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» Algorithmic Randomness of Closed Sets
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NIPS
2007
15 years 5 months ago
Optimistic Linear Programming gives Logarithmic Regret for Irreducible MDPs
We present an algorithm called Optimistic Linear Programming (OLP) for learning to optimize average reward in an irreducible but otherwise unknown Markov decision process (MDP). O...
Ambuj Tewari, Peter L. Bartlett
137
Voted
COLT
2001
Springer
15 years 8 months ago
Smooth Boosting and Learning with Malicious Noise
We describe a new boosting algorithm which generates only smooth distributions which do not assign too much weight to any single example. We show that this new boosting algorithm ...
Rocco A. Servedio
FOCS
2008
IEEE
15 years 10 months ago
Noise Tolerance of Expanders and Sublinear Expander Reconstruction
We consider the problem of online sublinear expander reconstruction and its relation to random walks in “noisy” expanders. Given access to an adjacency list representation of ...
Satyen Kale, Yuval Peres, C. Seshadhri
ICALP
2007
Springer
15 years 10 months ago
Reconciling Data Compression and Kolmogorov Complexity
While data compression and Kolmogorov complexity are both about effective coding of words, the two settings differ in the following respect. A compression algorithm or compressor...
Laurent Bienvenu, Wolfgang Merkle
ACTA
2000
82views more  ACTA 2000»
15 years 4 months ago
Semantics analysis through elementary meanings
Thesaurus is a collection of words classified according to some relatedness measures among them. In this paper, we lay the theoretical foundations of thesaurus construction through...
Youichi Kobuchi, Takashi Saito, Hidenobu Nunome