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NIPS
2004
9 years 12 months ago
Learning Gaussian Process Kernels via Hierarchical Bayes
We present a novel method for learning with Gaussian process regression in a hierarchical Bayesian framework. In a first step, kernel matrices on a fixed set of input points are l...
Anton Schwaighofer, Volker Tresp, Kai Yu
NIPS
2004
9 years 12 months ago
Edge of Chaos Computation in Mixed-Mode VLSI - A Hard Liquid
Computation without stable states is a computing paradigm different from Turing's and has been demonstrated for various types of simulated neural networks. This publication t...
Felix Schürmann, Karlheinz Meier, Johannes Sc...
NIPS
2004
9 years 12 months ago
Kernel Methods for Implicit Surface Modeling
We describe methods for computing an implicit model of a hypersurface that is given only by a finite sampling. The methods work by mapping the sample points into a reproducing ker...
Bernhard Schölkopf, Joachim Giesen, Simon Spa...
NIPS
2004
9 years 12 months ago
Outlier Detection with One-class Kernel Fisher Discriminants
The problem of detecting "atypical objects" or "outliers" is one of the classical topics in (robust) statistics. Recently, it has been proposed to address this...
Volker Roth
NIPS
2004
9 years 12 months ago
A Method for Inferring Label Sampling Mechanisms in Semi-Supervised Learning
We consider the situation in semi-supervised learning, where the "label sampling" mechanism stochastically depends on the true response (as well as potentially on the fe...
Saharon Rosset, Ji Zhu, Hui Zou, Trevor Hastie
NIPS
2004
9 years 12 months ago
Semi-Markov Conditional Random Fields for Information Extraction
We describe semi-Markov conditional random fields (semi-CRFs), a conditionally trained version of semi-Markov chains. Intuitively, a semiCRF on an input sequence x outputs a "...
Sunita Sarawagi, William W. Cohen
NIPS
2004
9 years 12 months ago
Following Curved Regularized Optimization Solution Paths
Regularization plays a central role in the analysis of modern data, where non-regularized fitting is likely to lead to over-fitted models, useless for both prediction and interpre...
Saharon Rosset
NIPS
2004
9 years 12 months ago
Learning, Regularization and Ill-Posed Inverse Problems
Many works have shown that strong connections relate learning from examples to regularization techniques for ill-posed inverse problems. Nevertheless by now there was no formal ev...
Lorenzo Rosasco, Andrea Caponnetto, Ernesto De Vit...
NIPS
2004
9 years 12 months ago
Semi-parametric Exponential Family PCA
We present a semi-parametric latent variable model based technique for density modelling, dimensionality reduction and visualization. Unlike previous methods, we estimate the late...
Sajama, Alon Orlitsky
NIPS
2004
9 years 12 months ago
Coarticulation in Markov Decision Processes
We investigate an approach for simultaneously committing to multiple activities, each modeled as a temporally extended action in a semi-Markov decision process (SMDP). For each ac...
Khashayar Rohanimanesh, Robert Platt Jr., Sridhar ...
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