Changhe Yuan

Publication Activity (10 Years)

Years Active: 2003-2024
Publications (10 Years): 25

Top Topics

Entity Resolution

Heuristic Search

Structure Learning

Top Venues

Publications

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 (2024)
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)
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)
Boxin Du, Changhe Yuan, Fei Wang, Hanghang Tong
Geometric Matrix Completion via Sylvester Multi-Graph Neural Network. CIKM (2023)
Boxin Du, Changhe Yuan, Robert A. Barton, Tal Neiman, Hanghang Tong
Self-supervised Hypergraph Representation Learning. Big Data (2022)
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)
Boxin Du, Changhe Yuan, Fei Wang, Hanghang Tong
Geometric Matrix Completion via Sylvester Multi-Graph Neural Network. CoRR (2022)
Boxin Du, Changhe Yuan, Robert A. Barton, Tal Neiman, Hanghang Tong
Hypergraph Pre-training with Graph Neural Networks. CoRR (2021)
Ni Y. Lu, Kun Zhang, Changhe Yuan
Improving Causal Discovery By Optimal Bayesian Network Learning. AAAI (2021)
Robert A. Barton, Tal Neiman, Changhe Yuan
Graph Neural Networks for Inconsistent Cluster Detection in Incremental Entity Resolution. CoRR (2021)
Shao Liu, Jiaqi Yang, Sos S. Agaian, Changhe Yuan
Novel features for art movement classification of portrait paintings. Image Vis. Comput. 108 (2021)
Robert A. Barton, Tal Neiman, Changhe Yuan
Graph Neural Networks for Inconsistent Cluster Detection in Incremental Entity Resolution. IEEE Data Eng. Bull. 44 (2) (2021)
Cong Chen, Jiaqi Yang, Chao Chen, Changhe Yuan
Solving Multiple Inference by Minimizing Expected Loss. PGM (2020)
Wenzheng Hu, Mingyang Li, Changhe Yuan, Changshui Zhang, Jianqiang Wang
Diversity in Neural Architecture Search. IJCNN (2020)
Cong Chen, Changhe Yuan, Chao Chen
Efficient Heuristic Search for M-Modes Inference. PGM (2020)
Cong Chen, Changhe Yuan
Learning Diverse Bayesian Networks. AAAI (2019)
Ze Ye, Cong Chen, Changhe Yuan, Chao Chen
Diverse Multiple Prediction on Neuron Image Reconstruction. MICCAI (1) (2019)
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)
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 (2019)
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)
Cong Chen, Changhe Yuan, Ze Ye, Chao Chen
Solving M-Modes in Loopy Graphs Using Tree Decompositions. PGM (2018)
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)
Xiaoyuan Zhu, Changhe Yuan
Hierarchical beam search for solving most relevant explanation in Bayesian networks. J. Appl. Log. 22 (2017)
Cong Chen, Changhe Yuan, Chao Chen
Solving M-Modes Using Heuristic Search. IJCAI (2016)
Xiaoyuan Zhu, Changhe Yuan
Exact Algorithms for MRE Inference. J. Artif. Intell. Res. 55 (2016)
Xiaoyuan Zhu, Changhe Yuan
Hierarchical Beam Search for Solving Most Relevant Explanation in Bayesian Networks. FLAIRS Conference (2015)
Xiaoyuan Zhu, Changhe Yuan
An Exact Algorithm for Solving Most Relevant Explanation in Bayesian Networks. AAAI (2015)
Xiannian Fan, Changhe Yuan
An Improved Lower Bound for Bayesian Network Structure Learning. AAAI (2015)
Ruilin Liu, Wendy Hui Wang, Changhe Yuan
Result Integrity Verification of Outsourced Bayesian Network Structure Learning. SDM (2014)
Xiannian Fan, Changhe Yuan, Brandon M. Malone
Tightening Bounds for Bayesian Network Structure Learning. AAAI (2014)
Xiannian Fan, Brandon M. Malone, Changhe Yuan
Finding Optimal Bayesian Network Structures with Constraints Learned from Data. UAI (2014)
Changhe Yuan, Heejin Lim, Tsai-Ching Lu
Most Relevant Explanation in Bayesian Networks. CoRR (2014)
Brandon M. Malone, Changhe Yuan
Evaluating Anytime Algorithms for Learning Optimal Bayesian Networks. CoRR (2013)
Brandon M. Malone, Changhe Yuan
Evaluating Anytime Algorithms for Learning Optimal Bayesian Networks. UAI (2013)
Arindam Khaled, Eric A. Hansen, Changhe Yuan
Solving Limited-Memory Influence Diagrams Using Branch-and-Bound Search. CoRR (2013)
Brandon M. Malone, Changhe Yuan
A Depth-First Branch and Bound Algorithm for Learning Optimal Bayesian Networks. GKR (2013)
Arindam Khaled, Eric A. Hansen, Changhe Yuan
Solving Limited-Memory Influence Diagrams Using Branch-and-Bound Search. UAI (2013)
