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» Hedging predictions in machine learning
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ICML
2010
IEEE
15 years 7 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
15 years 1 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 7 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 10 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 6 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...