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» On learning algorithm selection for classification
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MLCW
2005
Springer
14 years 2 months ago
Evaluating Predictive Uncertainty Challenge
This Chapter presents the PASCAL1 Evaluating Predictive Uncertainty Challenge, introduces the contributed Chapters by the participants who obtained outstanding results, and provide...
Joaquin Quiñonero Candela, Carl Edward Rasm...
JAIR
2011
134views more  JAIR 2011»
13 years 3 months ago
Scaling up Heuristic Planning with Relational Decision Trees
Current evaluation functions for heuristic planning are expensive to compute. In numerous planning problems these functions provide good guidance to the solution, so they are wort...
Tomás de la Rosa, Sergio Jiménez, Ra...
KDD
2008
ACM
178views Data Mining» more  KDD 2008»
14 years 9 months ago
Training structural svms with kernels using sampled cuts
Discriminative training for structured outputs has found increasing applications in areas such as natural language processing, bioinformatics, information retrieval, and computer ...
Chun-Nam John Yu, Thorsten Joachims
CVPR
2006
IEEE
14 years 11 months ago
BoostMotion: Boosting a Discriminative Similarity Function for Motion Estimation
Motion estimation for applications where appearance undergoes complex changes is challenging due to lack of an appropriate similarity function. In this paper, we propose to learn ...
Shaohua Kevin Zhou, Bogdan Georgescu, Dorin Comani...
CORR
2011
Springer
192views Education» more  CORR 2011»
13 years 3 months ago
Distribution-Independent Evolvability of Linear Threshold Functions
Valiant’s (2007) model of evolvability models the evolutionary process of acquiring useful functionality as a restricted form of learning from random examples. Linear threshold ...
Vitaly Feldman