Approximate inference algorithms for two-layer Bayesian networks

被引：0
|
作者：
Ng, AY [1 ]
Jordan, MI [1 ]
机构：
[1] Univ Calif Berkeley, Div Comp Sci, Berkeley, CA 94720 USA
来源：
ADVANCES IN NEURAL INFORMATION PROCESSING SYSTEMS 12 | 2000年 / 12卷
关键词：
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
We present a class of approximate inference algorithms for graphical models of the QMR-DT type. We give convergence rates for these algorithms and for the Jaakkola and Jordan (1999) algorithm, and verify these theoretical predictions empirically. We also present empirical results on the difficult QMR-DT network problem, obtaining performance of the new algorithms roughly comparable to the Jaakkola and Jordan algorithm.
引用
下载
收藏
页码：533 / 539
页数：7
相关论文
共 50 条
  • [1] On Designing Approximate Inference Algorithms for Multiply Sectioned Bayesian Networks
    Jin, Karen H.
    Wu, Dan
    Wu, Libing
    2009 IEEE INTERNATIONAL CONFERENCE ON GRANULAR COMPUTING ( GRC 2009), 2009, : 294 - +
  • [2] TRACKING USING BAYESIAN INFERENCE WITH A TWO-LAYER GRAPHICAL MODEL
    Rehrl, T.
    Thessing, N.
    Bannat, A.
    Gast, J.
    Arsic, D.
    Wallhoff, F.
    Rigoll, G.
    2010 IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING, 2010, : 3961 - 3964
  • [3] Templates and algorithms for two-layer cellular neural Networks
    Yang, ZH
    Nishio, Y
    Ushida, A
    PROCEEDING OF THE 2002 INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORKS, VOLS 1-3, 2002, : 1946 - 1951
  • [4] On the Expressiveness of Approximate Inference in Bayesian Neural Networks
    Foong, Andrew Y. K.
    Burt, David R.
    Li, Yingzhen
    Turner, Richard E.
    ADVANCES IN NEURAL INFORMATION PROCESSING SYSTEMS 33, NEURIPS 2020, 2020, 33
  • [5] Approximate inference on optimized quantum Bayesian networks
    Fathallah, Walid
    Amor, Nahla Ben
    Leray, Philippe
    International Journal of Approximate Reasoning, 2024, 175
  • [6] Law of Large Numbers for Bayesian two-layer Neural Network trained with Variational Inference
    Descours, Arnaud
    Huix, Tom
    Guillin, Arnaud
    Michel, Manon
    Moulines, Eric
    Nectoux, Boris
    THIRTY SIXTH ANNUAL CONFERENCE ON LEARNING THEORY, VOL 195, 2023, 195
  • [7] Fast and Provable Algorithms for Learning Two-Layer Polynomial Neural Networks
    Soltani, Mohammadreza
    Hegde, Chinmay
    IEEE TRANSACTIONS ON SIGNAL PROCESSING, 2019, 67 (13) : 3361 - 3371
  • [8] Algorithms for approximate probability propagation in Bayesian networks
    Cano, A
    Moral, S
    Salmerón, A
    ADVANCES IN BAYESIAN NETWORKS, 2004, 146 : 77 - 99
  • [9] Synchronizability of two-layer networks
    Xu, Mingming
    Zhou, Jin
    Lu, Jun-an
    Wu, Xiaoqun
    EUROPEAN PHYSICAL JOURNAL B, 2015, 88 (09):
  • [10] Two-layer queueing networks
    Kino, I
    JOURNAL OF THE OPERATIONS RESEARCH SOCIETY OF JAPAN, 1997, 40 (02) : 163 - 185
12345