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» A Framework for Multiple-Instance Learning
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190
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CVPR
2006
IEEE
16 years 9 months ago
Joint Boosting Feature Selection for Robust Face Recognition
A fundamental challenge in face recognition lies in determining what facial features are important for the identification of faces. In this paper, a novel face recognition framewo...
Rong Xiao, Wu-Jun Li, Yuandong Tian, Xiaoou Tang
219
Voted
KDD
2009
ACM
611views Data Mining» more  KDD 2009»
16 years 7 months ago
Fast approximate spectral clustering
Spectral clustering refers to a flexible class of clustering procedures that can produce high-quality clusterings on small data sets but which has limited applicability to large-s...
Donghui Yan, Ling Huang, Michael I. Jordan
KDD
2010
ACM
235views Data Mining» more  KDD 2010»
15 years 11 months ago
New perspectives and methods in link prediction
This paper examines important factors for link prediction in networks and provides a general, high-performance framework for the prediction task. Link prediction in sparse network...
Ryan Lichtenwalter, Jake T. Lussier, Nitesh V. Cha...
AIIDE
2007
15 years 9 months ago
Personality-based Adaptation for Teamwork in Game Agents
This paper presents a novel learning framework to provide computer game agents the ability to adapt to the player as well as other game agents. Our technique generally involves a ...
Chek Tien Tan, Ho-Lun Cheng
238
Voted
AAAI
1994
15 years 8 months ago
Solution Reuse in Dynamic Constraint Satisfaction Problems
Many AI problems can be modeled as constraint satisfaction problems (CSP), but many of them are actually dynamic: the set of constraints to consider evolves because of the environ...
Gérard Verfaillie, Thomas Schiex