Changhe Yuan

According to our database, Changhe Yuan authored at least 58 papers between 2003 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2023

Deep Metric Learning to Hierarchically Rank - An Application in Product Retrieval.

Kee Kiat Koo, Ashutosh Joshi, Nishaanth Reddy, Karim Bouyarmane, Ismail B. Tutar, Vaclav Petricek, Changhe Yuan

Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing: EMNLP 2023, 2023

Geometric Matrix Completion via Sylvester Multi-Graph Neural Network.

Boxin Du, Changhe Yuan, Fei Wang, Hanghang Tong

Proceedings of the 32nd ACM International Conference on Information and Knowledge Management, 2023

Enhancing Catalog Relationship Problems with Heterogeneous Graphs and Graph Neural Networks Distillation.

Boxin Du, Robert A. Barton, Grant Galloway, Junzhou Huang, Shioulin Sam, Ismail B. Tutar, Changhe Yuan

Proceedings of the 32nd ACM International Conference on Information and Knowledge Management, 2023

2022

AmpSum: Adaptive Multiple-Product Summarization towards Improving Recommendation Captions.

Quoc-Tuan Truong, Tong Zhao, Changhe Yuan, Jin Li, Jim Chan, Soo-Min Pantel, Hady W. Lauw

Proceedings of the WWW '22: The ACM Web Conference 2022, Virtual Event, Lyon, France, April 25, 2022

Self-supervised Hypergraph Representation Learning.

Boxin Du, Changhe Yuan, Robert A. Barton, Tal Neiman, Hanghang Tong

Proceedings of the IEEE International Conference on Big Data, 2022

2021

Novel features for art movement classification of portrait paintings.

Shao Liu, Jiaqi Yang, Sos S. Agaian, Changhe Yuan

Image Vis. Comput., 2021

Graph Neural Networks for Inconsistent Cluster Detection in Incremental Entity Resolution.

Robert A. Barton, Tal Neiman, Changhe Yuan

IEEE Data Eng. Bull., 2021

Hypergraph Pre-training with Graph Neural Networks.

Boxin Du, Changhe Yuan, Robert A. Barton, Tal Neiman, Hanghang Tong

CoRR, 2021

Improving Causal Discovery By Optimal Bayesian Network Learning.

Ni Y. Lu, Kun Zhang, Changhe Yuan

Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020

Efficient Heuristic Search for M-Modes Inference.

Cong Chen, Changhe Yuan, Chao Chen

Proceedings of the International Conference on Probabilistic Graphical Models, 2020

Solving Multiple Inference by Minimizing Expected Loss.

Cong Chen, Jiaqi Yang, Chao Chen, Changhe Yuan

Proceedings of the International Conference on Probabilistic Graphical Models, 2020

Diversity in Neural Architecture Search.

Wenzheng Hu, Mingyang Li, Changhe Yuan, Changshui Zhang, Jianqiang Wang

Proceedings of the 2020 International Joint Conference on Neural Networks, 2020

2019

Anterior insular cortex is a bottleneck of cognitive control.

Tingting Wu, Xingchao Wang, Qiong Wu, Alfredo Spagna, Jiaqi Yang, Changhe Yuan, Yanhong Wu, Zhixian Gao, Patrick R. Hof, Jin Fan

NeuroImage, 2019

Variational Training for Large-Scale Noisy-OR Bayesian Networks.

Geng Ji, Dehua Cheng, Huazhong Ning, Changhe Yuan, Hanning Zhou, Liang Xiong, Erik B. Sudderth

Proceedings of the Thirty-Fifth Conference on Uncertainty in Artificial Intelligence, 2019

Diverse Multiple Prediction on Neuron Image Reconstruction.

Ze Ye, Cong Chen, Changhe Yuan, Chao Chen

Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2019, 2019

Heuristic Search for Homology Localization Problem and Its Application in Cardiac Trabeculae Reconstruction.

Xudong Zhang, Pengxiang Wu, Changhe Yuan, Yusu Wang, Dimitris N. Metaxas, Chao Chen

Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019

Learning Diverse Bayesian Networks.

