ICML
2005
IEEE
14 years 5 months ago
2005
IEEE
This paper presents an algorithm to estimate simultaneously both mean and variance of a non parametric regression problem. The key point is that we are able to estimate variance l...
ICML
2005
IEEE
14 years 5 months ago
2005
IEEE
We extend the PAC-Bayes theorem to the sample-compression setting where each classifier is represented by two independent sources of information: a compression set which consists ...
ICML
2005
IEEE
14 years 5 months ago
2005
IEEE
We prove a quantitative connection between the expected sum of rewards of a policy and binary classification performance on created subproblems. This connection holds without any ...
ICML
2005
IEEE
14 years 5 months ago
2005
IEEE
We consider online learning where the target concept can change over time. Previous work on expert prediction algorithms has bounded the worst-case performance on any subsequence ...
ICML
2005
IEEE
14 years 5 months ago
2005
IEEE
The aim of this paper is to show that machine learning techniques can be used to derive a classifying function for human brain signal data measured by magnetoencephalography (MEG)...
ICML
2005
IEEE
14 years 5 months ago
2005
IEEE
Markov logic networks (MLNs) combine logic and probability by attaching weights to first-order clauses, and viewing these as templates for features of Markov networks. In this pap...
ICML
2005
IEEE
14 years 5 months ago
2005
IEEE
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...
ICML
2005
IEEE
14 years 5 months ago
2005
IEEE
Semi-supervised clustering algorithms aim to improve clustering results using limited supervision. The supervision is generally given as pairwise constraints; such constraints are...
ICML
2005
IEEE
14 years 5 months ago
2005
IEEE
In this paper we generalize the LARS feature selection method to the linear SVM model, derive an efficient algorithm for it, and empirically demonstrate its usefulness as a featur...
ICML
2005
IEEE
14 years 5 months ago
2005
IEEE
We investigate the empirical applicability of several bounds (a number of which are new) on the true error rate of learned classifiers which hold whenever the examples are chosen ...