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» Learning Subjective Functions with Large Margins
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KDD
2007
ACM
132views Data Mining» more  KDD 2007»
14 years 8 months ago
A scalable modular convex solver for regularized risk minimization
A wide variety of machine learning problems can be described as minimizing a regularized risk functional, with different algorithms using different notions of risk and different r...
Choon Hui Teo, Alex J. Smola, S. V. N. Vishwanatha...
ACMICEC
2006
ACM
157views ECommerce» more  ACMICEC 2006»
14 years 2 months ago
Adaptive mechanism design: a metalearning approach
Auction mechanism design has traditionally been a largely analytic process, relying on assumptions such as fully rational bidders. In practice, however, bidders often exhibit unkn...
David Pardoe, Peter Stone, Maytal Saar-Tsechansky,...
IPSN
2010
Springer
14 years 3 months ago
Online distributed sensor selection
A key problem in sensor networks is to decide which sensors to query when, in order to obtain the most useful information (e.g., for performing accurate prediction), subject to co...
Daniel Golovin, Matthew Faulkner, Andreas Krause
BMCBI
2006
152views more  BMCBI 2006»
13 years 8 months ago
Predicting deleterious nsSNPs: an analysis of sequence and structural attributes
Background: There has been an explosion in the number of single nucleotide polymorphisms (SNPs) within public databases. In this study we focused on non-synonymous protein coding ...
Richard J. B. Dobson, Patricia B. Munroe, Mark J. ...
CORR
2010
Springer
177views Education» more  CORR 2010»
13 years 8 months ago
Supervised Random Walks: Predicting and Recommending Links in Social Networks
Predicting the occurrence of links is a fundamental problem in networks. In the link prediction problem we are given a snapshot of a network and would like to infer which interact...
Lars Backstrom, Jure Leskovec