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» Evaluating algorithms that learn from data streams
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191
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BMCBI
2005
122views more  BMCBI 2005»
15 years 7 months ago
FACT - a framework for the functional interpretation of high-throughput experiments
Background: Interpreting the results of high-throughput experiments, such as those obtained from DNA-microarrays, is an often time-consuming task due to the high number of data-po...
Felix Kokocinski, Nicolas Delhomme, Gunnar Wrobel,...
NIPS
2007
15 years 8 months ago
Modeling Natural Sounds with Modulation Cascade Processes
Natural sounds are structured on many time-scales. A typical segment of speech, for example, contains features that span four orders of magnitude: Sentences (∼1 s); phonemes (âˆ...
Richard Turner, Maneesh Sahani
DATAMINE
2008
143views more  DATAMINE 2008»
15 years 7 months ago
Automatically countering imbalance and its empirical relationship to cost
Learning from imbalanced datasets presents a convoluted problem both from the modeling and cost standpoints. In particular, when a class is of great interest but occurs relatively...
Nitesh V. Chawla, David A. Cieslak, Lawrence O. Ha...
195
Voted
ICCV
2009
IEEE
17 years 12 days ago
Automatic annotation of human actions in video
This paper addresses the problem of automatic temporal annotation of realistic human actions in video using mini- mal manual supervision. To this end we consider two asso- ciate...
Olivier Duchenne, Ivan Laptev, Josef Sivic, Franci...
ATAL
2006
Springer
15 years 11 months ago
Efficient agents for cliff-edge environments with a large set of decision options
This paper proposes an efficient agent for competing in Cliff Edge (CE) environments, such as sealed-bid auctions, dynamic pricing and the ultimatum game. The agent competes in on...
Ron Katz, Sarit Kraus