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NIPS
2008
13 years 5 months ago
Sparse probabilistic projections
We present a generative model for performing sparse probabilistic projections, which includes sparse principal component analysis and sparse canonical correlation analysis as spec...
Cédric Archambeau, Francis Bach
NIPS
2008
13 years 5 months ago
On Computational Power and the Order-Chaos Phase Transition in Reservoir Computing
Randomly connected recurrent neural circuits have proven to be very powerful models for online computations when a trained memoryless readout function is appended. Such Reservoir ...
Benjamin Schrauwen, Lars Buesing, Robert A. Legens...
NIPS
2008
13 years 5 months ago
Exact Convex Confidence-Weighted Learning
Confidence-weighted (CW) learning [6], an online learning method for linear classifiers, maintains a Gaussian distributions over weight vectors, with a covariance matrix that repr...
Koby Crammer, Mark Dredze, Fernando Pereira
NIPS
2008
13 years 5 months ago
Characterizing neural dependencies with copula models
The coding of information by neural populations depends critically on the statistical dependencies between neuronal responses. However, there is no simple model that can simultane...
Pietro Berkes, Frank Wood, Jonathan Pillow
NIPS
2008
13 years 5 months ago
Dynamic visual attention: searching for coding length increments
A visual attention system should respond placidly when common stimuli are presented, while at the same time keep alert to anomalous visual inputs. In this paper, a dynamic visual ...
Xiaodi Hou, Liqing Zhang
NIPS
2008
13 years 5 months ago
Learning Bounded Treewidth Bayesian Networks
With the increased availability of data for complex domains, it is desirable to learn Bayesian network structures that are sufficiently expressive for generalization while at the ...
Gal Elidan, Stephen Gould
NIPS
2008
13 years 5 months ago
Generative versus discriminative training of RBMs for classification of fMRI images
Neuroimaging datasets often have a very large number of voxels and a very small number of training cases, which means that overfitting of models for this data can become a very se...
Tanya Schmah, Geoffrey E. Hinton, Richard S. Zemel...
NIPS
2008
13 years 5 months ago
Bayesian Model of Behaviour in Economic Games
Classical game theoretic approaches that make strong rationality assumptions have difficulty modeling human behaviour in economic games. We investigate the role of finite levels o...
Debajyoti Ray, Brooks King-Casas, P. Read Montague...
NIPS
2008
13 years 5 months ago
On the Reliability of Clustering Stability in the Large Sample Regime
Clustering stability is an increasingly popular family of methods for performing model selection in data clustering. The basic idea is that the chosen model should be stable under...
Ohad Shamir, Naftali Tishby