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ML
2002
ACM
220views Machine Learning» more  ML 2002»
13 years 8 months ago
Bayesian Methods for Support Vector Machines: Evidence and Predictive Class Probabilities
I describe a framework for interpreting Support Vector Machines (SVMs) as maximum a posteriori (MAP) solutions to inference problems with Gaussian Process priors. This probabilisti...
Peter Sollich
IJCAT
2010
133views more  IJCAT 2010»
13 years 7 months ago
A 3D shape classifier with neural network supervision
: The task of 3D shape classification is to assign a set of unordered shapes into pre-tagged classes with class labels, and find the most suitable class for a newly given shape. In...
Zhenbao Liu, Jun Mitani, Yukio Fukui, Seiichi Nish...
CC
2010
Springer
282views System Software» more  CC 2010»
13 years 7 months ago
Lower Bounds on the Randomized Communication Complexity of Read-Once Functions
Abstract. We prove lower bounds on the randomized two-party communication complexity of functions that arise from read-once boolean formulae. A read-once boolean formula is a formu...
Nikos Leonardos, Michael Saks
CIKM
2010
Springer
13 years 7 months ago
Online stratified sampling: evaluating classifiers at web-scale
Deploying a classifier to large-scale systems such as the web requires careful feature design and performance evaluation. Evaluation is particularly challenging because these larg...
Paul N. Bennett, Vitor R. Carvalho
COLT
2010
Springer
13 years 7 months ago
Regret Minimization With Concept Drift
In standard online learning, the goal of the learner is to maintain an average loss that is "not too big" compared to the loss of the best-performing function in a fixed...
Koby Crammer, Yishay Mansour, Eyal Even-Dar, Jenni...