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» LEO - DB2's LEarning Optimizer
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112
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SIGIR
2010
ACM
15 years 4 months ago
Extending average precision to graded relevance judgments
Evaluation metrics play a critical role both in the context of comparative evaluation of the performance of retrieval systems and in the context of learning-to-rank (LTR) as objec...
Stephen E. Robertson, Evangelos Kanoulas, Emine Yi...
120
Voted
ICCD
2000
IEEE
119views Hardware» more  ICCD 2000»
15 years 4 months ago
Source-Level Transformations for Improved Formal Verification
A major obstacle to widespread acceptance of formal verification is the difficulty in using the tools effectively. Although learning the basic syntax and operation of a formal ver...
Brian D. Winters, Alan J. Hu
109
Voted
GECCO
2010
Springer
158views Optimization» more  GECCO 2010»
15 years 4 months ago
Efficiently evolving programs through the search for novelty
A significant challenge in genetic programming is premature convergence to local optima, which often prevents evolution from solving problems. This paper introduces to genetic pro...
Joel Lehman, Kenneth O. Stanley
AAAI
2000
15 years 2 months ago
Decision Making under Uncertainty: Operations Research Meets AI (Again)
Models for sequential decision making under uncertainty (e.g., Markov decision processes,or MDPs) have beenstudied in operations research for decades. The recent incorporation of ...
Craig Boutilier
107
Voted
NIPS
1998
15 years 2 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