NIPS
2000
13 years 5 months ago
2000
We develop an approach for a sparse representation for Gaussian Process (GP) models in order to overcome the limitations of GPs caused by large data sets. The method is based on a...
NIPS
2000
13 years 5 months ago
2000
Output coding is a general method for solving multiclass problems by reducing them to multiple binary classification problems. Previous research on output coding has employed, alm...
NIPS
2000
13 years 5 months ago
2000
Preliminary work by the authors made use of the so-called "Manhattan world" assumption about the scene statistics of city and indoor scenes. This assumption stated that ...
NIPS
2000
13 years 5 months ago
2000
We describe a joint probabilistic model for modeling the contents and inter-connectivity of document collections such as sets of web pages or research paper archives. The model is...
NIPS
2000
13 years 5 months ago
2000
We propose a non-linear feature space transformation for speaker/environment adaptation which forces the individual dimensions of the acoustic data for every speaker to be Gaussia...
NIPS
2000
13 years 5 months ago
2000
The paradigm of Hebbian learning has recently received a novel interpretation with the discovery of synaptic plasticity that depends on the relative timing of pre and post synapti...
NIPS
2000
13 years 5 months ago
2000
The Vicinal Risk Minimization principle establishes a bridge between generative models and methods derived from the Structural Risk Minimization Principle such as Support Vector M...
NIPS
2000
13 years 5 months ago
2000
An on-line recursive algorithm for training support vector machines, one vector at a time, is presented. Adiabatic increments retain the KuhnTucker conditions on all previously se...
NIPS
2000
13 years 5 months ago
2000
A goal of statistical language modeling is to learn the joint probability function of sequences of words in a language. This is intrinsically difficult because of the curse of dim...
NIPS
2000
13 years 5 months ago
2000
We present a novel method for clustering using the support vector machine approach. Data points are mapped to a high dimensional feature space, where support vectors are used to d...