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IJCAI
2001
13 years 11 months ago
Knowledge Extraction from Local Function Networks
Extracting rules from RBFs is not a trivial task because of nonlinear functions or high input dimensionality. In such cases, some of the hidden units of the RBF network have a ten...
Kenneth McGarry, Stefan Wermter, John MacIntyre
NIPS
2004
13 years 11 months ago
Parametric Embedding for Class Visualization
In this paper, we propose a new method, Parametric Embedding (PE), for visualizing the posteriors estimated over a mixture model. PE simultaneously embeds both objects and their c...
Tomoharu Iwata, Kazumi Saito, Naonori Ueda, Sean S...
NIPS
2004
13 years 11 months ago
A Three Tiered Approach for Articulated Object Action Modeling and Recognition
Visual action recognition is an important problem in computer vision. In this paper, we propose a new method to probabilistically model and recognize actions of articulated object...
Le Lu, Gregory D. Hager, Laurent Younes
NIPS
2001
13 years 11 months ago
Probabilistic Inference of Hand Motion from Neural Activity in Motor Cortex
Statistical learning and probabilistic inference techniques are used to infer the hand position of a subject from multi-electrode recordings of neural activity in motor cortex. Fi...
Yun Gao, Michael J. Black, Elie Bienenstock, Shy S...
NIPS
2001
13 years 11 months ago
Bayesian time series classification
This paper proposes an approach to classification of adjacent segments of a time series as being either of classes. We use a hierarchical model that consists of a feature extract...
Peter Sykacek, Stephen J. Roberts