ICML
2010
IEEE
14 years 1 months ago
2010
IEEE
We study metric learning as a problem of information retrieval. We present a general metric learning algorithm, based on the structural SVM framework, to learn a metric such that ...
ICML
2010
IEEE
14 years 1 months ago
2010
IEEE
We present and derive a new stick-breaking construction of the beta process. The construction is closely related to a special case of the stick-breaking construction of the Dirich...
ICML
2010
IEEE
14 years 1 months ago
2010
IEEE
The goal of transfer learning is to improve the learning of a new target concept given knowledge of related source concept(s). We introduce the first boosting-based algorithms for...
ICML
2010
IEEE
14 years 1 months ago
2010
IEEE
A learning problem might have several measures of complexity (e.g., norm and dimensionality) that affect the generalization error. What is the interaction between these complexiti...
ICML
2010
IEEE
14 years 1 months ago
2010
IEEE
This paper introduces a novel multiagent learning algorithm, Convergence with Model Learning and Safety (or CMLeS in short), which achieves convergence, targeted optimality agains...
ICML
2010
IEEE
14 years 1 months ago
2010
IEEE
The importance of bringing causality into play when designing feature selection methods is more and more acknowledged in the machine learning community. This paper proposes a filt...
ICML
2010
IEEE
14 years 1 months ago
2010
IEEE
ICML
2010
IEEE
14 years 1 months ago
2010
IEEE
This paper proposes a multiple instance learning (MIL) algorithm for Gaussian processes (GP). The GP-MIL model inherits two crucial benefits from GP: (i) a principle manner of lea...
ICML
2010
IEEE
14 years 1 months ago
2010
IEEE
Generative topic models such as LDA are limited by their inability to utilize nontrivial input features to enhance their performance, and many topic models assume that topic assig...
ICML
2010
IEEE
14 years 1 months ago
2010
IEEE
We consider the problem of multi-task reinforcement learning where the learner is provided with a set of tasks, for which only a small number of samples can be generated for any g...