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» Proving Time Bounds for Randomized Distributed Algorithms
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NIPS
1998
14 years 11 months ago
Finite-Sample Convergence Rates for Q-Learning and Indirect Algorithms
In this paper, we address two issues of long-standing interest in the reinforcement learning literature. First, what kinds of performance guarantees can be made for Q-learning aft...
Michael J. Kearns, Satinder P. Singh
COLT
1994
Springer
15 years 2 months ago
Learning Probabilistic Automata with Variable Memory Length
We propose and analyze a distribution learning algorithm for variable memory length Markov processes. These processes can be described by a subclass of probabilistic nite automata...
Dana Ron, Yoram Singer, Naftali Tishby
STACS
1999
Springer
15 years 2 months ago
A Complete and Tight Average-Case Analysis of Learning Monomials
Abstract. We advocate to analyze the average complexity of learning problems. An appropriate framework for this purpose is introduced. Based on it we consider the problem of learni...
Rüdiger Reischuk, Thomas Zeugmann
COMPGEOM
2009
ACM
15 years 4 months ago
Epsilon nets and union complexity
We consider the following combinatorial problem: given a set of n objects (for example, disks in the plane, triangles), and an integer L ≥ 1, what is the size of the smallest su...
Kasturi R. Varadarajan
ANOR
2002
99views more  ANOR 2002»
14 years 9 months ago
An Inventory-Location Model: Formulation, Solution Algorithm and Computational Results
We introduce a distribution center (DC) location model that incorporates working inventory and safety stock inventory costs at the distribution centers. In addition, the model inco...
Mark S. Daskin, Collette R. Coullard, Zuo-Jun Max ...