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COLT
2008
Springer
15 years 6 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
JMLR
2010
118views more  JMLR 2010»
14 years 11 months ago
Learning to Rank for Personalized News Article Retrieval
This paper aims to tackle the very interesting and important problem of user personalized ranking of search results. The focus is on news retrieval and the data from which the ran...
Lorand Dali, Blaz Fortuna, Jan Rupnik
139
Voted
ML
2008
ACM
15 years 4 months ago
Inductive process modeling
In this paper, we pose a novel research problem for machine learning that involves constructing a process model from continuous data. We claim that casting learned knowledge in ter...
Will Bridewell, Pat Langley, Ljupco Todorovski, Sa...
CITA
2005
IEEE
15 years 9 months ago
Cache Hierarchy Inspired Compression: a Novel Architecture for Data Streams
- We present an architecture for data streams based on structures typically found in web cache hierarchies. The main idea is to build a meta level analyser from a number of levels ...
Geoffrey Holmes, Bernhard Pfahringer, Richard Kirk...
JMLR
2010
163views more  JMLR 2010»
14 years 11 months ago
Active Sequential Learning with Tactile Feedback
We consider the problem of tactile discrimination, with the goal of estimating an underlying state parameter in a sequential setting. If the data is continuous and highdimensional...
Hannes Saal, Jo-Anne Ting, Sethu Vijayakumar