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» On the Convergence of Bound Optimization Algorithms
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ATAL
2010
Springer
13 years 8 months ago
Asynchronous algorithms for approximate distributed constraint optimization with quality bounds
Distributed Constraint Optimization (DCOP) is a popular framework for cooperative multi-agent decision making. DCOP is NPhard, so an important line of work focuses on developing f...
Christopher Kiekintveld, Zhengyu Yin, Atul Kumar, ...
ISNN
2007
Springer
14 years 1 months ago
Neural Networks Training with Optimal Bounded Ellipsoid Algorithm
Abstract. Compared to normal learning algorithms, for example backpropagation, the optimal bounded ellipsoid (OBE) algorithm has some better properties, such as faster convergence,...
José de Jesús Rubio, Wen Yu
CORR
2006
Springer
172views Education» more  CORR 2006»
13 years 7 months ago
Approximate Convex Optimization by Online Game Playing
This paper describes a general framework for converting online game playing algorithms into constrained convex optimization algorithms. This framework allows us to convert the wel...
Elad Hazan
GECCO
2007
Springer
192views Optimization» more  GECCO 2007»
14 years 1 months ago
Convergence of stochastic search algorithms to gap-free pareto front approximations
Recently, a convergence proof of stochastic search algorithms toward finite size Pareto set approximations of continuous multi-objective optimization problems has been given. The...
Oliver Schütze, Marco Laumanns, Emilia Tantar...
NIPS
1998
13 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