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ECCV
1994
Springer
15 years 8 months ago
Markov Random Field Models in Computer Vision
A variety of computer vision problems can be optimally posed as Bayesian labeling in which the solution of a problem is dened as the maximum a posteriori (MAP) probability estimate...
Stan Z. Li
CORR
2010
Springer
92views Education» more  CORR 2010»
15 years 3 months ago
Random Projections for $k$-means Clustering
This paper discusses the topic of dimensionality reduction for k-means clustering. We prove that any set of n points in d dimensions (rows in a matrix A ∈ Rn×d ) can be project...
Christos Boutsidis, Anastasios Zouzias, Petros Dri...
FOCS
2010
IEEE
15 years 2 months ago
Black-Box Randomized Reductions in Algorithmic Mechanism Design
We give the first black-box reduction from arbitrary approximation algorithms to truthful approximation mechanisms for a non-trivial class of multiparameter problems. Specifically,...
Shaddin Dughmi, Tim Roughgarden
TIT
2010
61views Education» more  TIT 2010»
14 years 11 months ago
Tunstall code, Khodak variations, and random walks
A variable-to-fixed length encoder partitions the source string into variable-length phrases that belong to a given and fixed dictionary. Tunstall, and independently Khodak, desig...
Michael Drmota, Yuriy A. Reznik, Wojciech Szpankow...
138
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ICIP
2005
IEEE
16 years 6 months ago
Multi-step active object tracking with entropy based optimal actions using the sequential Kalman filter
We describe an enhanced method for the selection of optimal sensor actions in a probabilistic state estimation framework. We apply this to the selection of optimal focal lengths f...
Benjamin Deutsch, Heinrich Niemann, Joachim Denzle...