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» Learning Model Complexity in an Online Environment
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Publication
353views
15 years 4 months ago
Online Multi-Person Tracking-by-Detection from a Single, Uncalibrated Camera
In this paper, we address the problem of automatically detecting and tracking a variable number of persons in complex scenes using a monocular, potentially moving, uncalibrated ca...
Michael D. Breitenstein, Fabian Reichlin, Bastian ...
162
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ICCV
2009
IEEE
15 years 1 months ago
Real-time visual tracking via Incremental Covariance Tensor Learning
Visual tracking is a challenging problem, as an object may change its appearance due to pose variations, illumination changes, and occlusions. Many algorithms have been proposed t...
Yi Wu, Jian Cheng, Jinqiao Wang, Hanqing Lu
134
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ML
2000
ACM
150views Machine Learning» more  ML 2000»
15 years 3 months ago
Adaptive Retrieval Agents: Internalizing Local Context and Scaling up to the Web
This paper discusses a novel distributed adaptive algorithm and representation used to construct populations of adaptive Web agents. These InfoSpiders browse networked information ...
Filippo Menczer, Richard K. Belew
131
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ACMACE
2006
ACM
15 years 9 months ago
Motivated reinforcement learning for non-player characters in persistent computer game worlds
Massively multiplayer online computer games are played in complex, persistent virtual worlds. Over time, the landscape of these worlds evolves and changes as players create and pe...
Kathryn Elizabeth Merrick, Mary Lou Maher
161
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GECCO
2008
Springer
155views Optimization» more  GECCO 2008»
15 years 4 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