Mike Klaas Dustin Lang Nando de Freitas Computer Science Department...  Home/Search
Context Related
| cs.ubc.ca/%7Enando/papers...fastmax.pdf Cached: PS.gz PS PDF This document uses CoBlitz to cache paper downloads. If your firewall is blocking outgoing connections to port 3125, you can use these links to download local copies.
Image Update HelpPS.gz PS PDF From: sigproc.eng.cam.ac.uk/sm...papers (more) (Enter author homepages) |
Rate this article:      (best)Comment on this article |
Abstract: Many important algorithms for statistical inference can be expressed as a weighted maxkernel search problem. This is the case with the Viterbi algorithm for HMMs, message construction in maximum a posteriori BP (max-BP), as well as certain particlesmoothing algorithms. Previous work has focused on reducing the cost of this procedure in discrete regular grids [4]. MonteCarlo state spaces, which are vital for highdimensional inference, cannot be handled by these techniques. We present... (Update)
Cited by: More
Fast Particle Smoothing: If I Had a Million Particles - Klaas, Briers, de.. (Correct)
Active bibliography (related documents): More All
2.1: Fast maximum a posteriori inference in Monte Carlo state spaces - Mike Klaas Dustin (2005) (Correct)
0.5: Distance Transforms of Sampled Functions - Pedro Felzenszwalb Daniel (Correct)
0.3: Tracking Complex Objects Using Graphical Object Models - Sigal, Zhu, Comaniciu, Black (2004) (Correct)
Similar documents based on text:
0.0: Unknown - (Correct)
BibTeX entry: (Update)
Klaas, M., Lang, D., & de Freitas, N. (2005). Fast maximum a posteriori inference in Monte Carlo state spaces. Artificial Intelligence and Statistics. http://citeseer.ist.psu.edu/article/klaas05fast.html More
@misc{ klaas05fast,
author = "M. Klaas and D. Lang and N. de Freitas",
title = "Fast maximum a posteriori inference in Monte Carlo state spaces",
text = "Klaas, M., Lang, D., & de Freitas, N. (2005). Fast maximum a posteriori
inference in Monte Carlo state spaces. Artificial Intelligence and Statistics.",
year = "2005",
url = "citeseer.ist.psu.edu/article/klaas05fast.html" }
Citations (may not include all citations):1543 Probabilistic reasoning in intelligent systems: networks of .. (context) - Pearl - 1988
406 Sequential Monte Carlo methods in practice (context) - Doucet, de Freitas et al. - 2001
146 Monte Carlo statistical methods - Robert, Casella - 1999
22 The Anchors Hierarchy: Using the triangle inequality to surv.. - Moore - 2000
19 Recursive Bayesian estimation: Navigation and tracking appli.. (context) - Bergman - 1999
13 Maximum a posteriori sequence estimation using Monte Carlo p.. - Godsill, Doucet et al. - 2001
11 Body' problems in statistical learning (context) - Gray, Moore - 2000
6 Rapid evaluation of multiple density models - Gray, Moore - 2003
6 Fast algorithms for large-state-space HMMs with applications.. - Felzenszwalb, Huttenlocher et al. - 2003
3 cient belief propagation for early vision (context) - Felzenszwalb, Huttenlocher - 2004
3 cient multiscale sampling from products of Gaussian mixtures (context) - Ihler, Sudderth et al. - 2003
3 Beat tracking the graphical model way (context) - Lang, de Freitas - 2004
2 Shape matching with belief propagation: Using dynamic quanti.. (context) - Coughlan, Shen - 2004
Documents on the same site (http://www-sigproc.eng.cam.ac.uk/smc/papers.html): More
Rao-Blackwellized Monte Carlo Data Association for.. - Särkkä, Vehtari.. (Correct)
Data Fusion for Visual Tracking with Particles - Perez, Vermaak, Blake (2004) (Correct)
Multi-Robot Cooperative Localization: A Study of.. - Rekleitis, Dudek, Milios (2002) (Correct)
Online articles have much greater impact More about CiteSeer.IST Add search form to your site Submit documents Feedback
CiteSeer.IST - Copyright Penn State and NEC