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IJCAI
2007
15 years 8 months ago
Using Linear Programming for Bayesian Exploration in Markov Decision Processes
A key problem in reinforcement learning is finding a good balance between the need to explore the environment and the need to gain rewards by exploiting existing knowledge. Much ...
Pablo Samuel Castro, Doina Precup
KDD
2004
ACM
127views Data Mining» more  KDD 2004»
16 years 7 months ago
A generative probabilistic approach to visualizing sets of symbolic sequences
There is a notable interest in extending probabilistic generative modeling principles to accommodate for more complex structured data types. In this paper we develop a generative ...
Peter Tiño, Ata Kabán, Yi Sun
SIGIR
2009
ACM
16 years 1 months ago
Personalized music emotion recognition
In recent years, there has been a dramatic proliferation of research on information retrieval based on highly subjective concepts such as emotion, preference and aesthetic. Such r...
Yi-Hsuan Yang, Yu-Ching Lin, Homer H. Chen
IJCV
2000
161views more  IJCV 2000»
15 years 6 months ago
Probabilistic Detection and Tracking of Motion Boundaries
We propose a Bayesian framework for representing and recognizing local image motion in terms of two basic models: translational motion and motion boundaries. Motion boundaries are ...
Michael J. Black, David J. Fleet
168
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WSC
1994
15 years 8 months ago
Inside simulation software: how it works and why it matters
ABSTRACT This paper provides beginning and intermediate simulation practitioners and interested simulation consumers with a grounding in how discrete-event simulation software work...
Thomas J. Schriber, Daniel T. Brunner