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» Evaluating algorithms that learn from data streams
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148
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SIGIR
2012
ACM
13 years 2 months ago
Top-k learning to rank: labeling, ranking and evaluation
In this paper, we propose a novel top-k learning to rank framework, which involves labeling strategy, ranking model and evaluation measure. The motivation comes from the difficul...
Shuzi Niu, Jiafeng Guo, Yanyan Lan, Xueqi Cheng
97
Voted
IROS
2008
IEEE
203views Robotics» more  IROS 2008»
15 years 7 months ago
Learning equivalent action choices from demonstration
Abstract— In their interactions with the world robots inevitably face equivalent action choices, situations in which multiple actions are equivalently applicable. In this paper, ...
Sonia Chernova, Manuela M. Veloso
87
Voted
WDAG
2007
Springer
68views Algorithms» more  WDAG 2007»
15 years 6 months ago
Push-to-Pull Peer-to-Peer Live Streaming
In contrast to peer-to-peer file sharing, live streaming based on peer-to-peer technology is still awaiting its breakthrough. This may be due to the additional challenges live str...
Thomas Locher, Remo Meier, Stefan Schmid, Roger Wa...
WWW
2009
ACM
16 years 1 months ago
Unsupervised query categorization using automatically-built concept graphs
Automatic categorization of user queries is an important component of general purpose (Web) search engines, particularly for triggering rich, query-specific content and sponsored ...
Eustache Diemert, Gilles Vandelle
82
Voted
IJCNN
2006
IEEE
15 years 6 months ago
Support Vector Machines to Weight Voters in a Voting System of Entity Extractors
—Support Vector Machines are used to combine the outputs of multiple entity extractors, thus creating a composite entity extraction system. The composite system has a significant...
Deborah Duong, James Venuto, Ben Goertzel, Ryan Ri...