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ICML
2006
IEEE
15 years 10 months ago
Qualitative reinforcement learning
When the transition probabilities and rewards of a Markov Decision Process are specified exactly, the problem can be solved without any interaction with the environment. When no s...
Arkady Epshteyn, Gerald DeJong
ISSAC
1997
Springer
194views Mathematics» more  ISSAC 1997»
15 years 2 months ago
The Minimised Geometric Buchberger Algorithm: An Optimal Algebraic Algorithm for Integer Programming
IP problems characterise combinatorial optimisation problems where conventional numerical methods based on the hill-climbing technique can not be directly applied. Conventional me...
Qiang Li, Yike Guo, Tetsuo Ida, John Darlington
ICAI
2007
14 years 11 months ago
Dynamic Programming Algorithm for Training Functional Networks
Abstract— The paper proposes a dynamic programming algorithm for training of functional networks. The algorithm considers each node as a state. The problem is formulated as find...
Emad A. El-Sebakhy, Salahadin Mohammed, Moustafa E...
LION
2009
Springer
112views Optimization» more  LION 2009»
15 years 4 months ago
A Graph-Based Semi-supervised Algorithm for Protein Function Prediction from Interaction Maps
Abstract. Protein function prediction represents a fundamental challenge in bioinformatics. The increasing availability of proteomics network data has enabled the development of se...
Valerio Freschi
ISCIS
2003
Springer
15 years 3 months ago
A New Continuous Action-Set Learning Automaton for Function Optimization
In this paper, we study an adaptive random search method based on continuous action-set learning automaton for solving stochastic optimization problems in which only the noisecorr...
Hamid Beigy, Mohammad Reza Meybodi