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NIPS
1997
14 years 5 days 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
14 years 5 days 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
14 years 5 days 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
14 years 5 days ago
Multiple Threshold Neural Logic
Vasken Bohossian, Jehoshua Bruck
NIPS
1997
14 years 5 days ago
Refractoriness and Neural Precision
Michael J. Berry II, Markus Meister
NIPS
1997
14 years 5 days 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
14 years 5 days 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
14 years 5 days 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
NIPS
2000
14 years 5 days ago
Regularized Winnow Methods
In theory, the Winnow multiplicative update has certain advantages over the Perceptron additive update when there are many irrelevant attributes. Recently, there has been much eff...
Tong Zhang
NIPS
2000
14 years 5 days ago
Generalized Belief Propagation
In an important recent paper, Yedidia, Freeman, and Weiss [11] showed that there is a close connection between the belief propagation algorithm for probabilistic inference and the...
Jonathan S. Yedidia, William T. Freeman, Yair Weis...