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COLT
2007
Springer
14 years 1 months ago
Bounded Parameter Markov Decision Processes with Average Reward Criterion
Bounded parameter Markov Decision Processes (BMDPs) address the issue of dealing with uncertainty in the parameters of a Markov Decision Process (MDP). Unlike the case of an MDP, t...
Ambuj Tewari, Peter L. Bartlett
COLT
2007
Springer
14 years 1 months ago
Occam's Hammer
Abstract. We establish a generic theoretical tool to construct probabilistic bounds for algorithms where the output is a subset of objects from an initial pool of candidates (or mo...
Gilles Blanchard, François Fleuret
COLT
2007
Springer
14 years 1 months ago
Sparse Density Estimation with l1 Penalties
Florentina Bunea, Alexandre B. Tsybakov, Marten H....
COLT
2007
Springer
14 years 1 months ago
Mitotic Classes
For the natural notion of splitting classes into two disjoint subclasses via a recursive classifier working on texts, the question is addressed how these splittings can look in th...
Sanjay Jain, Frank Stephan
COLT
2007
Springer
14 years 1 months ago
Learning Large-Alphabet and Analog Circuits with Value Injection Queries
Abstract. We consider the problem of learning an acyclic discrete circuit with n wires, fan-in bounded by k and alphabet size s using value injection queries. For the class of tran...
Dana Angluin, James Aspnes, Jiang Chen, Lev Reyzin
COLT
2007
Springer
14 years 1 months ago
Sketching Information Divergences
When comparing discrete probability distributions, natural measures of similarity are not p distances but rather are informationdivergences such as Kullback-Leibler and Hellinger. ...
Sudipto Guha, Piotr Indyk, Andrew McGregor
COLT
2007
Springer
14 years 1 months ago
On-Line Estimation with the Multivariate Gaussian Distribution
We consider on-line density estimation with the multivariate Gaussian distribution. In each of a sequence of trials, the learner must posit a mean µ and covariance Σ; the learner...
Sanjoy Dasgupta, Daniel Hsu
COLT
2007
Springer
14 years 1 months ago
Property Testing: A Learning Theory Perspective
Property testing deals with tasks where the goal is to distinguish between the case that an object (e.g., function or graph) has a prespecified property (e.g., the function is li...
Dana Ron