NIPS
2001
13 years 11 months ago
2001
The rule-based bootstrapping introduced by Yarowsky, and its cotraining variant by Blum and Mitchell, have met with considerable empirical success. Earlier work on the theory of c...
NIPS
2001
13 years 11 months ago
2001
The adaptive TAP Gibbs free energy for a general densely connected probabilistic model with quadratic interactions and arbritary single site constraints is derived. We show how a ...
NIPS
2001
13 years 11 months ago
2001
The Temporal Coding Hypothesis of Miller and colleagues [7] suggests that animals integrate related temporal patterns of stimuli into single memory representations. We formalize t...
NIPS
2001
13 years 11 months ago
2001
We describe the g-factor which relates probability distributions on image features to distributions on the images themselves. The g-factor depends only on our choice of features a...
NIPS
2001
13 years 11 months ago
2001
The deep layers of the superior colliculus (DSC) integrate multisensory input and initiate an orienting response toward the source of stimulation. Multisensory response enhancemen...
NIPS
2001
13 years 11 months ago
2001
Support Vector Machines (SVMs) are currently the state-of-the-art models for many classication problems but they suer from the complexity of their training algorithm which is at l...
NIPS
2001
13 years 11 months ago
2001
We describe the application of kernel methods to Natural Language Processing (NLP) problems. In many NLP tasks the objects being modeled are strings, trees, graphs or other discre...
NIPS
2001
13 years 11 months ago
2001
Estimating insurance premia from data is a difficult regression problem for several reasons: the large number of variables, many of which are discrete, and the very peculiar shape...
NIPS
2001
13 years 11 months ago
2001
We propose a new classification for multi-agent learning algorithms, with each league of players characterized by both their possible strategies and possible beliefs. Using this c...
NIPS
2001
13 years 11 months ago
2001
In this paper, it is shown how to extract a hypothesis with small risk from the ensemble of hypotheses generated by an arbitrary on-line learning algorithm run on an independent an...