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» Unsupervised feature selection using a neuro-fuzzy approach
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FUZZIEEE
2007
IEEE
15 years 6 months ago
A Feature Selection Method Based on Choquet Integral and Typicality Analysis
— An iterative feature selection method based on feature typicality and interactivity analysis is presented in this paper. The aim is to enhance model interpretability by selecti...
Cyril Mazaud, Jan Rendek, Vincent Bombardier, Laur...
ICRA
2008
IEEE
208views Robotics» more  ICRA 2008»
15 years 6 months ago
Unsupervised body scheme learning through self-perception
— In this paper, we present an approach allowing a robot to learn a generative model of its own physical body from scratch using self-perception with a single monocular camera. O...
Jürgen Sturm, Christian Plagemann, Wolfram Bu...
NIPS
2003
15 years 1 months ago
Feature Selection in Clustering Problems
A novel approach to combining clustering and feature selection is presented. It implements a wrapper strategy for feature selection, in the sense that the features are directly se...
Volker Roth, Tilman Lange
CLEAR
2007
Springer
179views Biometrics» more  CLEAR 2007»
15 years 6 months ago
HMM-Based Acoustic Event Detection with AdaBoost Feature Selection
Given the spectral difference between speech and acoustic events, we propose using Kullback-Leibler distance to quantify the discriminant capability of all speech feature componen...
Xi Zhou, Xiaodan Zhuang, Ming Liu, Hao Tang, Mark ...
EMNLP
2007
15 years 1 months ago
LEDIR: An Unsupervised Algorithm for Learning Directionality of Inference Rules
Semantic inference is a core component of many natural language applications. In response, several researchers have developed algorithms for automatically learning inference rules...
Rahul Bhagat, Patrick Pantel, Eduard H. Hovy