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» A Boosting Algorithm for Regression
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TIP
2010
182views more  TIP 2010»
14 years 10 months ago
Flexible Manifold Embedding: A Framework for Semi-Supervised and Unsupervised Dimension Reduction
We propose a unified manifold learning framework for semi-supervised and unsupervised dimension reduction by employing a simple but effective linear regression function to map the ...
Feiping Nie, Dong Xu, Ivor Wai-Hung Tsang, Changsh...
VR
2003
IEEE
267views Virtual Reality» more  VR 2003»
15 years 8 months ago
An Experiment Comparing Double Exponential Smoothing and Kalman Filter-Based Predictive Tracking Algorithms
We present an experiment comparing double exponential smoothing and Kalman filter-based predictive tracking algorithms with derivative free measurement models. Our results show t...
Joseph J. LaViola Jr.
ICML
2000
IEEE
16 years 4 months ago
On-line Learning for Humanoid Robot Systems
Humanoid robots are high-dimensional movement systems for which analytical system identification and control methods are insufficient due to unknown nonlinearities in the system s...
Gaurav Tevatia, Jörg Conradt, Sethu Vijayakum...
124
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DATAMINE
2006
157views more  DATAMINE 2006»
15 years 3 months ago
Data Clustering with Partial Supervision
Clustering with partial supervision finds its application in situations where data is neither entirely nor accurately labeled. This paper discusses a semisupervised clustering algo...
Abdelhamid Bouchachia, Witold Pedrycz
133
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ICIP
2001
IEEE
16 years 4 months ago
Coding theoretic approach to image segmentation
This paper introduces multi-scale tree-based approaches to image segmentation, using Rissanen's coding theoretic minimum description length (MDL) principle to penalize overly...
Mário A. T. Figueiredo, Robert D. Nowak, Un...