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JMLR
2010
91views more  JMLR 2010»
13 years 7 months ago
Convexity of Proper Composite Binary Losses
A composite loss assigns a penalty to a realvalued prediction by associating the prediction with a probability via a link function then applying a class probability estimation (CP...
Mark D. Reid, Robert C. Williamson
JMLR
2010
119views more  JMLR 2010»
13 years 7 months ago
Online Passive-Aggressive Algorithms on a Budget
Zhuang Wang, Slobodan Vucetic
JMLR
2010
177views more  JMLR 2010»
13 years 7 months ago
Multitask Learning for Brain-Computer Interfaces
Brain-computer interfaces (BCIs) are limited in their applicability in everyday settings by the current necessity to record subjectspecific calibration data prior to actual use of...
Morteza Alamgir, Moritz Grosse-Wentrup, Yasemin Al...
JMLR
2010
103views more  JMLR 2010»
13 years 7 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
JMLR
2010
159views more  JMLR 2010»
13 years 7 months ago
Semi-Supervised Learning with Max-Margin Graph Cuts
This paper proposes a novel algorithm for semisupervised learning. This algorithm learns graph cuts that maximize the margin with respect to the labels induced by the harmonic fun...
Branislav Kveton, Michal Valko, Ali Rahimi, Ling H...
JMLR
2010
175views more  JMLR 2010»
13 years 7 months ago
Bayesian variable order Markov models
Christos Dimitrakakis
JMLR
2010
129views more  JMLR 2010»
13 years 7 months ago
Approximation of hidden Markov models by mixtures of experts with application to particle filtering
Selecting conveniently the proposal kernel and the adjustment multiplier weights of the auxiliary particle filter may increase significantly the accuracy and computational efficie...
Jimmy Olsson, Jonas Ströjby
JMLR
2010
69views more  JMLR 2010»
13 years 7 months ago
Nonparametric prior for adaptive sparsity
Vikas C. Raykar, Linda H. Zhao
JMLR
2010
110views more  JMLR 2010»
13 years 7 months ago
Nonlinear functional regression: a functional RKHS approach
This paper deals with functional regression, in which the input attributes as well as the response are functions. To deal with this problem, we develop a functional reproducing ke...
Hachem Kadri, Emmanuel Duflos, Philippe Preux, St&...