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HIS
2009
15 years 2 months ago
A Particle Swarm Optimization with Feasibility-Based Rules for Mixed-Variable Optimization Problems
A Particle Swarm Optimization algorithm with feasibility-based rules (FRPSO) is proposed in this paper to solve mixed-variable optimization problems. An approach to handle various ...
Chao-Li Sun, Jian-Chao Zeng, Jeng-Shyang Pan
CORR
2010
Springer
125views Education» more  CORR 2010»
15 years 5 months ago
Near-Optimal Bayesian Active Learning with Noisy Observations
We tackle the fundamental problem of Bayesian active learning with noise, where we need to adaptively select from a number of expensive tests in order to identify an unknown hypot...
Daniel Golovin, Andreas Krause, Debajyoti Ray
ICML
2002
IEEE
16 years 5 months ago
Hierarchically Optimal Average Reward Reinforcement Learning
Two notions of optimality have been explored in previous work on hierarchical reinforcement learning (HRL): hierarchical optimality, or the optimal policy in the space defined by ...
Mohammad Ghavamzadeh, Sridhar Mahadevan
IBIS
2006
109views more  IBIS 2006»
15 years 4 months ago
Formulation Schema Matching Problem for Combinatorial Optimization Problem
: Schema matching is the task of finding semantic correspondences between elements of two schemas, which plays a key role in many database applications. In this paper, we cast the ...
Zhi Zhang, Pengfei Shi, Haoyang Che, Yong Sun, Jun...
JGO
2010
117views more  JGO 2010»
15 years 3 months ago
Machine learning problems from optimization perspective
Both optimization and learning play important roles in a system for intelligent tasks. On one hand, we introduce three types of optimization tasks studied in the machine learning l...
Lei Xu