JMLR
2012
11 years 7 months ago
2012
Metric and kernel learning arise in several machine learning applications. However, most existing metric learning algorithms are limited to learning metrics over low-dimensional d...
JMLR
2012
11 years 7 months ago
2012
Sparse additive models are families of d-variate functions with the additive decomposition f∗ = ∑j∈S f∗ j , where S is an unknown subset of cardinality s d. In this paper,...
JMLR
2012
11 years 7 months ago
2012
JMLR
2012
11 years 7 months ago
2012
Many real-world problems are inherently hierarchically structured. The use of this structure in an agent’s policy may well be the key to improved scalability and higher performa...
JMLR
2012
11 years 7 months ago
2012
In recent years there has been a lot of interest in designing principled classification algorithms over multiple cues, based on the intuitive notion that using more features shou...
JMLR
2012
11 years 7 months ago
2012
We address the problem of finding the most likely assignment or MAP estimation in a Markov random field. We analyze the linear programming formulation of MAP through the lens of...
JMLR
2012
11 years 7 months ago
2012
This paper presents new and effective algorithms for learning kernels. In particular, as shown by our empirical results, these algorithms consistently outperform the so-called uni...
JMLR
2012
11 years 7 months ago
2012
We show that the stick-breaking construction of the beta process due to Paisley et al. (2010) can be obtained from the characterization of the beta process as a Poisson process. S...
JMLR
2012
11 years 7 months ago
2012
In this paper, we propose to apply sparse canonical correlation analysis (sparse CCA) to an important genome-wide association study problem, eQTL mapping. Existing sparse CCA mode...
JMLR
2012
11 years 7 months ago
2012
The main theme of this paper is to develop a novel eigenvalue optimization framework for learning a Mahalanobis metric. Within this context, we introduce a novel metric learning a...