Nevin Lianwen Zhang

According to our database, Nevin Lianwen Zhang authored at least 125 papers between 1992 and 2024.

Collaborative distances:

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

2024

Fine-Tuning Pre-trained Language Models for Robust Causal Representation Learning.

Jialin Yu, Yuxiang Zhou, Yulan He, Nevin L. Zhang, Ricardo Silva

CoRR, 2024

Uncovering, Explaining, and Mitigating the Superficial Safety of Backdoor Defense.

Rui Min, Zeyu Qin, Nevin L. Zhang, Li Shen, Minhao Cheng

CoRR, 2024

Breaking the mold: The challenge of large scale MARL specialization.

Stefan Juang, Hugh Cao, Arielle Zhou, Ruochen Liu, Nevin L. Zhang, Elvis S. Liu

CoRR, 2024

TCM-FTP: Fine-Tuning Large Language Models for Herbal Prescription Prediction.

Xingzhi Zhou, Xin Dong, Chunhao Li, Yuning Bai, Yulong Xu, Ka Chun Cheung, Simon See, Xinpeng Song, Runshun Zhang, Xuezhong Zhou, Nevin L. Zhang

CoRR, 2024

Resilient Practical Test-Time Adaptation: Soft Batch Normalization Alignment and Entropy-driven Memory Bank.

Xingzhi Zhou, Zhiliang Tian, Ka Chun Cheung, Simon See, Nevin L. Zhang

CoRR, 2024

Tree-Instruct: A Preliminary Study of the Intrinsic Relationship between Complexity and Alignment.

Yingxiu Zhao, Bowen Yu, Binyuan Hui, Haiyang Yu, Minghao Li, Fei Huang, Nevin L. Zhang, Yongbin Li

Proceedings of the 2024 Joint International Conference on Computational Linguistics, 2024

2023

Robustness May be More Brittle than We Think under Different Degrees of Distribution Shifts.

Kaican Li, Yifan Zhang, Lanqing Hong, Zhenguo Li, Nevin L. Zhang

CoRR, 2023

A Preliminary Study of the Intrinsic Relationship between Complexity and Alignment.

Yingxiu Zhao, Bowen Yu, Binyuan Hui, Haiyang Yu, Fei Huang, Yongbin Li, Nevin L. Zhang

CoRR, 2023

A Causal Framework to Unify Common Domain Generalization Approaches.

Nevin L. Zhang, Kaican Li, Han Gao, Weiyan Xie, Zhi Lin, Zhenguo Li, Luning Wang, Yongxiang Huang

CoRR, 2023

Contrastive Domain Generalization via Logit Attribution Matching.

Han Gao, Kaican Li, Yongxiang Huang, Luning Wang, Caleb Chen Cao, Nevin L. Zhang

CoRR, 2023

Two-stage holistic and contrastive explanation of image classification.

Weiyan Xie, Xiao-Hui Li, Zhi Lin, Leonard K. M. Poon, Caleb Chen Cao, Nevin L. Zhang

Proceedings of the Uncertainty in Artificial Intelligence, 2023

ViT-CX: Causal Explanation of Vision Transformers.

Weiyan Xie, Xiao-Hui Li, Caleb Chen Cao, Nevin L. Zhang

Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence, 2023

Causal Document-Grounded Dialogue Pre-training.

Yingxiu Zhao, Bowen Yu, Bowen Li, Haiyang Yu, Jinyang Li, Chao Wang, Fei Huang, Yongbin Li, Nevin L. Zhang

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

Local Temperature Beam Search: Avoid Neural Text DeGeneration via Enhanced Calibration.

Dongkyu Lee, Gyeonghun Kim, Janghoon Han, Taesuk Hong, Yireun Kim, Stanley Jungkyu Choi, Nevin L. Zhang

Proceedings of the Findings of the Association for Computational Linguistics: ACL 2023, 2023

2022

Semi-Supervised Lifelong Language Learning.

