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COLT
2008
Springer
15 years 9 months ago
Learning in the Limit with Adversarial Disturbances
We study distribution-dependent, data-dependent, learning in the limit with adversarial disturbance. We consider an optimization-based approach to learning binary classifiers from...
Constantine Caramanis, Shie Mannor
ML
1998
ACM
102views Machine Learning» more  ML 1998»
15 years 7 months ago
Statistical Mechanics of Online Learning of Drifting Concepts: A Variational Approach
We review the application of statistical mechanics methods to the study of online learning of a drifting concept in the limit of large systems. The model where a feed-forward netwo...
Renato Vicente, Osame Kinouchi, Nestor Caticha
PCM
2010
Springer
204views Multimedia» more  PCM 2010»
15 years 6 months ago
Learning Contextual Metrics for Automatic Image Annotation
Abstract. The semantic contextual information is shown to be an important resource for improving the scene and image recognition, but is seldom explored in the literature of previo...
Zuotao Liu, Xiangdong Zhou, Yu Xiang, Yan-Tao Zhen...
TCAD
2010
103views more  TCAD 2010»
15 years 2 months ago
Supervised Learning Based Power Management for Multicore Processors
- This paper presents a supervised learning based power management framework for a multi-processor system, where a power manager (PM) learns to predict the system performance state...
Hwisung Jung, Massoud Pedram
SIGMOD
2004
ACM
262views Database» more  SIGMOD 2004»
16 years 7 months ago
The Next Database Revolution
Database system architectures are undergoing revolutionary changes. Most importantly, algorithms and data are being unified by integrating programming languages with the database ...
Jim Gray