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ORCIDNevin Lianwen Zhang
Nevin L. Zhang – 張連文
Person information
- unicode name: 張連文
- affiliation: Hong Kong University of Science and Technology
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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- [i65]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) - [i64]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) - [i63]Stefan Juang, Hugh Cao, Arielle Zhou, Ruochen Liu, Nevin L. Zhang, Elvis S. Liu:
Breaking the mold: The challenge of large scale MARL specialization. CoRR abs/2410.02128 (2024) - [i62]Rui Min, Zeyu Qin, Nevin L. Zhang, Li Shen, Minhao Cheng:
Uncovering, Explaining, and Mitigating the Superficial Safety of Backdoor Defense. CoRR abs/2410.09838 (2024) - [i61]Jialin Yu, Yuxiang Zhou, Yulan He, Nevin L. Zhang, Ricardo Silva:
Fine-Tuning Pre-trained Language Models for Robust Causal Representation Learning. CoRR abs/2410.14375 (2024) - [i60]Kaican Li, Weiyan Xie, Yongxiang Huang, Didan Deng, Lanqing Hong, Zhenguo Li, Ricardo Silva, Nevin L. Zhang:
Dual Risk Minimization: Towards Next-Level Robustness in Fine-tuning Zero-Shot Models. CoRR abs/2411.19757 (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]Tao Chen, Nevin Lianwen Zhang:
Quartet-Based Learning of Shallow Latent Variables. Probabilistic Graphical Models 2006: 59-66 - [c26]Yi Wang, Nevin Lianwen Zhang:
Severity of Local Maxima for the EM Algorithm: Experiences with Hierarchical Latent Class Models. Probabilistic Graphical Models 2006: 301-308 - 2005
- [j16]Thomas D. Nielsen, Nevin Lianwen Zhang:
Special Issue on ECSQARU-2003: The Seventh European Conference on Symbolic and Quantitative Approaches to Reasoning with Uncertainty: Message from the Guest Editors. Int. J. Approx. Reason. 38(3): 215-216 (2005) - [j15]Tao Chen, Tomás Kocka, Nevin Lianwen Zhang:
Effective dimensions of partially observed polytrees. Int. J. Approx. Reason. 38(3): 311-332 (2005) - [j14]Weihong Zhang, Nevin Lianwen Zhang:
Restricted Value Iteration: Theory and Algorithms. J. Artif. Intell. Res. 23: 123-165 (2005) - 2004
- [j13]Nevin Lianwen Zhang, Thomas D. Nielsen, Finn Verner Jensen:
Latent variable discovery in classification models. Artif. Intell. Medicine 30(3): 283-299 (2004) - [j12]Nevin Lianwen Zhang, Tomás Kocka:
Effective Dimensions of Hierarchical Latent Class Models. J. Artif. Intell. Res. 21: 1-17 (2004) - [j11]Nevin Lianwen Zhang:
Hierarchical Latent Class Models for Cluster Analysis. J. Mach. Learn. Res. 5: 697-723 (2004) - [c25]Samuel P. M. Choi, Nevin Lianwen Zhang, Dit-Yan Yeung:
Reinforcement Learning in Episodic Non-stationary Markovian Environments. IC-AI 2004: 752-758 - [c24]Nevin Lianwen Zhang, Tomás Kocka:
Efficient Learning of Hierarchical Latent Class Models. ICTAI 2004: 585-593 - 2003
- [j10]David L. Poole, Nevin Lianwen Zhang:
Exploiting Contextual Independence In Probabilistic Inference. J. Artif. Intell. Res. 18: 263-313 (2003) - [c23]Tomás Kocka, Nevin Lianwen Zhang:
Effective Dimensions of Partially Observed Polytrees. ECSQARU 2003: 184-195 - [e1]Thomas D. Nielsen, Nevin Lianwen Zhang:
Symbolic and Quantitative Approaches to Reasoning with Uncertainty, 7th European Conference, ECSQARU 2003, Aalborg, Denmark, July 2-5, 2003. Proceedings. Lecture Notes in Computer Science 2711, Springer 2003, ISBN 3-540-40494-5 [contents] - 2002
- [j9]Nevin Lianwen Zhang:
Inference in Bayesian Networks: The Role of Context-Specific Independence. Int. J. Inf. Technol. Decis. Mak. 1(1): 91-119 (2002) - [c22]Nevin Lianwen Zhang:
Hierarchical Latent Class Models for Cluster Analysis. AAAI/IAAI 2002: 230-237 - [c21]Weihong Zhang, Nevin Lianwen Zhang:
Value Iteration Working with Belief Subset. AAAI/IAAI 2002: 307-313 - [c20]Weihong Zhang, Nevin Lianwen Zhang:
An Alternative Formulation of Dynamic-Programming Updates for POMDPs. AI&M 2002 - [c19]Tomás Kocka, Nevin Lianwen Zhang:
Dimension Correction for Hierarchical Latent Class Models. UAI 2002: 267-274 - 2001
- [j8]Nevin Lianwen Zhang, Weihong Zhang:
Speeding Up the Convergence of Value Iteration in Partially Observable Markov Decision Processes. J. Artif. Intell. Res. 14: 29-51 (2001) - [c18]Samuel Ping-Man Choi, Nevin Lianwen Zhang, Dit-Yan Yeung:
Solving Hidden-Mode Markov Decision Problems. AISTATS 2001: 49-56 - [c17]Nevin Lianwen Zhang, Weihong Zhang:
Space-Progressive Value Iteration: An Anytime Algorithm for a Class of POMDPs. ECSQARU 2001: 72-83 - [c16]Samuel P. M. Choi, Dit-Yan Yeung, Nevin Lianwen Zhang:
Hidden-Mode Markov Decision Processes for Nonstationary Sequential Decision Making. Sequence Learning 2001: 264-287
1990 – 1999
- 1999
- [c15]Nevin Lianwen Zhang, David L. Poole:
On the Role of Context-Specific Independence in Probabilistic Inference. IJCAI 1999: 1288-1293 - [c14]Samuel P. M. Choi, Dit-Yan Yeung, Nevin Lianwen Zhang:
An Environment Model for Nonstationary Reinforcement Learning. NIPS 1999: 987-993 - [c13]Nevin Lianwen Zhang, Stephen S. Lee, Weihong Zhang:
A Method for Speeding Up Value Iteration in Partially Observable Markov Decision Processes. UAI 1999: 696-703 - 1998
- [j7]Nevin Lianwen Zhang:
Computational Properties of Two Exact Algorithms for Bayesian Networks. Appl. Intell. 9(2): 173-183 (1998) - [j6]Nevin Lianwen Zhang:
Probabilistic Inference in Influence Diagrams. Comput. Intell. 14(4): 475-497 (1998) - [j5]Nevin Lianwen Zhang, Li Yan:
Independence of causal influence and clique tree propagation. Int. J. Approx. Reason. 19(3-4): 335-349 (1998) - [c12]Nevin Lianwen Zhang:
Context-Specific Independence, Decomposition of Conditional Probabilities, and Inference in Bayesian Networks. PRICAI 1998: 411-423 - [c11]Nevin Lianwen Zhang:
Probabilistic Inference in Influence Diagrams. UAI 1998: 514-522 - [c10]Nevin Lianwen Zhang, Stephen S. Lee:
Planning with Partially Observable Markov Decision Processes: Advances in Exact Solution Method. UAI 1998: 523-530 - 1997
- [j4]Nevin Lianwen Zhang, Wenju Liu:
A Model Approximation Scheme for Planning in Partially Observable Stochastic Domains. J. Artif. Intell. Res. 7: 199-230 (1997) - [c9]Anthony R. Cassandra, Michael L. Littman, Nevin Lianwen Zhang:
Incremental Pruning: A Simple, Fast, Exact Method for Partially Observable Markov Decision Processes. UAI 1997: 54-61 - [c8]Nevin Lianwen Zhang, Wenju Liu:
Region-Based Approximations for Planning in Stochastic Domains. UAI 1997: 472-480 - [c7]Nevin Lianwen Zhang, Li Yan:
Independence of Causal Influence and Clique Tree Propagation. UAI 1997: 481-488 - [c6]Nevin Lianwen Zhang, Weihong Zhang:
Fast Value Iteration for Goal-Directed Markov Decision Processes. UAI 1997: 489-494 - [i2]Nevin Lianwen Zhang, Wenju Liu:
A Model Approximation Scheme for Planning in Partially Observable Stochastic Domains. CoRR cs.AI/9711103 (1997) - 1996
- [j3]Nevin Lianwen Zhang:
Irrelevance and ParameterLearning in Bayesian Networks. Artif. Intell. 88(1-2): 359-373 (1996) - [j2]Nevin Lianwen Zhang, David L. Poole:
Exploiting Causal Independence in Bayesian Network Inference. J. Artif. Intell. Res. 5: 301-328 (1996) - [i1]Nevin Lianwen Zhang, David L. Poole:
Exploiting Causal Independence in Bayesian Network Inference. CoRR cs.AI/9612101 (1996) - 1995
- [c5]Nevin Lianwen Zhang:
Inference with Causal Independence in the CPSC Network. UAI 1995: 582-589 - 1994
- [j1]Nevin Lianwen Zhang, Runping Qi, David L. Poole:
A computational theory of decision networks. Int. J. Approx. Reason. 11(2): 83-158 (1994) - [c4]Runping Qi, Nevin Lianwen Zhang, David L. Poole:
Solving Asymmetric Decision Problems with Influence Diagrams. UAI 1994: 491-497 - [c3]Nevin Lianwen Zhang, David L. Poole:
Intercausal Independence and Heterogeneous Factorization. UAI 1994: 606-614 - 1993
- [c2]Nevin Lianwen Zhang, Runping Qi, David L. Poole:
Incremental computation of the value of perfect information in stepwise-decomposable influence diagrams. UAI 1993: 400-410 - 1992
- [c1]Nevin Lianwen Zhang, David L. Poole:
Stepwise-Decomposable Influence Diagrams. KR 1992: 141-152
Coauthor Index
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