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ICML
2005
IEEE
15 years 15 days ago
Learning Gaussian processes from multiple tasks
We consider the problem of multi-task learning, that is, learning multiple related functions. Our approach is based on a hierarchical Bayesian framework, that exploits the equival...
Kai Yu, Volker Tresp, Anton Schwaighofer
ICML
2005
IEEE
15 years 15 days ago
Dirichlet enhanced relational learning
We apply nonparametric hierarchical Bayesian modelling to relational learning. In a hierarchical Bayesian approach, model parameters can be "personalized", i.e., owned b...
Zhao Xu, Volker Tresp, Kai Yu, Shipeng Yu, Hans-Pe...
ICML
2005
IEEE
15 years 15 days ago
Building Sparse Large Margin Classifiers
This paper presents an approach to build Sparse Large Margin Classifiers (SLMC) by adding one more constraint to the standard Support Vector Machine (SVM) training problem. The ad...
Bernhard Schölkopf, Gökhan H. Bakir, Min...
ICML
2005
IEEE
15 years 15 days ago
Linear Asymmetric Classifier for cascade detectors
The detection of faces in images is fundamentally a rare event detection problem. Cascade classifiers provide an efficient computational solution, by leveraging the asymmetry in t...
Jianxin Wu, Matthew D. Mullin, James M. Rehg
ICML
2005
IEEE
15 years 15 days ago
Incomplete-data classification using logistic regression
A logistic regression classification algorithm is developed for problems in which the feature vectors may be missing data (features). Single or multiple imputation for the missing...
David Williams, Xuejun Liao, Ya Xue, Lawrence Cari...
ICML
2005
IEEE
15 years 15 days ago
Learning predictive representations from a history
Predictive State Representations (PSRs) have shown a great deal of promise as an alternative to Markov models. However, learning a PSR from a single stream of data generated from ...
Eric Wiewiora
ICML
2005
IEEE
15 years 15 days ago
Exploiting syntactic, semantic and lexical regularities in language modeling via directed Markov random fields
We present a directed Markov random field (MRF) model that combines n-gram models, probabilistic context free grammars (PCFGs) and probabilistic latent semantic analysis (PLSA) fo...
Shaojun Wang, Shaomin Wang, Russell Greiner, Dale ...
ICML
2005
IEEE
15 years 15 days ago
New kernels for protein structural motif discovery and function classification
We present new, general-purpose kernels for protein structure analysis, and describe how to apply them to structural motif discovery and function classification. Experiments show ...
Chang Wang, Stephen D. Scott
ICML
2005
IEEE
15 years 15 days ago
Bayesian sparse sampling for on-line reward optimization
We present an efficient "sparse sampling" technique for approximating Bayes optimal decision making in reinforcement learning, addressing the well known exploration vers...
Tao Wang, Daniel J. Lizotte, Michael H. Bowling, D...
ICML
2005
IEEE
15 years 15 days ago
Implicit surface modelling as an eigenvalue problem
We discuss the problem of fitting an implicit shape model to a set of points sampled from a co-dimension one manifold of arbitrary topology. The method solves a non-convex optimis...
Christian Walder, Olivier Chapelle, Bernhard Sch&o...