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AAAI
2010
13 years 11 months ago
Compressing POMDPs Using Locality Preserving Non-Negative Matrix Factorization
Partially Observable Markov Decision Processes (POMDPs) are a well-established and rigorous framework for sequential decision-making under uncertainty. POMDPs are well-known to be...
Georgios Theocharous, Sridhar Mahadevan
WSC
2000
13 years 11 months ago
Using simulation and critical points to define states in continuous search spaces
Many artificial intelligence techniques rely on the notion ate" as an abstraction of the actual state of the nd an "operator" as an abstraction of the actions that ...
Marc S. Atkin, Paul R. Cohen
STOC
1993
ACM
123views Algorithms» more  STOC 1993»
14 years 2 months ago
Constructing small sample spaces satisfying given constraints
Abstract. The subject of this paper is nding small sample spaces for joint distributions of n discrete random variables. Such distributions are often only required to obey a certa...
Daphne Koller, Nimrod Megiddo
TKDE
2008
141views more  TKDE 2008»
13 years 9 months ago
Location Fingerprinting In A Decorrelated Space
We present a novel approach to the problem of the indoor localization in wireless environments. The main contribution of this paper is four folds: (a) We show that, by projecting t...
Shih-Hau Fang, Tsung-Nan Lin, Po-Chiang Lin
NIPS
2003
13 years 11 months ago
Learning to Find Pre-Images
We consider the problem of reconstructing patterns from a feature map. Learning algorithms using kernels to operate in a reproducing kernel Hilbert space (RKHS) express their solu...
Gökhan H. Bakir, Jason Weston, Bernhard Sch&o...