Yingxiu Zhao, Yinhe Zheng, Bowen Yu, Zhiliang Tian, Dongkyu Lee, Jian Sun, Haiyang Yu, Yongbin Li, Nevin L. Zhang

CoRR, 2022

Prompt Conditioned VAE: Enhancing Generative Replay for Lifelong Learning in Task-Oriented Dialogue.

Yingxiu Zhao, Yinhe Zheng, Zhiliang Tian, Chang Gao, Bowen Yu, Haiyang Yu, Yongbin Li, Jian Sun, Nevin L. Zhang

CoRR, 2022

Deep Clustering with Features from Self-Supervised Pretraining.

Xingzhi Zhou, Nevin L. Zhang

CoRR, 2022

Example Perplexity.

Nevin L. Zhang, Weiyan Xie, Zhi Lin, Guanfang Dong, Xiao-Hui Li, Caleb Chen Cao, Yunpeng Wang

CoRR, 2022

SeqPATE: Differentially Private Text Generation via Knowledge Distillation.

Zhiliang Tian, Yingxiu Zhao, Ziyue Huang, Yu-Xiang Wang, Nevin L. Zhang, He He

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Prompt Conditioned VAE: Enhancing Generative Replay for Lifelong Learning in Task-Oriented Dialogue.

Yingxiu Zhao, Yinhe Zheng, Zhiliang Tian, Chang Gao, Jian Sun, Nevin L. Zhang

Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing, 2022

Semi-Supervised Lifelong Language Learning.

Yingxiu Zhao, Yinhe Zheng, Bowen Yu, Zhiliang Tian, Dongkyu Lee, Jian Sun, Yongbin Li, Nevin L. Zhang

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2022, 2022

Empathetic and Emotionally Positive Conversation Systems with an Emotion-specific Query-Response Memory.

Zhiliang Tian, Yinliang Wang, Yiping Song, Chi Zhang, Dongkyu Lee, Yingxiu Zhao, Dongsheng Li, Nevin L. Zhang

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2022, 2022

Hard Gate Knowledge Distillation - Leverage Calibration for Robust and Reliable Language Model.

Dongkyu Lee, Zhiliang Tian, Yingxiu Zhao, Ka Chun Cheung, Nevin Lianwen Zhang

Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing, 2022

Adaptive Label Smoothing with Self-Knowledge in Natural Language Generation.

Dongkyu Lee, Ka Chun Cheung, Nevin L. Zhang

Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing, 2022

Emotion-Aware Multimodal Pre-training for Image-Grounded Emotional Response Generation.

Zhiliang Tian, Zhihua Wen, Zhenghao Wu, Yiping Song, Jintao Tang, Dongsheng Li, Nevin L. Zhang

Proceedings of the Database Systems for Advanced Applications, 2022

Improving Meta-learning for Low-resource Text Classification and Generation via Memory Imitation.

Yingxiu Zhao, Zhiliang Tian, Huaxiu Yao, Yinhe Zheng, Dongkyu Lee, Yiping Song, Jian Sun, Nevin L. Zhang

Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2022

2021

DeepRapper: Neural Rap Generation with Rhyme and Rhythm Modeling.

Lanqing Xue, Kaitao Song, Duocai Wu, Xu Tan, Nevin L. Zhang, Tao Qin, Wei-Qiang Zhang, Tie-Yan Liu

Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing, 2021

Enhancing Content Preservation in Text Style Transfer Using Reverse Attention and Conditional Layer Normalization.

Dongkyu Lee, Zhiliang Tian, Lanqing Xue, Nevin L. Zhang

Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing, 2021

Learning from My Friends: Few-Shot Personalized Conversation Systems via Social Networks.

Zhiliang Tian, Wei Bi, Zihan Zhang, Dongkyu Lee, Yiping Song, Nevin L. Zhang

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

2020

Handling Collocations in Hierarchical Latent Tree Analysis for Topic Modeling.

