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» Boosting Methods for Regression
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ICIP
2002
IEEE
16 years 4 months ago
Model-driven statistical analysis of human gait motion
We describe a new method for analyzing and extracting human gait motion by combining statistical methods with image processing. The periodic motion of human gait is modeled by tri...
Jang-Hee Yoo, Mark S. Nixon, Chris J. Harris
92
Voted
CHI
2003
ACM
16 years 2 months ago
Combined model for text entry rate development
We combine the power law of learning and theoretical upper limit predictions to describe the development of text entry rates from users' first contact to asymptotic expert us...
Poika Isokoski, I. Scott MacKenzie
137
Voted
SBRN
2008
IEEE
15 years 9 months ago
Imitation Learning of an Intelligent Navigation System for Mobile Robots Using Reservoir Computing
The design of an autonomous navigation system for mobile robots can be a tough task. Noisy sensors, unstructured environments and unpredictability are among the problems which mus...
Eric A. Antonelo, Benjamin Schrauwen, Dirk Strooba...
129
Voted
CBMS
2007
IEEE
15 years 8 months ago
Text Categorization for Multi-label Documents and Many Categories
In this paper, we propose a new classification method that addresses classification in multiple categories of textual documents. We call it Matrix Regression (MR) due to its resem...
Iulian Sandu Popa, Karine Zeitouni, Georges Gardar...
CAEPIA
2003
Springer
15 years 7 months ago
Time-Series Prediction: Application to the Short-Term Electric Energy Demand
This paper describes a time-series prediction method based on the kNN technique. The proposed methodology is applied to the 24hour load forecasting problem. Also, based on recorded...
Alicia Troncoso Lora, Jesús Riquelme Santos...