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ICML
2007
IEEE
10 years 6 months ago
Hierarchical maximum entropy density estimation
We study the problem of simultaneously estimating several densities where the datasets are organized into overlapping groups, such as a hierarchy. For this problem, we propose a m...
David M. Blei, Miroslav Dudík, Robert E. Sc...
ICML
2007
IEEE
10 years 6 months ago
Asymptotic Bayesian generalization error when training and test distributions are different
In supervised learning, we commonly assume that training and test data are sampled from the same distribution. However, this assumption can be violated in practice and then standa...
Keisuke Yamazaki, Klaus-Robert Müller, Masash...
ICML
2007
IEEE
10 years 6 months ago
A permutation-augmented sampler for DP mixture models
We introduce a new inference algorithm for Dirichlet process mixture models. While Gibbs sampling and variational methods focus on local moves, the new algorithm makes more global...
Percy Liang, Michael I. Jordan, Benjamin Taskar
ICML
2007
IEEE
10 years 6 months ago
Magnitude-preserving ranking algorithms
Corinna Cortes, Mehryar Mohri, Ashish Rastogi
ICML
2007
IEEE
10 years 6 months ago
Statistical predicate invention
We propose statistical predicate invention as a key problem for statistical relational learning. SPI is the problem of discovering new concepts, properties and relations in struct...
Stanley Kok, Pedro Domingos
ICML
2007
IEEE
10 years 6 months ago
Efficiently computing minimax expected-size confidence regions
Given observed data and a collection of parameterized candidate models, a 1- confidence region in parameter space provides useful insight as to those models which are a good fit t...
Brent Bryan, H. Brendan McMahan, Chad M. Schafer, ...
ICML
2007
IEEE
10 years 6 months ago
A dependence maximization view of clustering
We propose a family of clustering algorithms based on the maximization of dependence between the input variables and their cluster labels, as expressed by the Hilbert-Schmidt Inde...
Le Song, Alexander J. Smola, Arthur Gretton, Karst...
ICML
2007
IEEE
10 years 6 months ago
An empirical evaluation of deep architectures on problems with many factors of variation
Recently, several learning algorithms relying on models with deep architectures have been proposed. Though they have demonstrated impressive performance, to date, they have only b...
Hugo Larochelle, Dumitru Erhan, Aaron C. Courville...
ICML
2007
IEEE
10 years 6 months ago
Trust region Newton methods for large-scale logistic regression
Large-scale logistic regression arises in many applications such as document classification and natural language processing. In this paper, we apply a trust region Newton method t...
Chih-Jen Lin, Ruby C. Weng, S. Sathiya Keerthi
ICML
2007
IEEE
10 years 6 months ago
Pegasos: Primal Estimated sub-GrAdient SOlver for SVM
We describe and analyze a simple and effective iterative algorithm for solving the optimization problem cast by Support Vector Machines (SVM). Our method alternates between stocha...
Shai Shalev-Shwartz, Yoram Singer, Nathan Srebro
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