default search action
Changhe Yuan
Person information
Refine list
refinements active!
zoomed in on ?? of ?? records
view refined list in
export refined list as
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
Geometric Matrix Completion via Sylvester Multi-Graph Neural Network. CIKM 2023: 3860-3864 - [c46]Boxin Du
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
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
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
manage site settings
To protect your privacy, all features that rely on external API calls from your browser are turned off by default. You need to opt-in for them to become active. All settings here will be stored as cookies with your web browser. For more information see our F.A.Q.
Unpaywalled article links
Add open access links from to the list of external document links (if available).
Privacy notice: By enabling the option above, your browser will contact the API of unpaywall.org to load hyperlinks to open access articles. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Unpaywall privacy policy.
Archived links via Wayback Machine
For web page which are no longer available, try to retrieve content from the of the Internet Archive (if available).
Privacy notice: By enabling the option above, your browser will contact the API of archive.org to check for archived content of web pages that are no longer available. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Internet Archive privacy policy.
Reference lists
Add a list of references from ,
, and
to record detail pages.
load references from crossref.org and opencitations.net
Privacy notice: By enabling the option above, your browser will contact the APIs of crossref.org, opencitations.net, and semanticscholar.org to load article reference information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Crossref privacy policy and the OpenCitations privacy policy, as well as the AI2 Privacy Policy covering Semantic Scholar.
Citation data
Add a list of citing articles from and
to record detail pages.
load citations from opencitations.net
Privacy notice: By enabling the option above, your browser will contact the API of opencitations.net and semanticscholar.org to load citation information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the OpenCitations privacy policy as well as the AI2 Privacy Policy covering Semantic Scholar.
OpenAlex data
Load additional information about publications from .
Privacy notice: By enabling the option above, your browser will contact the API of openalex.org to load additional information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the information given by OpenAlex.
last updated on 2024-10-12 22:55 CEST by the dblp team
all metadata released as open data under CC0 1.0 license
see also: Terms of Use | Privacy Policy | Imprint
dblp was originally created in 1993 at:
since 2018, dblp has been operated and maintained by:
the dblp computer science bibliography is funded and supported by: