learning Optimal Bayesian Networks. CoRR abs/1210.4913 (2012) - [i1]Changhe Yuan, Marek J. Druzdzel:
An Importance Sampling Algorithm Based on Evidence Pre-propagation. CoRR abs/1212.2507 (2012) - 2011
- [j4]Changhe Yuan, Heejin Lim, Michael L. Littman:
Most Relevant Explanation: computational complexity and approximation methods. Ann. Math. Artif. Intell. 61(3): 159-183 (2011) - [j3]Changhe Yuan, Heejin Lim, Tsai-Ching Lu:
Most Relevant Explanation in Bayesian Networks. J. Artif. Intell. Res. 42: 309-352 (2011) - [c20]Brandon M. Malone, Changhe Yuan, Eric A. Hansen:
Memory-Efficient Dynamic Programming for Learning Optimal Bayesian Networks. AAAI 2011: 1057-1062 - [c19]Changhe Yuan, Brandon M. Malone, XiaoJian Wu:
Learning Optimal Bayesian Networks Using A* Search. IJCAI 2011: 2186-2191 - [c18]Brandon M. Malone, Changhe Yuan, Eric A. Hansen, Susan Bridges:
Improving the Scalability of Optimal Bayesian Network Learning with External-Memory Frontier Breadth-First Branch and Bound Search. UAI 2011: 479-488 - 2010
- [c17]Heejin Lim, Changhe Yuan:
Computational complexity and approximization methods of most relevant explanation. ISAIM 2010 - [c16]Changhe Yuan, XiaoJian Wu:
Solving influence diagrams using heuristic search. ISAIM 2010 - [c15]Changhe Yuan, XiaoJian Wu, Eric A. Hansen:
Solving Multistage Influence Diagrams using Branch-and-Bound Search. UAI 2010: 691-700
2000 – 2009
- 2009
- [c14]Changhe Yuan:
Some Properties of Most Relevant Explanation. ExaCt 2009: 118-126 - [c13]Changhe Yuan, Eric A. Hansen:
Efficient Computation of Jointree Bounds for Systematic MAP Search. IJCAI 2009: 1982-1989 - [c12]Changhe Yuan, Xiaolu Liu, Tsai-Ching Lu, Heejin Lim:
Most Relevant Explanation: Properties, Algorithms, and Evaluations. UAI 2009: 631-638 - 2008
- [c11]Changhe Yuan, Tsai-Ching Lu:
A General Framework for Generating Multivariate Explanations in Bayesian Networks. AAAI 2008: 1119-1124 - [c10]Nan Wang, Changhe Yuan, Shane C. Burgess, Bindu Nanduri, Mark L. Lawrence, Susan Bridges:
Integrating Evidence for Evaluation of Potential Novel Protein-coding Genes Using Bayesian Networks. BIOCOMP 2008: 838-843 - 2007
- [j2]Changhe Yuan, Marek J. Druzdzel:
Theoretical analysis and practical insights on importance sampling in Bayesian networks. Int. J. Approx. Reason. 46(2): 320-333 (2007) - [c9]Changhe Yuan, Marek J. Druzdzel:
Generalized Evidence Pre-propagated Importance Sampling for Hybrid Bayesian Networks. AAAI 2007: 1296-1303 - [c8]Changhe Yuan, Marek J. Druzdzel:
Improving Importance Sampling by Adaptive Split-Rejection Control in Bayesian Networks. Canadian AI 2007: 332-343 - [c7]Xiaoxun Sun, Marek J. Druzdzel, Changhe Yuan:
Dynamic Weighting A* Search-Based MAP Algorithm for Bayesian Networks. IJCAI 2007: 2385-2390 - [c6]Changhe Yuan, Marek J. Druzdzel:
Importance Sampling for General Hybrid Bayesian Networks. AISTATS 2007: 652-659 - 2006
- [j1]Changhe Yuan, Marek J. Druzdzel:
Importance sampling algorithms for Bayesian networks: Principles and performance. Math. Comput. Model. 43(9-10): 1189-1207 (2006) - [c5]Xiaoxun Sun, Marek J. Druzdzel, Changhe Yuan:
Dynamic Weighting A* Search-based MAP Algorithm for Bayesian Networks. Probabilistic Graphical Models 2006: 279-286 - [c4]Changhe Yuan, Marek J. Druzdzel:
Hybrid Loopy Belief Propagation. Probabilistic Graphical Models 2006: 317-324 - 2005
- [c3]Changhe Yuan, Marek J. Druzdzel:
How Heavy Should the Tails Be? FLAIRS 2005: 799-805 - 2004
- [c2]Changhe Yuan, Tsai-Ching Lu, Marek J. Druzdzel:
Annealed MAP. UAI 2004: 628-635 - 2003
- [c1]Changhe Yuan, Marek J. Druzdzel:
An Importance Sampling Algorithm Based on Evidence Pre-propagation. UAI 2003: 624-631
Coauthor Index
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