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» Bounding the cost of learned rules
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ICML
2003
IEEE
14 years 8 months ago
Online Ranking/Collaborative Filtering Using the Perceptron Algorithm
In this paper we present a simple to implement truly online large margin version of the Perceptron ranking (PRank) algorithm, called the OAP-BPM (Online Aggregate Prank-Bayes Poin...
Edward F. Harrington
CLOUDCOM
2010
Springer
13 years 5 months ago
Bag-of-Tasks Scheduling under Budget Constraints
Commercial cloud offerings, such as Amazon's EC2, let users allocate compute resources on demand, charging based on reserved time intervals. While this gives great flexibilit...
Ana-Maria Oprescu, Thilo Kielmann
NIPS
2007
13 years 8 months ago
A New View of Automatic Relevance Determination
Automatic relevance determination (ARD) and the closely-related sparse Bayesian learning (SBL) framework are effective tools for pruning large numbers of irrelevant features leadi...
David P. Wipf, Srikantan S. Nagarajan
ICML
2005
IEEE
14 years 8 months ago
Computational aspects of Bayesian partition models
The conditional distribution of a discrete variable y, given another discrete variable x, is often specified by assigning one multinomial distribution to each state of x. The cost...
Mikko Koivisto, Kismat Sood
GECCO
2008
Springer
155views Optimization» more  GECCO 2008»
13 years 8 months ago
Towards memoryless model building
Probabilistic model building methods can render difficult problems feasible by identifying and exploiting dependencies. They build a probabilistic model from the statistical prope...
David Iclanzan, Dumitru Dumitrescu