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» Learning with the Set Covering Machine
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107
Voted
ICML
2005
IEEE
16 years 1 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
119
Voted
ICML
2003
IEEE
16 years 1 months ago
Online Convex Programming and Generalized Infinitesimal Gradient Ascent
Convex programming involves a convex set F Rn and a convex cost function c : F R. The goal of convex programming is to find a point in F which minimizes c. In online convex prog...
Martin Zinkevich
74
Voted
ICML
2002
IEEE
16 years 1 months ago
Univariate Polynomial Inference by Monte Carlo Message Length Approximation
We apply the Message from Monte Carlo (MMC) algorithm to inference of univariate polynomials. MMC is an algorithm for point estimation from a Bayesian posterior sample. It partiti...
Leigh J. Fitzgibbon, David L. Dowe, Lloyd Allison
115
Voted
ICML
2000
IEEE
16 years 1 months ago
Maximum Entropy Markov Models for Information Extraction and Segmentation
Hidden Markov models (HMMs) are a powerful probabilistic tool for modeling sequential data, and have been applied with success to many text-related tasks, such as part-of-speech t...
Andrew McCallum, Dayne Freitag, Fernando C. N. Per...
99
Voted
ALT
2008
Springer
15 years 9 months ago
Visual Analytics: Combining Automated Discovery with Interactive Visualizations
In numerous application areas fast growing data sets develop with ever higher complexity and dynamics. A central challenge is to filter the substantial information and to communic...
Daniel A. Keim, Florian Mansmann, Daniela Oelke, H...