default search action
Nevin Lianwen Zhang
Nevin L. Zhang – 張連文
Person information
- unicode name: 張連文
- affiliation: Hong Kong University of Science and Technology
Refine list
refinements active!
zoomed in on ?? of ?? records
view refined list in
export refined list as
showing all ?? records
2020 – today
- 2024
- [c74]Yingxiu Zhao, Bowen Yu, Binyuan Hui, Haiyang Yu, Minghao Li, Fei Huang, Nevin L. Zhang, Yongbin Li:
Tree-Instruct: A Preliminary Study of the Intrinsic Relationship between Complexity and Alignment. LREC/COLING 2024: 16776-16789 - [i61]Xingzhi Zhou, Zhiliang Tian, Ka Chun Cheung, Simon See, Nevin L. Zhang:
Resilient Practical Test-Time Adaptation: Soft Batch Normalization Alignment and Entropy-driven Memory Bank. CoRR abs/2401.14619 (2024) - [i60]Xingzhi Zhou, Xin Dong, Chunhao Li, Yuning Bai, Yulong Xu, Ka Chun Cheung, Simon See, Xinpeng Song, Runshun Zhang, Xuezhong Zhou, Nevin L. Zhang:
TCM-FTP: Fine-Tuning Large Language Models for Herbal Prescription Prediction. CoRR abs/2407.10510 (2024) - 2023
- [c73]Dongkyu Lee, Gyeonghun Kim, Janghoon Han, Taesuk Hong, Yireun Kim, Stanley Jungkyu Choi, Nevin L. Zhang:
Local Temperature Beam Search: Avoid Neural Text DeGeneration via Enhanced Calibration. ACL (Findings) 2023: 9903-9915 - [c72]Yingxiu Zhao, Bowen Yu, Bowen Li, Haiyang Yu, Jinyang Li, Chao Wang, Fei Huang, Yongbin Li, Nevin L. Zhang:
Causal Document-Grounded Dialogue Pre-training. EMNLP 2023: 7160-7174 - [c71]Weiyan Xie, Xiao-Hui Li, Caleb Chen Cao, Nevin L. Zhang:
ViT-CX: Causal Explanation of Vision Transformers. IJCAI 2023: 1569-1577 - [c70]Weiyan Xie, Xiao-Hui Li, Zhi Lin, Leonard K. M. Poon, Caleb Chen Cao, Nevin L. Zhang:
Two-stage holistic and contrastive explanation of image classification. UAI 2023: 2335-2345 - [i59]Han Gao, Kaican Li, Yongxiang Huang, Luning Wang, Caleb Chen Cao, Nevin L. Zhang:
Contrastive Domain Generalization via Logit Attribution Matching. CoRR abs/2305.07888 (2023) - [i58]Yingxiu Zhao, Bowen Yu, Haiyang Yu, Bowen Li, Jinyang Li, Chao Wang, Fei Huang, Yongbin Li, Nevin L. Zhang:
Causal Document-Grounded Dialogue Pre-training. CoRR abs/2305.10927 (2023) - [i57]Weiyan Xie, Xiao-Hui Li, Zhi Lin, Leonard K. M. Poon, Caleb Chen Cao, Nevin L. Zhang:
Two-Stage Holistic and Contrastive Explanation of Image Classification. CoRR abs/2306.06339 (2023) - [i56]Nevin L. Zhang, Kaican Li, Han Gao, Weiyan Xie, Zhi Lin, Zhenguo Li, Luning Wang, Yongxiang Huang:
A Causal Framework to Unify Common Domain Generalization Approaches. CoRR abs/2307.06825 (2023) - [i55]Yingxiu Zhao, Bowen Yu, Binyuan Hui, Haiyang Yu, Fei Huang, Yongbin Li, Nevin L. Zhang:
A Preliminary Study of the Intrinsic Relationship between Complexity and Alignment. CoRR abs/2308.05696 (2023) - [i54]Kaican Li, Yifan Zhang, Lanqing Hong, Zhenguo Li, Nevin L. Zhang:
Robustness May be More Brittle than We Think under Different Degrees of Distribution Shifts. CoRR abs/2310.06622 (2023) - 2022