Cong Chen, Changhe Yuan

Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

2018

Solving M-Modes in Loopy Graphs Using Tree Decompositions.

Cong Chen, Changhe Yuan, Ze Ye, Chao Chen

Proceedings of the International Conference on Probabilistic Graphical Models, 2018

2017

Hierarchical beam search for solving most relevant explanation in Bayesian networks.

Xiaoyuan Zhu, Changhe Yuan

J. Appl. Log., 2017

Optimal Topological Cycles and Their Application in Cardiac Trabeculae Restoration.

Pengxiang Wu, Chao Chen, Yusu Wang, Shaoting Zhang, Changhe Yuan, Zhen Qian, Dimitris N. Metaxas, Leon Axel

Proceedings of the Information Processing in Medical Imaging, 2017

2016

Exact Algorithms for MRE Inference.

Xiaoyuan Zhu, Changhe Yuan

J. Artif. Intell. Res., 2016

Solving M-Modes Using Heuristic Search.

Cong Chen, Changhe Yuan, Chao Chen

Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence, 2016

2015

An Exact Algorithm for Solving Most Relevant Explanation in Bayesian Networks.

Xiaoyuan Zhu, Changhe Yuan

Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence, 2015

An Improved Lower Bound for Bayesian Network Structure Learning.

Xiannian Fan, Changhe Yuan

Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence, 2015

2014

Finding Optimal Bayesian Network Structures with Constraints Learned from Data.

Xiannian Fan, Brandon M. Malone, Changhe Yuan

Proceedings of the Thirtieth Conference on Uncertainty in Artificial Intelligence, 2014

Result Integrity Verification of Outsourced Bayesian Network Structure Learning.

Ruilin Liu, Wendy Hui Wang, Changhe Yuan

Proceedings of the 2014 SIAM International Conference on Data Mining, 2014

Tightening Bounds for Bayesian Network Structure Learning.

Xiannian Fan, Changhe Yuan, Brandon M. Malone

Proceedings of the Twenty-Eighth AAAI Conference on Artificial Intelligence, 2014

2013

Learning Optimal Bayesian Networks: A Shortest Path Perspective.

Changhe Yuan, Brandon M. Malone

J. Artif. Intell. Res., 2013

Evaluating Anytime Algorithms for Learning Optimal Bayesian Networks.

Brandon M. Malone, Changhe Yuan

Proceedings of the Twenty-Ninth Conference on Uncertainty in Artificial Intelligence, 2013

Solving Limited-Memory Influence Diagrams Using Branch-and-Bound Search.

Arindam Khaled, Eric A. Hansen, Changhe Yuan

Proceedings of the Twenty-Ninth Conference on Uncertainty in Artificial Intelligence, 2013

A Depth-First Branch and Bound Algorithm for Learning Optimal Bayesian Networks.

Brandon M. Malone, Changhe Yuan

Proceedings of the Graph Structures for Knowledge Representation and Reasoning, 2013

2012

Mixture model analysis reflecting dynamics of the population diversity of 2009 pandemic H1N1 influenza virus.

Li-Ping Long, Changhe Yuan, Zhipeng Cai, Huiping Xu, Xiu-Feng Wan

Silico Biol., 2012

Importance Sampling in Bayesian Networks: An Influence-Based Approximation Strategy for Importance Functions

Changhe Yuan, Marek J. Druzdzel

CoRR, 2012

Empirical evaluation of scoring functions for Bayesian network model selection.

Zhifa Liu, Brandon M. Malone, Changhe Yuan

BMC Bioinform., 2012

An Improved Admissible Heuristic for Learning Optimal Bayesian Networks.

Changhe Yuan, Brandon M. Malone

Proceedings of the Twenty-Eighth Conference on Uncertainty in Artificial Intelligence, 2012

2011

Most Relevant Explanation in Bayesian Networks.

Changhe Yuan, Heejin Lim, Tsai-Ching Lu

J. Artif. Intell. Res., 2011

Most Relevant Explanation: computational complexity and approximation methods.

Changhe Yuan, Heejin Lim, Michael L. Littman

Ann. Math. Artif. Intell., 2011

Improving the Scalability of Optimal Bayesian Network Learning with External-Memory Frontier Breadth-First Branch and Bound Search.

