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» Performance comparison of memetic algorithms
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135
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NIPS
1998
15 years 4 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
136
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BNCOD
2009
162views Database» more  BNCOD 2009»
15 years 4 months ago
Answering Multiple-Item Queries in Data Broadcast Systems
A lot of research has been done on answering single-item queries, only a few have looked at answering multiple-item queries in data broadcast systems. The few that did, have propos...
Adesola Omotayo, Ken Barker, Moustafa A. Hammad, L...
136
Voted
JMLR
2010
107views more  JMLR 2010»
14 years 10 months ago
Learning Instance-Specific Predictive Models
This paper introduces a Bayesian algorithm for constructing predictive models from data that are optimized to predict a target variable well for a particular instance. This algori...
Shyam Visweswaran, Gregory F. Cooper
105
Voted
APPROX
2005
Springer
103views Algorithms» more  APPROX 2005»
15 years 9 months ago
Where's the Winner? Max-Finding and Sorting with Metric Costs
Traditionally, a fundamental assumption in evaluating the performance of algorithms for sorting and selection has been that comparing any two elements costs one unit (of time, work...
Anupam Gupta, Amit Kumar
130
Voted
GECCO
2003
Springer
245views Optimization» more  GECCO 2003»
15 years 8 months ago
A Non-dominated Sorting Particle Swarm Optimizer for Multiobjective Optimization
Abstract. This paper introduces a modified PSO, Non-dominated Sorting Particle Swarm Optimizer (NSPSO), for better multiobjective optimization. NSPSO extends the basic form of PSO...
Xiaodong Li