NIPS
2004
14 years 29 days ago
2004
The Bradley-Terry model for paired comparison has been popular in many areas. We propose a generalized version in which paired individual comparisons are extended to paired team c...
NIPS
2004
14 years 29 days ago
2004
In this paper we present a framework for using multi-layer perceptron (MLP) networks in nonlinear generative models trained by variational Bayesian learning. The nonlinearity is h...
NIPS
2004
14 years 29 days ago
2004
Schema learning is a way to discover probabilistic, constructivist, predictive action models (schemas) from experience. It includes methods for finding and using hidden state to m...
NIPS
2004
14 years 29 days ago
2004
Motivated by the particular problems involved in communicating with "locked-in" paralysed patients, we aim to develop a braincomputer interface that uses auditory stimul...
NIPS
2004
14 years 29 days ago
2004
The support vector machine (SVM) is a widely used tool for classification. Many efficient implementations exist for fitting a two-class SVM model. The user has to supply values fo...
NIPS
2004
14 years 29 days ago
2004
The NIPS 2003 workshops included a feature selection competition organized by the authors. We provided participants with five datasets from different application domains and calle...
NIPS
2004
14 years 29 days ago
2004
Statistical approaches to language learning typically focus on either short-range syntactic dependencies or long-range semantic dependencies between words. We present a generative...
NIPS
2004
14 years 29 days ago
2004
We consider the semi-supervised learning problem, where a decision rule is to be learned from labeled and unlabeled data. In this framework, we motivate minimum entropy regulariza...
NIPS
2004
14 years 29 days ago
2004
We describe an algorithm for support vector machines (SVM) that can be parallelized efficiently and scales to very large problems with hundreds of thousands of training vectors. I...
NIPS
2004
14 years 29 days ago
2004
In this paper we propose a novel method for learning a Mahalanobis distance measure to be used in the KNN classification algorithm. The algorithm directly maximizes a stochastic v...