Leonard K. M. Poon, Nevin L. Zhang, Haoran Xie, Gary Cheng

CoRR, 2020

Learning the Structure of Auto-Encoding Recommenders.

Farhan Khawar, Leonard K. M. Poon, Nevin L. Zhang

Proceedings of the WWW '20: The Web Conference 2020, Taipei, Taiwan, April 20-24, 2020, 2020

Response-Anticipated Memory for On-Demand Knowledge Integration in Response Generation.

Zhiliang Tian, Wei Bi, Dongkyu Lee, Lanqing Xue, Yiping Song, Xiaojiang Liu, Nevin L. Zhang

Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, 2020

Not All Attention Is Needed: Gated Attention Network for Sequence Data.

Lanqing Xue, Xiaopeng Li, Nevin L. Zhang

Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019

Cleaned Similarity for Better Memory-Based Recommenders.

Farhan Khawar, Nevin L. Zhang

Proceedings of the 42nd International ACM SIGIR Conference on Research and Development in Information Retrieval, 2019

Learning Latent Superstructures in Variational Autoencoders for Deep Multidimensional Clustering.

Xiaopeng Li, Zhourong Chen, Leonard K. M. Poon, Nevin L. Zhang

Proceedings of the 7th International Conference on Learning Representations, 2019

Modeling Multidimensional User Preferences for Collaborative Filtering.

Farhan Khawar, Nevin L. Zhang

Proceedings of the 35th IEEE International Conference on Data Engineering, 2019

Fast Structure Learning for Deep Feedforward Networks via Tree Skeleton Expansion.

Zhourong Chen, Xiaopeng Li, Zhiliang Tian, Nevin L. Zhang

Proceedings of the Symbolic and Quantitative Approaches to Reasoning with Uncertainty, 2019

A Novel Document Generation Process for Topic Detection Based on Hierarchical Latent Tree Models.

Peixian Chen, Zhourong Chen, Nevin L. Zhang

Proceedings of the Symbolic and Quantitative Approaches to Reasoning with Uncertainty, 2019

Conformative Filtering for Implicit Feedback Data.

Farhan Khawar, Nevin L. Zhang

Proceedings of the Advances in Information Retrieval, 2019

Learning to Abstract for Memory-augmented Conversational Response Generation.

Zhiliang Tian, Wei Bi, Xiaopeng Li, Nevin L. Zhang

Proceedings of the 57th Conference of the Association for Computational Linguistics, 2019

2018

UC-LTM: Unidimensional clustering using latent tree models for discrete data.

Leonard K. M. Poon, April H. Liu, Nevin L. Zhang

Int. J. Approx. Reason., 2018

Using Taste Groups for Collaborative Filtering.

Farhan Khawar, Nevin L. Zhang

CoRR, 2018

Matrix Factorization Equals Efficient Co-occurrence Representation.

Farhan Khawar, Nevin L. Zhang

CoRR, 2018

Learning Hierarchical Item Categories from Implicit Feedback Data for Efficient Recommendations and Browsing.

Farhan Khawar, Nevin L. Zhang

CoRR, 2018

Learning Sparse Deep Feedforward Networks via Tree Skeleton Expansion.

Zhourong Chen, Xiaopeng Li, Nevin L. Zhang

CoRR, 2018

Latent Tree Variational Autoencoder for Joint Representation Learning and Multidimensional Clustering.

Xiaopeng Li, Zhourong Chen, Nevin L. Zhang

CoRR, 2018

Building Sparse Deep Feedforward Networks using Tree Receptive Fields.

Xiaopeng Li, Zhourong Chen, Nevin L. Zhang

Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence, 2018

2017

Document Generation with Hierarchical Latent Tree Models.

Peixian Chen, Zhourong Chen, Nevin L. Zhang

CoRR, 2017

Conformative Filtering for Implicit Feedback Data.

Farhan Khawar, Nevin L. Zhang, Jinxing Yu

CoRR, 2017

Latent tree models for hierarchical topic detection.

