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ICML
2005
IEEE
16 years 5 months ago
Active learning for Hidden Markov Models: objective functions and algorithms
Hidden Markov Models (HMMs) model sequential data in many fields such as text/speech processing and biosignal analysis. Active learning algorithms learn faster and/or better by cl...
Brigham Anderson, Andrew Moore
ICDE
2007
IEEE
89views Database» more  ICDE 2007»
15 years 8 months ago
A Flexible Query Graph Based Model for the Efficient Execution of Continuous Queries
In this paper, we propose a simple and flexible execution model that (i) supports a wide spectrum of alternative optimization and execution strategies and their mixtures, (ii) pro...
Yijian Bai, Hetal Thakkar, Haixun Wang, Carlo Zani...
AAAI
1996
15 years 5 months ago
Learning Models of Intelligent Agents
Agents that operate in a multi-agent system need an efficient strategy to handle their encounters with other agents involved. Searching for an optimal interactive strategy is a ha...
David Carmel, Shaul Markovitch
TNN
1998
112views more  TNN 1998»
15 years 4 months ago
A class of competitive learning models which avoids neuron underutilization problem
— In this paper, we study a qualitative property of a class of competitive learning (CL) models, which is called the multiplicatively biased competitive learning (MBCL) model, na...
Clifford Sze-Tsan Choy, Wan-Chi Siu
CEC
2007
IEEE
15 years 10 months ago
Convergence and rate of convergence of a foraging ant model
— We present an ant model that solves a discrete foraging problem. We describe simulations and provide a complete convergence analysis: we show that the ant population computes t...
Amine M. Boumaza, Bruno Scherrer