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NIPS
1998
15 years 8 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
TCOM
2008
84views more  TCOM 2008»
15 years 6 months ago
On the Performance of Closed-Loop Transmit Diversity with Noisy Channel Estimates and Finite-Depth Interleaved Convolutional Cod
Abstract-- In this paper, closed-form expressions for the uncoded bit error probability of closed-loop transmit diversity (CLTD) algorithms with two transmit and one receive antenn...
Jittra Jootar, James R. Zeidler, John G. Proakis
IHI
2012
217views Healthcare» more  IHI 2012»
14 years 2 months ago
Declarative privacy policy: finite models and attribute-based encryption
Regulations and policies regarding Electronic Health Information (EHI) are increasingly complex. Federal and State policy makers have called for both education to increase stakeho...
Peifung E. Lam, John C. Mitchell, Andre Scedrov, S...
CDC
2010
IEEE
129views Control Systems» more  CDC 2010»
15 years 1 months ago
A symbolic approach to controlling piecewise affine systems
Abstract-- We present a computational framework for automatic synthesis of a feedback control strategy for a piecewise affine (PWA) system from a specification given as a Linear Te...
Jana Tumova, Boyan Yordanov, Calin Belta, Ivana Ce...
CORR
2010
Springer
92views Education» more  CORR 2010»
15 years 6 months ago
Parameterizing by the Number of Numbers
The usefulness of parameterized algorithmics has often depended on what Niedermeier has called, "the art of problem parameterization." In this paper we introduce and expl...
Michael R. Fellows, Serge Gaspers, Frances A. Rosa...