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» Hedging predictions in machine learning
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128
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ICML
2009
IEEE
16 years 5 months ago
Graph construction and b-matching for semi-supervised learning
Graph based semi-supervised learning (SSL) methods play an increasingly important role in practical machine learning systems. A crucial step in graph based SSL methods is the conv...
Tony Jebara, Jun Wang, Shih-Fu Chang
141
Voted
JSA
2006
97views more  JSA 2006»
15 years 4 months ago
Dynamic feature selection for hardware prediction
It is often possible to greatly improve the performance of a hardware system via the use of predictive (speculative) techniques. For example, the performance of out-of-order micro...
Alan Fern, Robert Givan, Babak Falsafi, T. N. Vija...
ICML
2009
IEEE
16 years 5 months ago
Multi-class image segmentation using conditional random fields and global classification
A key aspect of semantic image segmentation is to integrate local and global features for the prediction of local segment labels. We present an approach to multi-class segmentatio...
Nils Plath, Marc Toussaint, Shinichi Nakajima
ICML
2009
IEEE
16 years 5 months ago
A Bayesian approach to protein model quality assessment
Given multiple possible models b1, b2, . . . bn for a protein structure, a common sub-task in in-silico Protein Structure Prediction is ranking these models according to their qua...
Hetunandan Kamisetty, Christopher James Langmead
ICML
2008
IEEE
16 years 5 months ago
Beam sampling for the infinite hidden Markov model
The infinite hidden Markov model is a nonparametric extension of the widely used hidden Markov model. Our paper introduces a new inference algorithm for the infinite Hidden Markov...
Jurgen Van Gael, Yunus Saatci, Yee Whye Teh, Zoubi...