Peixian Chen, Nevin L. Zhang, Tengfei Liu, Leonard K. M. Poon, Zhourong Chen, Farhan Khawar

Artif. Intell., 2017

Mining Textual Reviews with Hierarchical Latent Tree Analysis.

Leonard K. M. Poon, Chun Fai Leung, Nevin L. Zhang

Proceedings of the Data Mining and Big Data - Second International Conference, 2017

Topic Browsing System for Research Papers Based on Hierarchical Latent Tree Analysis.

Leonard K. M. Poon, Chun Fai Leung, Peixian Chen, Nevin L. Zhang

Proceedings of the Web and Big Data - First International Joint Conference, 2017

Latent Tree Analysis.

Nevin L. Zhang, Leonard K. M. Poon

Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence, 2017

Sparse Boltzmann Machines with Structure Learning as Applied to Text Analysis.

Zhourong Chen, Nevin L. Zhang, Dit-Yan Yeung, Peixian Chen

Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence, 2017

2016

Topic Browsing for Research Papers with Hierarchical Latent Tree Analysis.

Leonard K. M. Poon, Nevin L. Zhang

CoRR, 2016

Identification and classification of TCM syndrome types among patients with vascular mild cognitive impairment using latent tree analysis.

Chen Fu, Nevin L. Zhang, Bao Xin Chen, Zhourong Chen, Xiang Lan Jin, Rong Juan Guo, Zhi Gang Chen, Yun Ling Zhang

CoRR, 2016

Latent Tree Models for Hierarchical Topic Detection.

Peixian Chen, Nevin L. Zhang, Tengfei Liu, Leonard K. M. Poon, Zhourong Chen

CoRR, 2016

Progressive EM for Latent Tree Models and Hierarchical Topic Detection.

Peixian Chen, Nevin L. Zhang, Leonard K. M. Poon, Zhourong Chen

Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence, 2016

2015

Greedy learning of latent tree models for multidimensional clustering.

Tengfei Liu, Nevin Lianwen Zhang, Peixian Chen, April Hua Liu, Leonard K. M. Poon, Yi Wang

Mach. Learn., 2015

Bayesian adaptive matrix factorization with automatic model selection.

Peixian Chen, Naiyan Wang, Nevin L. Zhang, Dit-Yan Yeung

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2015

Unidimensional Clustering of Discrete Data Using Latent Tree Models.

April H. Liu, Leonard K. M. Poon, Nevin Lianwen Zhang

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

2014

Latent tree models for rounding in spectral clustering.

April H. Liu, Leonard K. M. Poon, Tengfei Liu, Nevin Lianwen Zhang

Neurocomputing, 2014

An Evidence-Based Approach to Patient Classification in Traditional Chinese Medicine based on Latent Tree Analysis.

Nevin Lianwen Zhang, Chen Fu, Tengfei Liu, Kin Man Poon, Peixian Chen, Bao Xin Chen, Yun Ling Zhang

CoRR, 2014

Hierarchical Latent Tree Analysis for Topic Detection.

Tengfei Liu, Nevin Lianwen Zhang, Peixian Chen

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2014

A Study of Recently Discovered Equalities about Latent Tree Models Using Inverse Edges.

Nevin Lianwen Zhang, Xiaofei Wang, Peixian Chen

Proceedings of the Probabilistic Graphical Models - 7th European Workshop, 2014

2013

A Survey on Latent Tree Models and Applications.

Raphaël Mourad, Christine Sinoquet, Nevin Lianwen Zhang, Tengfei Liu, Philippe Leray

J. Artif. Intell. Res., 2013

LTC: A latent tree approach to classification.

Yi Wang, Nevin Lianwen Zhang, Tao Chen, Leonard K. M. Poon

Int. J. Approx. Reason., 2013

Model-based clustering of high-dimensional data: Variable selection versus facet determination.

