Nevin Lianwen Zhang

2008
50		Yi Wang, Nevin Lianwen Zhang, Tao Chen: Latent Tree Models and Approximate Inference in Bayesian Networks. AAAI 2008: 1112-1118
49	EE	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
48	EE	Nevin Lianwen Zhang, Shihong Yuan, Tao Chen, Yi Wang: Latent tree models and diagnosis in traditional Chinese medicine. Artificial Intelligence in Medicine 42(3): 229-245 (2008)
2007
47	EE	Nevin Lianwen Zhang, Shihong Yuan, Tao Chen, Yi Wang: Hierarchical Latent Class Models and Statistical Foundation for Traditional Chinese Medicine. AIME 2007: 139-143
46	EE	Nevin Lianwen Zhang: Discovering Latent Structures: Experience with the CoIL Challenge 2000 Data Set. International Conference on Computational Science (4) 2007: 26-34
2006
45	EE	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
44	EE	Tao Chen, Nevin Lianwen Zhang: Quartet-Based Learning of Shallow Latent Variables. Probabilistic Graphical Models 2006: 59-66
2005
43	EE	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. Reasoning 38(3): 215-216 (2005)
42	EE	Tao Chen, Tomás Kocka, Nevin Lianwen Zhang: Effective dimensions of partially observed polytrees. Int. J. Approx. Reasoning 38(3): 311-332 (2005)
41	EE	Weihong Zhang, Nevin Lianwen Zhang: Restricted Value Iteration: Theory and Algorithms. J. Artif. Intell. Res. (JAIR) 23: 123-165 (2005)
2004
40		Samuel P. M. Choi, Nevin Lianwen Zhang, Dit-Yan Yeung: Reinforcement Learning in Episodic Non-stationary Markovian Environments. IC-AI 2004: 752-758
39	EE	Nevin Lianwen Zhang, Tomás Kocka: Efficient Learning of Hierarchical Latent Class Models. ICTAI 2004: 585-593
38	EE	Nevin Lianwen Zhang, Thomas D. Nielsen, Finn Verner Jensen: Latent variable discovery in classification models. Artificial Intelligence in Medicine 30(3): 283-299 (2004)
37	EE	Nevin Lianwen Zhang, Tomás Kocka: Effective Dimensions of Hierarchical Latent Class Models. J. Artif. Intell. Res. (JAIR) 21: 1-17 (2004)
36	EE	Nevin Lianwen Zhang: Hierarchical Latent Class Models for Cluster Analysis. Journal of Machine Learning Research 5: 697-723 (2004)
2003
35		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 Springer 2003
34	EE	Tomás Kocka, Nevin Lianwen Zhang: Effective Dimensions of Partially Observed Polytrees. ECSQARU 2003: 184-195
33	EE	David Poole, Nevin Lianwen Zhang: Exploiting Contextual Independence In Probabilistic Inference. J. Artif. Intell. Res. (JAIR) 18: 263-313 (2003)
2002
32		Nevin Lianwen Zhang: Hierarchical Latent Class Models for Cluster Analysis. AAAI/IAAI 2002: 230-237
31		Weihong Zhang, Nevin Lianwen Zhang: Value Iteration Working with Belief Subset. AAAI/IAAI 2002: 307-
30	EE	Weihong Zhang, Nevin Lianwen Zhang: An Alternative Formulation of Dynamic-Programming Updates for POMDPs. AMAI 2002
29		Tomás Kocka, Nevin Lianwen Zhang: Dimension Correction for Hierarchical Latent Class Models. UAI 2002: 267-274
28	EE	Nevin Lianwen Zhang: Inference in Bayesian Networks: The Role of Context-Specific Independence. International Journal of Information Technology and Decision Making 1(1): 91-119 (2002)
2001
27	EE	Nevin Lianwen Zhang, Weihong Zhang: Space-Progressive Value Iteration: An Anytime Algorithm for a Class of POMDPs. ECSQARU 2001: 72-83
26	EE	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
25	EE	Nevin Lianwen Zhang, Weihong Zhang: Speeding Up the Convergence of Value Iteration in Partially Observable Markov Decision Processes. J. Artif. Intell. Res. (JAIR) 14: 29-51 (2001)
1999
24		Nevin Lianwen Zhang, David Poole: On the Role of Context-Specific Independence in Probabilistic Inference. IJCAI 1999: 1288-1293
