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MIR
2005
ACM
129views Multimedia» more  MIR 2005»
14 years 2 months ago
Tracking concept drifting with an online-optimized incremental learning framework
Concept drifting is an important and challenging research issue in the field of machine learning. This paper mainly addresses the issue of semantic concept drifting in time series...
Jun Wu, Dayong Ding, Xian-Sheng Hua, Bo Zhang
GECCO
2008
Springer
155views Optimization» more  GECCO 2008»
13 years 10 months ago
Towards memoryless model building
Probabilistic model building methods can render difficult problems feasible by identifying and exploiting dependencies. They build a probabilistic model from the statistical prope...
David Iclanzan, Dumitru Dumitrescu
ICML
2003
IEEE
14 years 9 months ago
Bayes Meets Bellman: The Gaussian Process Approach to Temporal Difference Learning
We present a novel Bayesian approach to the problem of value function estimation in continuous state spaces. We define a probabilistic generative model for the value function by i...
Yaakov Engel, Shie Mannor, Ron Meir
SASO
2008
IEEE
14 years 3 months ago
Leveraging Organizational Guidance Policies with Learning to Self-Tune Multiagent Systems
As organization-based multiagent systems are applied to more complex problems, configuring and tuning the systems can become nearly as complex as the original problem a system wa...
Scott J. Harmon, Scott A. DeLoach, Robby, Doina Ca...
ICAC
2005
IEEE
14 years 2 months ago
PICCIL: Interactive Learning to Support Log File Categorization
Motivated by the real-world application of categorizing system log messages into defined situation categories, this paper describes an interactive text categorization method, PICC...
David Loewenstern, Sheng Ma, Abdi Salahshour