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NIPS
1997
13 years 6 months ago
Learning to Order Things
There are many applications in which it is desirable to order rather than classify instances. Here we consider the problem of learning how to order, given feedback in the form of ...
William W. Cohen, Robert E. Schapire, Yoram Singer
NIPS
1997
13 years 6 months ago
Incorporating Test Inputs into Learning
In many applications, such as credit default prediction and medical image recognition, test inputs are available in addition to the labeled training examples. We propose a method ...
Zehra Cataltepe, Malik Magdon-Ismail
NIPS
1997
13 years 6 months ago
A Non-Parametric Multi-Scale Statistical Model for Natural Images
The observed distribution of natural images is far from uniform. On the contrary, real images have complex and important structure that can be exploited for image processing, reco...
Jeremy S. De Bonet, Paul A. Viola
NIPS
1997
13 years 6 months ago
Structure Driven Image Database Retrieval
A new algorithm is presented which approximates the perceived visual similarity between images. The images are initially transformed into a feature space which captures visual str...
Jeremy S. De Bonet, Paul A. Viola
NIPS
1997
13 years 6 months ago
Multiple Threshold Neural Logic
Vasken Bohossian, Jehoshua Bruck
NIPS
1997
13 years 6 months ago
Refractoriness and Neural Precision
Michael J. Berry II, Markus Meister
NIPS
1997
13 years 6 months ago
Using Expectation to Guide Processing: A Study of Three Real-World Applications
In many real world tasks, only a small fraction of the available inputs are important at any particular time. This paper presents a method for ascertaining the relevance of inputs...
Shumeet Baluja
NIPS
1997
13 years 6 months ago
Generalized Prioritized Sweeping
Prioritized sweeping is a model-based reinforcement learning method that attempts to focus an agent’s limited computational resources to achieve a good estimate of the value of ...
David Andre, Nir Friedman, Ronald Parr
NIPS
1997
13 years 6 months ago
Nonparametric Model-Based Reinforcement Learning
This paper describes some of the interactions of model learning algorithms and planning algorithms we have found in exploring model-based reinforcement learning. The paper focuses...
Christopher G. Atkeson