23	EE	Samuel P. M. Choi, Dit-Yan Yeung, Nevin Lianwen Zhang: An Environment Model for Nonstationary Reinforcement Learning. NIPS 1999: 987-993
22	EE	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
21		Nevin Lianwen Zhang: Context-Specific Independence, Decomposition of Conditional Probabilities, and Inference in Bayesian Networks. PRICAI 1998: 411-423
20	EE	Nevin Lianwen Zhang: Probabilistic Inference in Influence Diagrams. UAI 1998: 514-522
19	EE	Nevin Lianwen Zhang, Stephen S. Lee: Planning with Partially Observable Markov Decision Processes: Advances in Exact Solution Method. UAI 1998: 523-530
18		Nevin Lianwen Zhang: Computational Properties of Two Exact Algorithms for Bayesian Networks. Appl. Intell. 9(2): 173-183 (1998)
17		Nevin Lianwen Zhang: Probabilistic Inference in Influence Diagrams. Computational Intelligence 14: 475-497 (1998)
16	EE	Nevin Lianwen Zhang, Li Yan: Independence of causal influence and clique tree propagation. Int. J. Approx. Reasoning 19(3-4): 335-349 (1998)
1997
15	EE	Nevin Lianwen Zhang, Wenju Liu: Region-Based Approximations for Planning in Stochastic Domains. UAI 1997: 472-480
14	EE	Nevin Lianwen Zhang, Li Yan: Independence of Causal Influence and Clique Tree Propagation. UAI 1997: 481-488
13	EE	Nevin Lianwen Zhang, Weihong Zhang: Fast Value Iteration for Goal-Directed Markov Decision Processes. UAI 1997: 489-494
12	EE	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
11	EE	Nevin Lianwen Zhang, Wenju Liu: A Model Approximation Scheme for Planning in Partially Observable Stochastic Domains CoRR cs.AI/9711103: (1997)
10		Nevin Lianwen Zhang, Wenju Lin: A Model Approximation Scheme for Planning in Partially Observable Stochastic Domains. J. Artif. Intell. Res. (JAIR) 7: 199-230 (1997)
1996
9	EE	Nevin Lianwen Zhang: Irrelevance and ParameterLearning in Bayesian Networks. Artif. Intell. 88(1-2): 359-373 (1996)
8	EE	Nevin Lianwen Zhang, David Poole: Exploiting Causal Independence in Bayesian Network Inference CoRR cs.AI/9612101: (1996)
7		Nevin Lianwen Zhang, David Poole: Exploiting Causal Independence in Bayesian Network Inference. J. Artif. Intell. Res. (JAIR) 5: 301-328 (1996)
1995
6	EE	Nevin Lianwen Zhang: Inference with Causal Independence in the CPSC Network. UAI 1995: 582-589
1994
5	EE	Runping Qi, Nevin Lianwen Zhang, David Poole: Solving Asymmetric Decision Problems with Influence Diagrams. UAI 1994: 491-497
4	EE	Nevin Lianwen Zhang, David Poole: Intercausal Independence and Heterogeneous Factorization. UAI 1994: 606-614
3	EE	Nevin Lianwen Zhang, Runping Qi, David Poole: A computational theory of decision networks. Int. J. Approx. Reasoning 11(2): 83-158 (1994)
1993
2	EE	Nevin Lianwen Zhang, Runping Qi, David Poole: Incremental computation of the value of perfect information in stepwise-decomposable influence diagrams. UAI 1993: 400-410
1992
1		Nevin Lianwen Zhang, David Poole: Stepwise-Decomposable Influence Diagrams. KR 1992: 141-152

Coauthor Index

1	Anthony R. Cassandra	[12]
2	Tao Chen	[42] [44] [47] [48] [50]
3	Samuel P. M. Choi	[23] [26] [40]
4	Finn Verner Jensen	[38]
5	Tomas Kocka (Tomás Kocka)	[29] [34] [37] [39] [42]
6	Stephen S. Lee	[19] [22]
7	Wenju Lin	[10]
8	Michael L. Littman	[12]
9	Wenju Liu	[11] [15]
10	Thomas D. Nielsen	[35] [38] [43]
11	David Poole	[1] [2] [3] [4] [5] [7] [8] [24] [33]
12	Runping Qi	[2] [3] [5]
13	Yi Wang	[45] [47] [48] [50]
14	Li Yan	[14] [16]
15	Dit-Yan Yeung	[23] [26] [40]
16	Shihong Yuan	[47] [48]
17	Weihong Zhang	[13] [22] [25] [27] [30] [31] [41]

Colors in the list of coauthors