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» Progressive Optimization in Action
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TSMC
2002
102views more  TSMC 2002»
15 years 1 months ago
Generalized pursuit learning schemes: new families of continuous and discretized learning automata
The fastest learning automata (LA) algorithms currently available fall in the family of estimator algorithms introduced by Thathachar and Sastry [24]. The pioneering work of these ...
M. Agache, B. John Oommen
GECCO
2006
Springer
186views Optimization» more  GECCO 2006»
15 years 5 months ago
Genetic algorithms for action set selection across domains: a demonstration
Action set selection in Markov Decision Processes (MDPs) is an area of research that has received little attention. On the other hand, the set of actions available to an MDP agent...
Greg Lee, Vadim Bulitko
ICMLA
2007
15 years 3 months ago
Control of a re-entrant line manufacturing model with a reinforcement learning approach
This paper presents the application of a reinforcement learning (RL) approach for the near-optimal control of a re-entrant line manufacturing (RLM) model. The RL approach utilizes...
José A. Ramírez-Hernández, Em...
CVPR
2008
IEEE
16 years 3 months ago
Learning human actions via information maximization
In this paper, we present a novel approach for automatically learning a compact and yet discriminative appearance-based human action model. A video sequence is represented by a ba...
Jingen Liu, Mubarak Shah
CVPR
2008
IEEE
16 years 3 months ago
Discriminative human action segmentation and recognition using semi-Markov model
Given an input video sequence of one person conducting a sequence of continuous actions, we consider the problem of jointly segmenting and recognizing actions. We propose a discri...
Qinfeng Shi, Li Wang, Li Cheng, Alexander J. Smola