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AAAI
2006
13 years 11 months ago
Action Selection in Bayesian Reinforcement Learning
My research attempts to address on-line action selection in reinforcement learning from a Bayesian perspective. The idea is to develop more effective action selection techniques b...
Tao Wang
CORR
2006
Springer
138views Education» more  CORR 2006»
13 years 10 months ago
Tight Bounds on the Complexity of Recognizing Odd-Ranked Elements
Let S = s1, s2, s3, ..., sn be a given vector of n distinct real numbers. The rank of z R with respect to S is defined as the number of elements si S such that si z. We consider...
Shripad Thite
SIGMOD
2004
ACM
262views Database» more  SIGMOD 2004»
14 years 10 months ago
The Next Database Revolution
Database system architectures are undergoing revolutionary changes. Most importantly, algorithms and data are being unified by integrating programming languages with the database ...
Jim Gray
ICS
2010
Tsinghua U.
14 years 7 months ago
Distribution-Specific Agnostic Boosting
We consider the problem of boosting the accuracy of weak learning algorithms in the agnostic learning framework of Haussler (1992) and Kearns et al. (1992). Known algorithms for t...
Vitaly Feldman
MOBICOM
2009
ACM
14 years 4 months ago
Opportunistic flooding in low-duty-cycle wireless sensor networks with unreliable links
Intended for network-wide dissemination of commands, configurations and code binaries, flooding has been investigated extensively in wireless networks. However, little work has ...
Shuo Guo, Yu Gu, Bo Jiang, Tian He