Changhe Yuan, Brandon M. Malone
Learning Optimal Bayesian Networks: A Shortest Path Perspective. J. Artif. Intell. Res. 48 (2013)
Changhe Yuan, Brandon M. Malone
An Improved Admissible Heuristic for Learning Optimal Bayesian Networks. UAI (2012)
Changhe Yuan, Marek J. Druzdzel
An Importance Sampling Algorithm Based on Evidence Pre-propagation CoRR (2012)
Zhifa Liu, Brandon M. Malone, Changhe Yuan
Empirical evaluation of scoring functions for Bayesian network model selection. BMC Bioinform. 13 (S-15) (2012)
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 (2012)
Changhe Yuan, XiaoJian Wu, Eric A. Hansen
Solving Multistage Influence Diagrams using Branch-and-Bound Search CoRR (2012)
Changhe Yuan, Marek J. Druzdzel
Importance Sampling in Bayesian Networks: An Influence-Based Approximation Strategy for Importance Functions CoRR (2012)
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) (2012)
Changhe Yuan, Tsai-Ching Lu, Marek J. Druzdzel
Annealed MAP CoRR (2012)
Changhe Yuan, Xiaolu Liu, Tsai-Ching Lu, Heejin Lim
Most Relevant Explanation: Properties, Algorithms, and Evaluations CoRR (2012)
Changhe Yuan, Brandon M. Malone
An Improved Admissible Heuristic for Learning Optimal Bayesian Networks CoRR (2012)
Arindam Khaled, Changhe Yuan, Eric A. Hansen
Solving Limited Memory Influence Diagrams Using Branch-and-Bound Search. ISAIM (2012)
Changhe Yuan, Heejin Lim, Tsai-Ching Lu
Most Relevant Explanation in Bayesian Networks. J. Artif. Intell. Res. 42 (2011)
Changhe Yuan, Heejin Lim, Michael L. Littman
Most Relevant Explanation: computational complexity and approximation methods. Ann. Math. Artif. Intell. 61 (3) (2011)
Brandon M. Malone, Changhe Yuan, Eric A. Hansen
Memory-Efficient Dynamic Programming for Learning Optimal Bayesian Networks. AAAI (2011)
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)
Changhe Yuan, Brandon M. Malone, XiaoJian Wu
Learning Optimal Bayesian Networks Using A* Search. IJCAI (2011)
Changhe Yuan, XiaoJian Wu, Eric A. Hansen
Solving Multistage Influence Diagrams using Branch-and-Bound Search. UAI (2010)
Heejin Lim, Changhe Yuan
Computational complexity and approximization methods of most relevant explanation. ISAIM (2010)
Changhe Yuan, XiaoJian Wu
Solving influence diagrams using heuristic search. ISAIM (2010)
Changhe Yuan, Eric A. Hansen
Efficient Computation of Jointree Bounds for Systematic MAP Search. IJCAI (2009)
Changhe Yuan, Xiaolu Liu, Tsai-Ching Lu, Heejin Lim
Most Relevant Explanation: Properties, Algorithms, and Evaluations. UAI (2009)
Changhe Yuan
Some Properties of Most Relevant Explanation. ExaCt (2009)
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)
Changhe Yuan, Tsai-Ching Lu
A General Framework for Generating Multivariate Explanations in Bayesian Networks. AAAI (2008)
Changhe Yuan, Marek J. Druzdzel
Generalized Evidence Pre-propagated Importance Sampling for Hybrid Bayesian Networks. AAAI (2007)
Changhe Yuan, Marek J. Druzdzel
Importance Sampling for General Hybrid Bayesian Networks. AISTATS (2007)
Changhe Yuan, Marek J. Druzdzel
Theoretical analysis and practical insights on importance sampling in Bayesian networks. Int. J. Approx. Reason. 46 (2) (2007)
Xiaoxun Sun, Marek J. Druzdzel, Changhe Yuan
Dynamic Weighting A* Search-Based MAP Algorithm for Bayesian Networks. IJCAI (2007)
Changhe Yuan, Marek J. Druzdzel
Improving Importance Sampling by Adaptive Split-Rejection Control in Bayesian Networks. Canadian Conference on AI (2007)
Changhe Yuan, Marek J. Druzdzel
Hybrid Loopy Belief Propagation. Probabilistic Graphical Models (2006)
Changhe Yuan, Marek J. Druzdzel
Importance sampling algorithms for Bayesian networks: Principles and performance. Math. Comput. Model. 43 (9-10) (2006)
Xiaoxun Sun, Marek J. Druzdzel, Changhe Yuan
Dynamic Weighting A* Search-based MAP Algorithm for Bayesian Networks. Probabilistic Graphical Models (2006)
Changhe Yuan, Marek J. Druzdzel
How Heavy Should the Tails Be? FLAIRS Conference (2005)
Changhe Yuan, Tsai-Ching Lu, Marek J. Druzdzel
Annealed MAP. UAI (2004)
Changhe Yuan, Marek J. Druzdzel
An Importance Sampling Algorithm Based on Evidence Pre-propagation. UAI (2003)