- [c69]Yingxiu Zhao, Zhiliang Tian, Huaxiu Yao, Yinhe Zheng, Dongkyu Lee, Yiping Song, Jian Sun, Nevin L. Zhang:
Improving Meta-learning for Low-resource Text Classification and Generation via Memory Imitation. ACL (1) 2022: 583-595 - [c68]Zhiliang Tian, Zhihua Wen, Zhenghao Wu, Yiping Song, Jintao Tang, Dongsheng Li, Nevin L. Zhang:
Emotion-Aware Multimodal Pre-training for Image-Grounded Emotional Response Generation. DASFAA (3) 2022: 3-19 - [c67]Yingxiu Zhao, Yinhe Zheng, Bowen Yu, Zhiliang Tian, Dongkyu Lee, Jian Sun, Yongbin Li, Nevin L. Zhang:
Semi-Supervised Lifelong Language Learning. EMNLP (Findings) 2022: 3937-3951 - [c66]Zhiliang Tian, Yinliang Wang, Yiping Song, Chi Zhang, Dongkyu Lee, Yingxiu Zhao, Dongsheng Li, Nevin L. Zhang:
Empathetic and Emotionally Positive Conversation Systems with an Emotion-specific Query-Response Memory. EMNLP (Findings) 2022: 6364-6376 - [c65]Dongkyu Lee, Ka Chun Cheung, Nevin L. Zhang:
Adaptive Label Smoothing with Self-Knowledge in Natural Language Generation. EMNLP 2022: 9781-9792 - [c64]Dongkyu Lee, Zhiliang Tian, Yingxiu Zhao, Ka Chun Cheung, Nevin Lianwen Zhang:
Hard Gate Knowledge Distillation - Leverage Calibration for Robust and Reliable Language Model. EMNLP 2022: 9793-9803 - [c63]Yingxiu Zhao, Yinhe Zheng, Zhiliang Tian, Chang Gao, Jian Sun, Nevin L. Zhang:
Prompt Conditioned VAE: Enhancing Generative Replay for Lifelong Learning in Task-Oriented Dialogue. EMNLP 2022: 11153-11169 - [c62]Zhiliang Tian, Yingxiu Zhao, Ziyue Huang, Yu-Xiang Wang, Nevin L. Zhang, He He:
SeqPATE: Differentially Private Text Generation via Knowledge Distillation. NeurIPS 2022 - [i53]Nevin L. Zhang, Weiyan Xie, Zhi Lin, Guanfang Dong, Xiao-Hui Li, Caleb Chen Cao, Yunpeng Wang:
Example Perplexity. CoRR abs/2203.08813 (2022) - [i52]Yingxiu Zhao, Zhiliang Tian, Huaxiu Yao, Yinhe Zheng, Dongkyu Lee, Yiping Song, Jian Sun, Nevin L. Zhang:
Improving Meta-learning for Low-resource Text Classification and Generation via Memory Imitation. CoRR abs/2203.11670 (2022) - [i51]Xingzhi Zhou, Nevin L. Zhang:
Deep Clustering with Features from Self-Supervised Pretraining. CoRR abs/2207.13364 (2022) - [i50]Yingxiu Zhao, Yinhe Zheng, Zhiliang Tian, Chang Gao, Bowen Yu, Haiyang Yu, Yongbin Li, Jian Sun, Nevin L. Zhang:
Prompt Conditioned VAE: Enhancing Generative Replay for Lifelong Learning in Task-Oriented Dialogue. CoRR abs/2210.07783 (2022) - [i49]Dongkyu Lee, Zhiliang Tian, Yingxiu Zhao, Ka Chun Cheung, Nevin L. Zhang:
Hard Gate Knowledge Distillation - Leverage Calibration for Robust and Reliable Language Model. CoRR abs/2210.12427 (2022) - [i48]Dongkyu Lee, Ka Chun Cheung, Nevin L. Zhang:
Adaptive Label Smoothing with Self-Knowledge in Natural Language Generation. CoRR abs/2210.13459 (2022) - [i47]Weiyan Xie, Xiao-Hui Li, Caleb Chen Cao, Nevin L. Zhang:
ViT-CX: Causal Explanation of Vision Transformers. CoRR abs/2211.03064 (2022) - [i46]Yingxiu Zhao, Yinhe Zheng, Bowen Yu, Zhiliang Tian, Dongkyu Lee, Jian Sun, Haiyang Yu, Yongbin Li, Nevin L. Zhang:
Semi-Supervised Lifelong Language Learning. CoRR abs/2211.13050 (2022) - 2021
- [c61]Zhiliang Tian, Wei Bi, Zihan Zhang, Dongkyu Lee, Yiping Song, Nevin L. Zhang:
Learning from My Friends: Few-Shot Personalized Conversation Systems via Social Networks. AAAI 2021: 13907-13915 - [c60]Lanqing Xue, Kaitao Song, Duocai Wu, Xu Tan, Nevin L. Zhang, Tao Qin, Wei-Qiang Zhang, Tie-Yan Liu:
DeepRapper: Neural Rap Generation with Rhyme and Rhythm Modeling. ACL/IJCNLP (1) 2021: 69-81 - [c59]Dongkyu Lee, Zhiliang Tian, Lanqing Xue, Nevin L. Zhang:
Enhancing Content Preservation in Text Style Transfer Using Reverse Attention and Conditional Layer Normalization. ACL/IJCNLP (1) 2021: 93-102 - [i45]Zhiliang Tian, Wei Bi, Zihan Zhang, Dongkyu Lee, Yiping Song, Nevin L. Zhang:
Learning from My Friends: Few-Shot Personalized Conversation Systems via Social Networks. CoRR abs/2105.10323 (2021) - [i44]Lanqing Xue, Kaitao Song, Duocai Wu, Xu Tan, Nevin L. Zhang, Tao Qin, Wei-Qiang Zhang, Tie-Yan Liu:
DeepRapper: Neural Rap Generation with Rhyme and Rhythm Modeling. CoRR abs/2107.01875 (2021) - [i43]Dongkyu Lee, Zhiliang Tian, Lanqing Xue, Nevin L. Zhang:
Enhancing Content Preservation in Text Style Transfer Using Reverse Attention and Conditional Layer Normalization. CoRR abs/2108.00449 (2021) - 2020
- [c58]Lanqing Xue, Xiaopeng Li, Nevin L. Zhang:
Not All Attention Is Needed: Gated Attention Network for Sequence Data. AAAI 2020: 6550-6557 - [c57]Zhiliang Tian, Wei Bi, Dongkyu Lee, Lanqing Xue, Yiping Song, Xiaojiang Liu, Nevin L. Zhang:
Response-Anticipated Memory for On-Demand Knowledge Integration in Response Generation. ACL 2020: 650-659 - [c56]Farhan Khawar, Leonard K. M. Poon, Nevin L. Zhang:
Learning the Structure of Auto-Encoding Recommenders. WWW 2020: 519-529 - [i42]Zhiliang Tian, Wei Bi, Dongkyu Lee, Lanqing Xue, Yiping Song, Xiaojiang Liu, Nevin L. Zhang:
Response-Anticipated Memory for On-Demand Knowledge Integration in Response Generation. CoRR abs/2005.06128 (2020) - [i41]Leonard K. M. Poon, Nevin L. Zhang, Haoran Xie, Gary Cheng:
Handling Collocations in Hierarchical Latent Tree Analysis for Topic Modeling. CoRR abs/2007.05163 (2020) - [i40]Farhan Khawar, Leonard Kin Man Poon, Nevin Lianwen Zhang:
Learning the Structure of Auto-Encoding Recommenders. CoRR abs/2008.07956 (2020)
2010 – 2019
- 2019
- [c55]Zhiliang Tian, Wei Bi, Xiaopeng Li, Nevin L. Zhang:
Learning to Abstract for Memory-augmented Conversational Response Generation. ACL (1) 2019: 3816-3825 - [c54]Farhan Khawar, Nevin L. Zhang:
Conformative Filtering for Implicit Feedback Data. ECIR (1) 2019: 164-178 - [c53]Peixian Chen, Zhourong Chen, Nevin L. Zhang:
A Novel Document Generation Process for Topic Detection Based on Hierarchical Latent Tree Models. ECSQARU 2019: 265-276 - [c52]Zhourong Chen, Xiaopeng Li, Zhiliang Tian, Nevin L. Zhang:
Fast Structure Learning for Deep Feedforward Networks via Tree Skeleton Expansion. ECSQARU 2019: 277-289 - [c51]Farhan Khawar, Nevin L. Zhang:
Modeling Multidimensional User Preferences for Collaborative Filtering. ICDE 2019: 1618-1621 - [c50]Xiaopeng Li, Zhourong Chen, Leonard K. M. Poon, Nevin L. Zhang:
Learning Latent Superstructures in Variational Autoencoders for Deep Multidimensional Clustering. ICLR (Poster) 2019 - [c49]Farhan Khawar, Nevin L. Zhang:
Cleaned Similarity for Better Memory-Based Recommenders. SIGIR 2019: 1193-1196 - [i39]Farhan Khawar, Nevin L. Zhang:
Cleaned Similarity for Better Memory-Based Recommenders. CoRR abs/1905.07370 (2019) - [i38]Lanqing Xue, Xiaopeng Li, Nevin L. Zhang:
Not All Attention Is Needed: Gated Attention Network for Sequence Data. CoRR abs/1912.00349 (2019) - 2018
- [j27]Leonard K. M. Poon, April H. Liu, Nevin L. Zhang:
UC-LTM: Unidimensional clustering using latent tree models for discrete data. Int. J. Approx. Reason. 92: 392-409 (2018) - [c48]Xiaopeng Li, Zhourong Chen, Nevin L. Zhang:
Building Sparse Deep Feedforward Networks using Tree Receptive Fields. IJCAI 2018: 5045-5051 - [i37]Xiaopeng Li, Zhourong Chen, Nevin L. Zhang:
Latent Tree Variational Autoencoder for Joint Representation Learning and Multidimensional Clustering. CoRR abs/1803.05206 (2018) - [i36]Xiaopeng Li, Zhourong Chen, Nevin L. Zhang:
Building Sparse Deep Feedforward Networks using Tree Receptive Fields. CoRR abs/1803.05209 (2018) - [i35]Zhourong Chen, Xiaopeng Li, Nevin L. Zhang:
Learning Sparse Deep Feedforward Networks via Tree Skeleton Expansion. CoRR abs/1803.06120 (2018) - [i34]Farhan Khawar, Nevin L. Zhang:
Learning Hierarchical Item Categories from Implicit Feedback Data for Efficient Recommendations and Browsing. CoRR abs/1806.02056 (2018) - [i33]Farhan Khawar, Nevin L. Zhang:
Matrix Factorization Equals Efficient Co-occurrence Representation. CoRR abs/1808.09371 (2018) - [i32]Farhan Khawar, Nevin L. Zhang:
Using Taste Groups for Collaborative Filtering. CoRR abs/1808.09785 (2018) - 2017
- [j26]Peixian Chen, Nevin L. Zhang, Tengfei Liu, Leonard K. M. Poon, Zhourong Chen, Farhan Khawar:
Latent tree models for hierarchical topic detection. Artif. Intell. 250: 105-124 (2017) - [c47]Zhourong Chen, Nevin L. Zhang, Dit-Yan Yeung, Peixian Chen:
Sparse Boltzmann Machines with Structure Learning as Applied to Text Analysis. AAAI 2017: 1805-1811 - [c46]Nevin L. Zhang, Leonard K. M. Poon:
Latent Tree Analysis. AAAI 2017: 4891-4898 - [c45]Leonard K. M. Poon, Chun Fai Leung, Peixian Chen, Nevin L. Zhang:
Topic Browsing System for Research Papers Based on Hierarchical Latent Tree Analysis. APWeb/WAIM (2) 2017: 341-344 - [c44]Leonard K. M. Poon, Chun Fai Leung, Nevin L. Zhang:
Mining Textual Reviews with Hierarchical Latent Tree Analysis. DMBD 2017: 401-408 - [i31]Farhan Khawar, Nevin L. Zhang, Jinxing Yu:
Conformative Filtering for Implicit Feedback Data. CoRR abs/1704.01889 (2017) - [i30]Peixian Chen, Zhourong Chen, Nevin L. Zhang:
Document Generation with Hierarchical Latent Tree Models. CoRR abs/1712.04116 (2017) - 2016
- [c43]Peixian Chen, Nevin L. Zhang, Leonard K. M. Poon, Zhourong Chen:
Progressive EM for Latent Tree Models and Hierarchical Topic Detection. AAAI 2016: 1498-1504 - [i29]Chen Fu, Nevin L. Zhang, Bao Xin Chen, Zhourong Chen, Xiang Lan Jin, Rong Juan Guo, Zhi Gang Chen, Yun Ling Zhang:
Identification and classification of TCM syndrome types among patients with vascular mild cognitive impairment using latent tree analysis. CoRR abs/1601.06923 (2016) - [i28]Peixian Chen, Nevin L. Zhang, Tengfei Liu, Leonard K. M. Poon, Zhourong Chen:
Latent Tree Models for Hierarchical Topic Detection. CoRR abs/1605.06650 (2016) - [i27]Zhourong Chen, Nevin L. Zhang, Dit-Yan Yeung, Peixian Chen:
Sparse Boltzmann Machines with Structure Learning as Applied to Text Analysis. CoRR abs/1609.05294 (2016) - [i26]Leonard K. M. Poon, Nevin L. Zhang:
Topic Browsing for Research Papers with Hierarchical Latent Tree Analysis. CoRR abs/1609.09188 (2016) - [i25]Nevin L. Zhang, Leonard K. M. Poon:
Latent Tree Analysis. CoRR abs/1610.00085 (2016) - 2015
- [j25]Tengfei Liu, Nevin Lianwen Zhang, Peixian Chen, April Hua Liu, Leonard K. M. Poon, Yi Wang:
Greedy learning of latent tree models for multidimensional clustering. Mach. Learn. 98(1-2): 301-330 (2015) - [c42]April H. Liu, Leonard K. M. Poon, Nevin Lianwen Zhang:
Unidimensional Clustering of Discrete Data Using Latent Tree Models. AAAI 2015: 2771-2777 - [c41]Peixian Chen, Naiyan Wang, Nevin L. Zhang, Dit-Yan Yeung:
Bayesian adaptive matrix factorization with automatic model selection. CVPR 2015: 1284-1292 - [i24]Peixian Chen, Nevin L. Zhang, Leonard K. M. Poon, Zhourong Chen:
Progressive EM for Latent Tree Models and Hierarchical Topic Detection. CoRR abs/1508.00973 (2015) - 2014
- [j24]April H. Liu, Leonard K. M. Poon, Tengfei Liu, Nevin Lianwen Zhang:
Latent tree models for rounding in spectral clustering. Neurocomputing 144: 448-462 (2014) - [c40]Nevin Lianwen Zhang, Xiaofei Wang, Peixian Chen:
A Study of Recently Discovered Equalities about Latent Tree Models Using Inverse Edges. Probabilistic Graphical Models 2014: 567-580 - [c39]Tengfei Liu, Nevin Lianwen Zhang, Peixian Chen:
Hierarchical Latent Tree Analysis for Topic Detection. ECML/PKDD (2) 2014: 256-272 - [e2]Nevin L. Zhang, Jin Tian:
Proceedings of the Thirtieth Conference on Uncertainty in Artificial Intelligence, UAI 2014, Quebec City, Quebec, Canada, July 23-27, 2014. AUAI Press 2014, ISBN 978-0-9749039-1-0 [contents] - [i23]Yi Wang, Nevin Lianwen Zhang, Tao Chen:
Latent Tree Models and Approximate Inference in Bayesian Networks. CoRR abs/1401.3429 (2014) - [i22]Raphaël Mourad, Christine Sinoquet, Nevin Lianwen Zhang, Tengfei Liu, Philippe Leray:
A Survey on Latent Tree Models and Applications. CoRR abs/1402.0577 (2014) - [i21]Nevin Lianwen Zhang, Chen Fu, Tengfei Liu, Kin Man Poon, Peixian Chen, Bao Xin Chen, Yun Ling Zhang:
An Evidence-Based Approach to Patient Classification in Traditional Chinese Medicine based on Latent Tree Analysis. CoRR abs/1410.7140 (2014) - 2013
- [j23]Leonard K. M. Poon, Nevin Lianwen Zhang, Tengfei Liu, April H. Liu:
Model-based clustering of high-dimensional data: Variable selection versus facet determination. Int. J. Approx. Reason. 54(1): 196-215 (2013) - [j22]Yi Wang, Nevin Lianwen Zhang, Tao Chen, Leonard K. M. Poon:
LTC: A latent tree approach to classification. Int. J. Approx. Reason. 54(4): 560-572 (2013) - [j21]Raphaël Mourad, Christine Sinoquet, Nevin Lianwen Zhang, Tengfei Liu, Philippe Leray:
A Survey on Latent Tree Models and Applications. J. Artif. Intell. Res. 47: 157-203 (2013) - [i20]Tomas Kocka, Nevin Lianwen Zhang:
Dimension Correction for Hierarchical Latent Class Models. CoRR abs/1301.0578 (2013) - [i19]Nevin Lianwen Zhang, Stephen S. Lee, Weihong Zhang:
A Method for Speeding Up Value Iteration in Partially Observable Markov Decision Processes. CoRR abs/1301.6751 (2013) - [i18]Nevin Lianwen Zhang:
Probabilistic Inference in Influence Diagrams. CoRR abs/1301.7416 (2013) - [i17]Nevin Lianwen Zhang, Stephen S. Lee:
Planning with Partially Observable Markov Decision Processes: Advances in Exact Solution Method. CoRR abs/1301.7417 (2013) - [i16]Anthony R. Cassandra, Michael L. Littman, Nevin Lianwen Zhang:
Incremental Pruning: A Simple, Fast, Exact Method for Partially Observable Markov Decision Processes. CoRR abs/1302.1525 (2013) - [i15]Nevin Lianwen Zhang, Wenju Liu:
Region-Based Approximations for Planning in Stochastic Domains. CoRR abs/1302.1573 (2013) - [i14]Nevin Lianwen Zhang, Li Yan:
Independence of Causal Influence and Clique Tree Propagation. CoRR abs/1302.1574 (2013) - [i13]Nevin Lianwen Zhang, Weihong Zhang:
Fast Value Iteration for Goal-Directed Markov Decision Processes. CoRR abs/1302.1575 (2013) - [i12]Nevin Lianwen Zhang:
Inference with Causal Independence in the CPSC Network. CoRR abs/1302.4993 (2013) - [i11]Runping Qi, Nevin Lianwen Zhang, David L. Poole:
Solving Asymmetric Decision Problems with Influence Diagrams. CoRR abs/1302.6840 (2013) - [i10]Nevin Lianwen Zhang, David L. Poole:
Inter-causal Independence and Heterogeneous Factorization. CoRR abs/1302.6855 (2013) - [i9]Nevin Lianwen Zhang, Runping Qi, David L. Poole:
Incremental computation of the value of perfect information in stepwise-decomposable influence diagrams. CoRR abs/1303.1502 (2013) - [i8]Nevin Lianwen Zhang, David L. Poole:
Sidestepping the Triangulation Problem in Bayesian Net Computations. CoRR abs/1303.5440 (2013) - 2012
- [j20]Tao Chen, Nevin Lianwen Zhang, Tengfei Liu, Kin Man Poon, Yi Wang:
Model-based multidimensional clustering of categorical data. Artif. Intell. 176(1): 2246-2269 (2012) - [c38]Leonard K. M. Poon, April H. Liu, Tengfei Liu, Nevin Lianwen Zhang:
A Model-Based Approach to Rounding in Spectral Clustering. UAI 2012: 685-694 - [i7]Leonard K. M. Poon, April H. Liu, Tengfei Liu, Nevin Lianwen Zhang:
