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PPOPP
2009
ACM
16 years 4 months ago
Mapping parallelism to multi-cores: a machine learning based approach
The efficient mapping of program parallelism to multi-core processors is highly dependent on the underlying architecture. This paper proposes a portable and automatic compiler-bas...
Zheng Wang, Michael F. P. O'Boyle
134
Voted
IUI
2003
ACM
15 years 9 months ago
Lessons learned in modeling schizophrenic and depressed responsive virtual humans for training
This paper describes lessons learned in developing the linguistic, cognitive, emotional, and gestural models underlying virtual human behavior in a training application designed t...
Robert C. Hubal, Geoffrey A. Frank, Curry I. Guinn
152
Voted
FLAIRS
2008
15 years 6 months ago
Learning a Probabilistic Model of Event Sequences from Internet Weblog Stories
One of the central problems in building broad-coverage story understanding systems is generating expectations about event sequences, i.e. predicting what happens next given some a...
Mehdi Manshadi, Reid Swanson, Andrew S. Gordon
IR
2010
15 years 2 months ago
Learning to rank with (a lot of) word features
In this article we present Supervised Semantic Indexing (SSI) which defines a class of nonlinear (quadratic) models that are discriminatively trained to directly map from the word...
Bing Bai, Jason Weston, David Grangier, Ronan Coll...
ICLP
2009
Springer
16 years 4 months ago
Generative Modeling by PRISM
PRISM is a probabilistic extension of Prolog. It is a high level language for probabilistic modeling capable of learning statistical parameters from observed data. After reviewing ...
Taisuke Sato