Leonard K. M. Poon, Nevin Lianwen Zhang, Tengfei Liu, April H. Liu

Int. J. Approx. Reason., 2013

Sidestepping the Triangulation Problem in Bayesian Net Computations

Nevin Lianwen Zhang, David L. Poole

CoRR, 2013

Inter-causal Independence and Heterogeneous Factorization

Nevin Lianwen Zhang, David L. Poole

CoRR, 2013

2012

Model-based multidimensional clustering of categorical data.

Tao Chen, Nevin Lianwen Zhang, Tengfei Liu, Kin Man Poon, Yi Wang

Artif. Intell., 2012

A Model-Based Approach to Rounding in Spectral Clustering.

Leonard K. M. Poon, April H. Liu, Tengfei Liu, Nevin Lianwen Zhang

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

2011

Discovery of Regularities in the Use of Herbs in Traditional Chinese Medicine Prescriptions.

Nevin Lianwen Zhang, Runsun Zhang, Tao Chen

Proceedings of the New Frontiers in Applied Data Mining, 2011

Fast Multidimensional Clustering of Categorical Data.

Tengfei Liu, Nevin Lianwen Zhang, Kin Man Poon, Yi Wang, Hua Liu

Proceedings of the 2nd MultiClust Workshop: Discovering, 2011

Latent Tree Classifier.

Yi Wang, Nevin Lianwen Zhang, Tao Chen, Leonard K. M. Poon

Proceedings of the Symbolic and Quantitative Approaches to Reasoning with Uncertainty, 2011

2010

The Role of Operation Granularity in Search-Based Learning of Latent Tree Models.

Tao Chen, Nevin Lianwen Zhang, Yi Wang

Proceedings of the New Frontiers in Artificial Intelligence, 2010

Variable Selection in Model-Based Clustering: To Do or To Facilitate.

Leonard K. M. Poon, Nevin Lianwen Zhang, Tao Chen, Yi Wang

Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010

Statistical truths in traditional Chinese medicine theories.

Nevin L. Zhang, Shihong Yuan

Proceedings of the 2010 IEEE International Conference on Bioinformatics and Biomedicine Workshops, 2010

2008

Weights of Evidence and Internal Conflict for Support Functions.

Nevin Lianwen Zhang

Proceedings of the Classic Works of the Dempster-Shafer Theory of Belief Functions, 2008

Discovery of latent structures: Experience with the CoIL Challenge 2000 data set.

Nevin Lianwen Zhang, Yi Wang, Tao Chen

J. Syst. Sci. Complex., 2008

Latent Tree Models and Approximate Inference in Bayesian Networks.

Yi Wang, Nevin Lianwen Zhang, Tao Chen

J. Artif. Intell. Res., 2008

Latent tree models and diagnosis in traditional Chinese medicine.

Nevin Lianwen Zhang, Shihong Yuan, Tao Chen, Yi Wang

Artif. Intell. Medicine, 2008

2007

Discovering Latent Structures: Experience with the CoIL Challenge 2000 Data Set.

Nevin Lianwen Zhang

Proceedings of the Computational Science - ICCS 2007, 7th International Conference, Beijing, China, May 27, 2007

Hierarchical Latent Class Models and Statistical Foundation for Traditional Chinese Medicine.

Nevin Lianwen Zhang, Shihong Yuan, Tao Chen, Yi Wang

Proceedings of the Artificial Intelligence in Medicine, 2007

2006

Severity of Local Maxima for the EM Algorithm: Experiences with Hierarchical Latent Class Models.

Yi Wang, Nevin Lianwen Zhang

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

Quartet-Based Learning of Shallow Latent Variables.

Tao Chen, Nevin Lianwen Zhang

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

Quartet-Based Learning of Hierarchical Latent Class Models: Discovery of Shallow Latent Variables.

Tao Chen, Nevin Lianwen Zhang

Proceedings of the International Symposium on Artificial Intelligence and Mathematics, 2006

2005

Restricted Value Iteration: Theory and Algorithms.

Weihong Zhang, Nevin Lianwen Zhang

J. Artif. Intell. Res., 2005

Special Issue on ECSQARU-2003: The Seventh European Conference on Symbolic and Quantitative Approaches to Reasoning with Uncertainty: Message from the Guest Editors.

