Sciweavers

JMLR
2012
11 years 9 months ago
Constrained 1-Spectral Clustering
An important form of prior information in clustering comes in form of cannot-link and must-link constraints. We present a generalization of the popular spectral clustering techniq...
Syama Sundar Rangapuram, Matthias Hein
JMLR
2012
11 years 9 months ago
Deterministic Annealing for Semi-Supervised Structured Output Learning
In this paper we propose a new approach for semi-supervised structured output learning. Our approach uses relaxed labeling on unlabeled data to deal with the combinatorial nature ...
Paramveer S. Dhillon, S. Sathiya Keerthi, Kedar Be...
JMLR
2012
11 years 9 months ago
On Nonparametric Guidance for Learning Autoencoder Representations
Unsupervised discovery of latent representations, in addition to being useful for density modeling, visualisation and exploratory data analysis, is also increasingly important for...
Jasper Snoek, Ryan Prescott Adams, Hugo Larochelle
JMLR
2012
11 years 9 months ago
Multi-label Subspace Ensemble
A challenging problem of multi-label learning is that both the label space and the model complexity will grow rapidly with the increase in the number of labels, and thus makes the...
Tianyi Zhou, Dacheng Tao
JMLR
2012
11 years 9 months ago
A Bayesian Analysis of the Radioactive Releases of Fukushima
The Fukushima Daiichi disaster 11 March, 2011 is considered the largest nuclear accident since the 1986 Chernobyl disaster and has been rated at level 7 on the International Nucle...
Ryota Tomioka, Morten Mørup
JMLR
2012
11 years 9 months ago
Deep Boltzmann Machines as Feed-Forward Hierarchies
The deep Boltzmann machine is a powerful model that extracts the hierarchical structure of observed data. While inference is typically slow due to its undirected nature, we argue ...
Grégoire Montavon, Mikio L. Braun, Klaus-Ro...
JMLR
2012
11 years 9 months ago
MULTIBOOST: A Multi-purpose Boosting Package
Djalel Benbouzid, Róbert Busa-Fekete, Norma...
JMLR
2012
11 years 9 months ago
Multiresolution Deep Belief Networks
Motivated by the observation that coarse and fine resolutions of an image reveal different structures in the underlying visual phenomenon, we present a model based on the Deep B...
Yichuan Tang, Abdel-rahman Mohamed
JMLR
2012
11 years 9 months ago
Minimax Rates of Estimation for Sparse PCA in High Dimensions
We study sparse principal components analysis in the high-dimensional setting, where p (the number of variables) can be much larger than n (the number of observations). We prove o...
Vincent Q. Vu, Jing Lei
JMLR
2012
11 years 9 months ago
Domain Adaptation: A Small Sample Statistical Approach
We study the prevalent problem when a test distribution differs from the training distribution. We consider a setting where our training set consists of a small number of sample d...
Ruslan Salakhutdinov, Sham M. Kakade, Dean P. Fost...