Fast maximum a posteriori inference in Monte Carlo state spaces

AISTATS 2005 - Proceedings of the 10th International Workshop on Artificial Intelligence and Statistics

Volumn , Issue , 2005, Pages 158-165

  Klaas, Mike ^a   Lang, Dustin ^a   De Freitas, Nando ^a  

^a UNIVERSITY OF BRITISH COLUMBIA   (Canada)

Author keywords

[No Author keywords available]

Indexed keywords

DUAL-TREE; HIGH-DIMENSIONAL; MAXIMUM A POSTERIORI; MONTE CARLO; PERFORMANCE GAIN; REGULAR GRIDS; SEARCH PROBLEM; STATE SPACE; STATISTICAL INFERENCE;

ARTIFICIAL INTELLIGENCE; TREES (MATHEMATICS);

ALGORITHMS;

EID: 84862621081     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (13)

1. N Bergman, Recursive Bayesian estimation: Navigation and tracking applications, Ph.D. thesis, Department of Electrical Engineering, Linköping University, Sweeden, 1999.
2. J M Coughlan and H Shen, Shape matching with belief propagation: Using dynamic quantization to accomodate occlusion and clutter, GMBV, 2004.
3. A Doucet, N de Freitas, and N J Gordon (eds.), Sequential Monte Carlo methods in practice, Springer-Verlag, 2001.
4. P Felzenszwalb and D Huttenlocher, Efficient belief propagation for early vision, CVPR, 2004.
5. P Felzenszwalb, D Huttenlocher, and J Kleinberg, Fast algorithms for large-state-space HMMs with applications to web usage analysis, NIPS (2003).
6. S J Godsill, A Doucet, and M West, Maximum a posteriori sequence estimation using Monte Carlo particle filters, Ann. Inst. Stat. Math. 53 (2001), no. 1, 82-96.
7. A Gray and A Moore, 'N-Body' problems in statistical learning, NIPS, 2000, pp. 521-527.
8. A Gray and A Moore, Rapid evaluation of multiple density models, AISTATS, 2003.
9. A T Ihler, E B Sudderth, W T Freeman, and A S Willsky, Efficient multiscale sampling from products of Gaussian mixtures, NIPS 16, 2003.
10. D Lang and N de Freitas, Beat tracking the graphical model way, NIPS 17, 2004.
11. A Moore, The Anchors Hierarchy: Using the triangle inequality to survive high dimensional data, UAI 12, 2000, pp. 397-405.
12. J Pearl, Probabilistic reasoning in intelligent systems: networks of plausible inference, Morgan-Kaufmann, 1988.
13. C P Robert and G Casella, Monte Carlo statistical methods, Springer-Verlag, New York, 1999.