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NIPS
2007
15 years 8 months ago
What makes some POMDP problems easy to approximate?
Point-based algorithms have been surprisingly successful in computing approximately optimal solutions for partially observable Markov decision processes (POMDPs) in high dimension...
David Hsu, Wee Sun Lee, Nan Rong
ICML
2010
IEEE
15 years 8 months ago
Learning Fast Approximations of Sparse Coding
In Sparse Coding (SC), input vectors are reconstructed using a sparse linear combination of basis vectors. SC has become a popular method for extracting features from data. For a ...
Karol Gregor, Yann LeCun
SIAMSC
2008
167views more  SIAMSC 2008»
15 years 6 months ago
Low-Dimensional Polytope Approximation and Its Applications to Nonnegative Matrix Factorization
In this study, nonnegative matrix factorization is recast as the problem of approximating a polytope on the probability simplex by another polytope with fewer facets. Working on th...
Moody T. Chu, Matthew M. Lin
ICDT
2009
ACM
148views Database» more  ICDT 2009»
16 years 7 months ago
Tight results for clustering and summarizing data streams
In this paper we investigate algorithms and lower bounds for summarization problems over a single pass data stream. In particular we focus on histogram construction and K-center c...
Sudipto Guha
STOC
2006
ACM
138views Algorithms» more  STOC 2006»
16 years 7 months ago
Searching dynamic point sets in spaces with bounded doubling dimension
We present a new data structure that facilitates approximate nearest neighbor searches on a dynamic set of points in a metric space that has a bounded doubling dimension. Our data...
Richard Cole, Lee-Ad Gottlieb