Thomas D. Nielsen, Nevin Lianwen Zhang

Int. J. Approx. Reason., 2005

Effective dimensions of partially observed polytrees.

Tao Chen, Tomás Kocka, Nevin Lianwen Zhang

Int. J. Approx. Reason., 2005

2004

Hierarchical Latent Class Models for Cluster Analysis.

Nevin Lianwen Zhang

J. Mach. Learn. Res., 2004

Effective Dimensions of Hierarchical Latent Class Models.

Nevin Lianwen Zhang, Tomás Kocka

J. Artif. Intell. Res., 2004

Latent variable discovery in classification models.

Nevin Lianwen Zhang, Thomas D. Nielsen, Finn Verner Jensen

Artif. Intell. Medicine, 2004

Efficient Learning of Hierarchical Latent Class Models.

Nevin Lianwen Zhang, Tomás Kocka

Proceedings of the 16th IEEE International Conference on Tools with Artificial Intelligence (ICTAI 2004), 2004

Reinforcement Learning in Episodic Non-stationary Markovian Environments.

Samuel P. M. Choi, Nevin Lianwen Zhang, Dit-Yan Yeung

Proceedings of the International Conference on Artificial Intelligence, 2004

2003

Exploiting Contextual Independence In Probabilistic Inference.

David L. Poole, Nevin Lianwen Zhang

J. Artif. Intell. Res., 2003

Effective Dimensions of Partially Observed Polytrees.

Tomás Kocka, Nevin Lianwen Zhang

Proceedings of the Symbolic and Quantitative Approaches to Reasoning with Uncertainty, 2003

2002

Inference in Bayesian Networks: The Role of Context-Specific Independence.

Nevin Lianwen Zhang

Int. J. Inf. Technol. Decis. Mak., 2002

Dimension Correction for Hierarchical Latent Class Models.

Tomás Kocka, Nevin Lianwen Zhang

Proceedings of the UAI '02, 2002

An Alternative Formulation of Dynamic-Programming Updates for POMDPs.

Weihong Zhang, Nevin Lianwen Zhang

Proceedings of the International Symposium on Artificial Intelligence and Mathematics, 2002

Value Iteration Working with Belief Subset.

Weihong Zhang, Nevin Lianwen Zhang

Proceedings of the Eighteenth National Conference on Artificial Intelligence and Fourteenth Conference on Innovative Applications of Artificial Intelligence, July 28, 2002

2001

Speeding Up the Convergence of Value Iteration in Partially Observable Markov Decision Processes.

Nevin Lianwen Zhang, Weihong Zhang

J. Artif. Intell. Res., 2001

Hidden-Mode Markov Decision Processes for Nonstationary Sequential Decision Making.

Samuel P. M. Choi, Dit-Yan Yeung, Nevin Lianwen Zhang

Proceedings of the Sequence Learning - Paradigms, Algorithms, and Applications, 2001

Space-Progressive Value Iteration: An Anytime Algorithm for a Class of POMDPs.

Nevin Lianwen Zhang, Weihong Zhang

Proceedings of the Symbolic and Quantitative Approaches to Reasoning with Uncertainty, 2001

Solving Hidden-Mode Markov Decision Problems.

Samuel Ping-Man Choi, Nevin Lianwen Zhang, Dit-Yan Yeung

Proceedings of the Eighth International Workshop on Artificial Intelligence and Statistics, 2001

1999

A Method for Speeding Up Value Iteration in Partially Observable Markov Decision Processes.

Nevin Lianwen Zhang, Stephen S. Lee, Weihong Zhang

Proceedings of the UAI '99: Proceedings of the Fifteenth Conference on Uncertainty in Artificial Intelligence, Stockholm, Sweden, July 30, 1999

An Environment Model for Nonstationary Reinforcement Learning.

