NIPS
2003
13 years 6 months ago
2003
The standard 2-norm SVM is known for its good performance in twoclass classi£cation. In this paper, we consider the 1-norm SVM. We argue that the 1-norm SVM may have some advanta...
NIPS
2003
13 years 6 months ago
2003
The Google search engine has enjoyed huge success with its web page ranking algorithm, which exploits global, rather than local, hyperlink structure of the web using random walks....
NIPS
2003
13 years 6 months ago
2003
We consider the general problem of learning from labeled and unlabeled data, which is often called semi-supervised learning or transductive inference. A principled approach to sem...
NIPS
2003
13 years 6 months ago
2003
We present a novel strategy for automatically debugging programs given sampled data from thousands of actual user runs. Our goal is to pinpoint those features that are most correl...
NIPS
2003
13 years 6 months ago
2003
In this paper we obtain convergence bounds for the concentration of Bayesian posterior distributions (around the true distribution) using a novel method that simplifies and enhan...
NIPS
2003
13 years 6 months ago
2003
This paper compares the ability of human observers to detect target image curves with that of an ideal observer. The target curves are sampled from a generative model which speci...
NIPS
2003
13 years 6 months ago
2003
A mixed-signal image filtering VLSI has been developed aiming at real-time generation of edge-based image vectors for robust image recognition. A four-stage asynchronous median de...
NIPS
2003
13 years 6 months ago
2003
Face detection is a canonical example of a rare event detection problem, in which target patterns occur with much lower frequency than nontargets. Out of millions of face-sized wi...
NIPS
2003
13 years 6 months ago
2003
Recently, relevance vector machines (RVM) have been fashioned from a sparse Bayesian learning (SBL) framework to perform supervised learning using a weight prior that encourages s...
NIPS
2003
13 years 6 months ago
2003
Gradient-following learning methods can encounter problems of implementation in many applications, and stochastic variants are frequently used to overcome these difficulties. We ...