A Model-Based Approach to Rounding in Spectral Clustering. CoRR abs/1210.4883 (2012) - 2011
- [c37]Yi Wang, Nevin Lianwen Zhang, Tao Chen, Leonard K. M. Poon:
Latent Tree Classifier. ECSQARU 2011: 410-421 - [c36]Tengfei Liu, Nevin Lianwen Zhang, Kin Man Poon, Yi Wang, Hua Liu:
Fast Multidimensional Clustering of Categorical Data. MultiClust@ECML/PKDD 2011: 19-30 - [c35]Nevin Lianwen Zhang, Runsun Zhang, Tao Chen:
Discovery of Regularities in the Use of Herbs in Traditional Chinese Medicine Prescriptions. PAKDD Workshops 2011: 353-360 - [i6]Nevin Lianwen Zhang, Weihong Zhang:
Speeding Up the Convergence of Value Iteration in Partially Observable Markov Decision Processes. CoRR abs/1106.0251 (2011) - [i5]David L. Poole, Nevin Lianwen Zhang:
Exploiting Contextual Independence In Probabilistic Inference. CoRR abs/1106.4864 (2011) - [i4]Tomas Kocka, Nevin Lianwen Zhang:
Effective Dimensions of Hierarchical Latent Class Models. CoRR abs/1107.0027 (2011) - [i3]Nevin Lianwen Zhang, Weihong Zhang:
Restricted Value Iteration: Theory and Algorithms. CoRR abs/1107.0042 (2011) - 2010
- [c34]Nevin L. Zhang, Shihong Yuan:
Statistical truths in traditional Chinese medicine theories. BIBM Workshops 2010: 631-634 - [c33]Leonard K. M. Poon, Nevin Lianwen Zhang, Tao Chen, Yi Wang:
Variable Selection in Model-Based Clustering: To Do or To Facilitate. ICML 2010: 887-894 - [c32]Tao Chen, Nevin Lianwen Zhang, Yi Wang:
The Role of Operation Granularity in Search-Based Learning of Latent Tree Models. JSAI-isAI Workshops 2010: 219-231
2000 – 2009
- 2008
- [j19]Nevin Lianwen Zhang, Shihong Yuan, Tao Chen, Yi Wang:
Latent tree models and diagnosis in traditional Chinese medicine. Artif. Intell. Medicine 42(3): 229-245 (2008) - [j18]Yi Wang, Nevin Lianwen Zhang, Tao Chen:
Latent Tree Models and Approximate Inference in Bayesian Networks. J. Artif. Intell. Res. 32: 879-900 (2008) - [j17]Nevin Lianwen Zhang, Yi Wang, Tao Chen:
Discovery of latent structures: Experience with the CoIL Challenge 2000 data set. J. Syst. Sci. Complex. 21(2): 172-183 (2008) - [c31]Yi Wang, Nevin Lianwen Zhang, Tao Chen:
Latent Tree Models and Approximate Inference in Bayesian Networks. AAAI 2008: 1112-1118 - [p1]Nevin Lianwen Zhang:
Weights of Evidence and Internal Conflict for Support Functions. Classic Works of the Dempster-Shafer Theory of Belief Functions 2008: 411-418 - 2007
- [c30]Nevin Lianwen Zhang, Shihong Yuan, Tao Chen, Yi Wang:
Hierarchical Latent Class Models and Statistical Foundation for Traditional Chinese Medicine. AIME 2007: 139-143 - [c29]Nevin Lianwen Zhang:
Discovering Latent Structures: Experience with the CoIL Challenge 2000 Data Set. International Conference on Computational Science (4) 2007: 26-34 - 2006
- [c28]Tao Chen, Nevin Lianwen Zhang:
Quartet-Based Learning of Hierarchical Latent Class Models: Discovery of Shallow Latent Variables. AI&M 2006 - [c27]