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JMLR
2010
103views more  JMLR 2010»
14 years 10 months ago
Learning Nonlinear Dynamic Models from Non-sequenced Data
Virtually all methods of learning dynamic systems from data start from the same basic assumption: the learning algorithm will be given a sequence of data generated from the dynami...
Tzu-Kuo Huang, Le Song, Jeff Schneider
156
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ACL
2011
14 years 7 months ago
Event Extraction as Dependency Parsing
Nested event structures are a common occurrence in both open domain and domain specific extraction tasks, e.g., a “crime” event can cause a “investigation” event, which c...
David McClosky, Mihai Surdeanu, Christopher D. Man...
IWINAC
2011
Springer
14 years 6 months ago
Clustering of Trajectories in Video Surveillance Using Growing Neural Gas
Abstract. One of the more important issues in intelligent video surveillance systems is the ability to handle events from the motion of objects. Thus, the classification of the tr...
Javier Acevedo-Rodríguez, Saturnino Maldona...
RTAS
2011
IEEE
14 years 6 months ago
Maximizing Contention-Free Executions in Multiprocessor Scheduling
—It is widely assumed that scheduling real-time tasks becomes more difficult as their deadlines get shorter. With deadlines shorter, however, tasks potentially compete less with...
Jinkyu Lee, Arvind Easwaran, Insik Shin
SIGIR
2011
ACM
14 years 6 months ago
Learning to rank from a noisy crowd
We study how to best use crowdsourced relevance judgments learning to rank [1, 7]. We integrate two lines of prior work: unreliable crowd-based binary annotation for binary classi...
Abhimanu Kumar, Matthew Lease