Samuel P. M. Choi, Dit-Yan Yeung, Nevin Lianwen Zhang

Proceedings of the Advances in Neural Information Processing Systems 12, [NIPS Conference, Denver, Colorado, USA, November 29, 1999

On the Role of Context-Specific Independence in Probabilistic Inference.

Nevin Lianwen Zhang, David L. Poole

Proceedings of the Sixteenth International Joint Conference on Artificial Intelligence, 1999

1998

Independence of causal influence and clique tree propagation.

Nevin Lianwen Zhang, Li Yan

Int. J. Approx. Reason., 1998

Probabilistic Inference in Influence Diagrams.

Nevin Lianwen Zhang

Comput. Intell., 1998

Computational Properties of Two Exact Algorithms for Bayesian Networks.

Nevin Lianwen Zhang

Appl. Intell., 1998

Planning with Partially Observable Markov Decision Processes: Advances in Exact Solution Method.

Nevin Lianwen Zhang, Stephen S. Lee

Proceedings of the UAI '98: Proceedings of the Fourteenth Conference on Uncertainty in Artificial Intelligence, 1998

Context-Specific Independence, Decomposition of Conditional Probabilities, and Inference in Bayesian Networks.

Nevin Lianwen Zhang

Proceedings of the PRICAI'98, 1998

1997

A Model Approximation Scheme for Planning in Partially Observable Stochastic Domains.

Nevin Lianwen Zhang, Wenju Liu

J. Artif. Intell. Res., 1997

Fast Value Iteration for Goal-Directed Markov Decision Processes.

Nevin Lianwen Zhang, Weihong Zhang

Proceedings of the UAI '97: Proceedings of the Thirteenth Conference on Uncertainty in Artificial Intelligence, 1997

Region-Based Approximations for Planning in Stochastic Domains.

Nevin Lianwen Zhang, Wenju Liu

Proceedings of the UAI '97: Proceedings of the Thirteenth Conference on Uncertainty in Artificial Intelligence, 1997

Incremental Pruning: A Simple, Fast, Exact Method for Partially Observable Markov Decision Processes.

Anthony R. Cassandra, Michael L. Littman, Nevin Lianwen Zhang

Proceedings of the UAI '97: Proceedings of the Thirteenth Conference on Uncertainty in Artificial Intelligence, 1997

1996

Exploiting Causal Independence in Bayesian Network Inference.

Nevin Lianwen Zhang, David L. Poole

J. Artif. Intell. Res., 1996

Irrelevance and ParameterLearning in Bayesian Networks.

Nevin Lianwen Zhang

Artif. Intell., 1996

1995

Inference with Causal Independence in the CPSC Network.

Nevin Lianwen Zhang

Proceedings of the UAI '95: Proceedings of the Eleventh Annual Conference on Uncertainty in Artificial Intelligence, 1995

1994

A computational theory of decision networks.

Nevin Lianwen Zhang, Runping Qi, David L. Poole

Int. J. Approx. Reason., 1994

Intercausal Independence and Heterogeneous Factorization.

Nevin Lianwen Zhang, David L. Poole

Proceedings of the UAI '94: Proceedings of the Tenth Annual Conference on Uncertainty in Artificial Intelligence, 1994

Solving Asymmetric Decision Problems with Influence Diagrams.

Runping Qi, Nevin Lianwen Zhang, David L. Poole

Proceedings of the UAI '94: Proceedings of the Tenth Annual Conference on Uncertainty in Artificial Intelligence, 1994

1993

Incremental computation of the value of perfect information in stepwise-decomposable influence diagrams.

Nevin Lianwen Zhang, Runping Qi, David L. Poole

Proceedings of the UAI '93: Proceedings of the Ninth Annual Conference on Uncertainty in Artificial Intelligence, 1993

1992

Stepwise-Decomposable Influence Diagrams.

Nevin Lianwen Zhang, David L. Poole

Proceedings of the 3rd International Conference on Principles of Knowledge Representation and Reasoning (KR'92). Cambridge, 1992