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NIPS
2008
13 years 6 months ago
Efficient Inference in Phylogenetic InDel Trees
Accurate and efficient inference in evolutionary trees is a central problem in computational biology. While classical treatments have made unrealistic site independence assumption...
Alexandre Bouchard-Côté, Michael I. J...
NIPS
2008
13 years 6 months ago
Modeling the effects of memory on human online sentence processing with particle filters
Language comprehension in humans is significantly constrained by memory, yet rapid, highly incremental, and capable of utilizing a wide range of contextual information to resolve ...
Roger P. Levy, Florencia Reali, Thomas L. Griffith...
NIPS
2008
13 years 6 months ago
DiscLDA: Discriminative Learning for Dimensionality Reduction and Classification
Probabilistic topic models have become popular as methods for dimensionality reduction in collections of text documents or images. These models are usually treated as generative m...
Simon Lacoste-Julien, Fei Sha, Michael I. Jordan
NIPS
2008
13 years 6 months ago
Non-stationary dynamic Bayesian networks
Abstract: Structure learning of dynamic Bayesian networks provide a principled mechanism for identifying conditional dependencies in time-series data. This learning procedure assum...
Joshua W. Robinson, Alexander J. Hartemink
NIPS
2008
13 years 6 months ago
Skill Characterization Based on Betweenness
We present a characterization of a useful class of skills based on a graphical representation of an agent's interaction with its environment. Our characterization uses betwee...
Özgür Simsek, Andrew G. Barto
NIPS
2008
13 years 6 months ago
Shared Segmentation of Natural Scenes Using Dependent Pitman-Yor Processes
We develop a statistical framework for the simultaneous, unsupervised segmentation and discovery of visual object categories from image databases. Examining a large set of manuall...
Erik B. Sudderth, Michael I. Jordan
NIPS
2008
13 years 6 months ago
Support Vector Machines with a Reject Option
We consider the problem of binary classification where the classifier may abstain instead of classifying each observation. The Bayes decision rule for this setup, known as Chow�...
Yves Grandvalet, Alain Rakotomamonjy, Joseph Keshe...
NIPS
2008
13 years 6 months ago
Resolution Limits of Sparse Coding in High Dimensions
This paper addresses the problem of sparsity pattern detection for unknown ksparse n-dimensional signals observed through m noisy, random linear measurements. Sparsity pattern rec...
Alyson K. Fletcher, Sundeep Rangan, Vivek K. Goyal
NIPS
2008
13 years 6 months ago
Online Metric Learning and Fast Similarity Search
Metric learning algorithms can provide useful distance functions for a variety of domains, and recent work has shown good accuracy for problems where the learner can access all di...
Prateek Jain, Brian Kulis, Inderjit S. Dhillon, Kr...
NIPS
2008
13 years 6 months ago
Multi-task Gaussian Process Learning of Robot Inverse Dynamics
The inverse dynamics problem for a robotic manipulator is to compute the torques needed at the joints to drive it along a given trajectory; it is beneficial to be able to learn th...
Kian Ming Adam Chai, Christopher K. I. Williams, S...