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» Hedging predictions in machine learning
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ICML
2010
IEEE
15 years 5 months ago
Modeling Interaction via the Principle of Maximum Causal Entropy
The principle of maximum entropy provides a powerful framework for statistical models of joint, conditional, and marginal distributions. However, there are many important distribu...
Brian Ziebart, J. Andrew Bagnell, Anind K. Dey
PRL
2011
14 years 11 months ago
Efficient approximate Regularized Least Squares by Toeplitz matrix
Machine Learning based on the Regularized Least Square (RLS) model requires one to solve a system of linear equations. Direct-solution methods exhibit predictable complexity and s...
Sergio Decherchi, Paolo Gastaldo, Rodolfo Zunino
ICML
2005
IEEE
16 years 5 months ago
Bayesian hierarchical clustering
We present a novel algorithm for agglomerative hierarchical clustering based on evaluating marginal likelihoods of a probabilistic model. This algorithm has several advantages ove...
Katherine A. Heller, Zoubin Ghahramani
COLT
2001
Springer
15 years 9 months ago
Tracking a Small Set of Experts by Mixing Past Posteriors
In this paper, we examine on-line learning problems in which the target concept is allowed to change over time. In each trial a master algorithm receives predictions from a large ...
Olivier Bousquet, Manfred K. Warmuth
BMCBI
2007
140views more  BMCBI 2007»
15 years 4 months ago
Accurate prediction of protein secondary structure and solvent accessibility by consensus combiners of sequence and structure in
Background: Structural properties of proteins such as secondary structure and solvent accessibility contribute to three-dimensional structure prediction, not only in the ab initio...
Gianluca Pollastri, Alberto J. M. Martin, Catherin...