Brandon M. Malone, Changhe Yuan, Eric A. Hansen, Susan Bridges

Proceedings of the UAI 2011, 2011

Learning Optimal Bayesian Networks Using A* Search.

Changhe Yuan, Brandon M. Malone, XiaoJian Wu

Proceedings of the IJCAI 2011, 2011

Memory-Efficient Dynamic Programming for Learning Optimal Bayesian Networks.

Brandon M. Malone, Changhe Yuan, Eric A. Hansen

Proceedings of the Twenty-Fifth AAAI Conference on Artificial Intelligence, 2011

2010

Solving Multistage Influence Diagrams using Branch-and-Bound Search.

Changhe Yuan, XiaoJian Wu, Eric A. Hansen

Proceedings of the UAI 2010, 2010

Solving influence diagrams using heuristic search.

Changhe Yuan, XiaoJian Wu

Proceedings of the International Symposium on Artificial Intelligence and Mathematics, 2010

Computational complexity and approximization methods of most relevant explanation.

Heejin Lim, Changhe Yuan

Proceedings of the International Symposium on Artificial Intelligence and Mathematics, 2010

2009

Most Relevant Explanation: Properties, Algorithms, and Evaluations.

Changhe Yuan, Xiaolu Liu, Tsai-Ching Lu, Heejin Lim

Proceedings of the UAI 2009, 2009

Efficient Computation of Jointree Bounds for Systematic MAP Search.

Changhe Yuan, Eric A. Hansen

Proceedings of the IJCAI 2009, 2009

Some Properties of Most Relevant Explanation.

Changhe Yuan

Proceedings of the Explanation-aware Computing, 2009

2008

Integrating Evidence for Evaluation of Potential Novel Protein-coding Genes Using Bayesian Networks.

Nan Wang, Changhe Yuan, Shane C. Burgess, Bindu Nanduri, Mark L. Lawrence, Susan Bridges

Proceedings of the International Conference on Bioinformatics & Computational Biology, 2008

A General Framework for Generating Multivariate Explanations in Bayesian Networks.

Changhe Yuan, Tsai-Ching Lu

Proceedings of the Twenty-Third AAAI Conference on Artificial Intelligence, 2008

2007

Importance Sampling for General Hybrid Bayesian Networks.

Changhe Yuan, Marek J. Druzdzel

Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics, 2007

Theoretical analysis and practical insights on importance sampling in Bayesian networks.

Changhe Yuan, Marek J. Druzdzel

Int. J. Approx. Reason., 2007

Improving Importance Sampling by Adaptive Split-Rejection Control in Bayesian Networks.

Changhe Yuan, Marek J. Druzdzel

Proceedings of the Advances in Artificial Intelligence, 2007

Generalized Evidence Pre-propagated Importance Sampling for Hybrid Bayesian Networks.

Changhe Yuan, Marek J. Druzdzel

Proceedings of the Twenty-Second AAAI Conference on Artificial Intelligence, 2007

2006

Importance sampling algorithms for Bayesian networks: Principles and performance.

Changhe Yuan, Marek J. Druzdzel

Math. Comput. Model., 2006

Hybrid Loopy Belief Propagation.

Changhe Yuan, Marek J. Druzdzel

Proceedings of the Third European Workshop on Probabilistic Graphical Models, 2006

Dynamic Weighting A* Search-based MAP Algorithm for Bayesian Networks.

Xiaoxun Sun, Marek J. Druzdzel, Changhe Yuan

Proceedings of the Third European Workshop on Probabilistic Graphical Models, 2006

2005

How Heavy Should the Tails Be?

Changhe Yuan, Marek J. Druzdzel

Proceedings of the Eighteenth International Florida Artificial Intelligence Research Society Conference, 2005

2004

Annealed MAP.

Changhe Yuan, Tsai-Ching Lu, Marek J. Druzdzel

Proceedings of the UAI '04, 2004

2003

An Importance Sampling Algorithm Based on Evidence Pre-propagation.

Changhe Yuan, Marek J. Druzdzel

Proceedings of the UAI '03, 2003