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JMLR
2012
11 years 9 months ago
Exploiting Unrelated Tasks in Multi-Task Learning
We study the problem of learning a group of principal tasks using a group of auxiliary tasks, unrelated to the principal ones. In many applications, joint learning of unrelated ta...
Bernardino Romera-Paredes, Andreas Argyriou, Nadia...
JMLR
2012
11 years 9 months ago
Contextual Bandit Learning with Predictable Rewards
Contextual bandit learning is a reinforcement learning problem where the learner repeatedly receives a set of features (context), takes an action and receives a reward based on th...
Alekh Agarwal, Miroslav Dudík, Satyen Kale,...
JMLR
2012
11 years 9 months ago
Multiple Texture Boltzmann Machines
We assess the generative power of the mPoTmodel of [10] with tiled-convolutional weight sharing as a model for visual textures by specifically training on this task, evaluating m...
Jyri J. Kivinen, Christopher K. I. Williams
JMLR
2012
11 years 9 months ago
A metric learning perspective of SVM: on the relation of LMNN and SVM
Support Vector Machines, SVMs, and the Large Margin Nearest Neighbor algorithm, LMNN, are two very popular learning algorithms with quite different learning biases. In this paper...
Huyen Do, Alexandros Kalousis, Jun Wang, Adam Wozn...
JMLR
2012
11 years 9 months ago
Structured Output Learning with High Order Loss Functions
Often when modeling structured domains, it is desirable to leverage information that is not naturally expressed as simply a label. Examples include knowledge about the evaluation ...
Daniel Tarlow, Richard S. Zemel
JMLR
2012
11 years 9 months ago
Detecting Network Cliques with Radon Basis Pursuit
In this paper, we propose a novel formulation of the network clique detection problem by introducing a general network data representation framework. We show connections between o...
Xiaoye Jiang, Yuan Yao, Han Liu, Leonidas J. Guiba...
JMLR
2012
11 years 9 months ago
Sparsistency of the Edge Lasso over Graphs
James Sharpnack, Aarti Singh, Alessandro Rinaldo
JMLR
2012
11 years 9 months ago
Randomized Optimum Models for Structured Prediction
One approach to modeling structured discrete data is to describe the probability of states via an energy function and Gibbs distribution. A recurring difficulty in these models is...
Daniel Tarlow, Ryan Prescott Adams, Richard S. Zem...
JMLR
2012
11 years 9 months ago
High-dimensional Sparse Inverse Covariance Estimation using Greedy Methods
Christopher C. Johnson, Ali Jalali, Pradeep D. Rav...
JMLR
2012
11 years 9 months ago
Hierarchical Latent Dictionaries for Models of Brain Activation
In this work, we propose a hierarchical latent dictionary approach to estimate the timevarying mean and covariance of a process for which we have only limited noisy samples. We fu...
Alona Fyshe, Emily B. Fox, David B. Dunson, Tom M....