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» A Framework for Multiple-Instance Learning
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126
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MCS
2010
Springer
15 years 7 months ago
Online Non-stationary Boosting
Abstract. Oza’s Online Boosting algorithm provides a version of AdaBoost which can be trained in an online way for stationary problems. One perspective is that this enables the p...
Adam Pocock, Paraskevas Yiapanis, Jeremy Singer, M...
120
Voted
ITNG
2010
IEEE
15 years 7 months ago
A Fast and Stable Incremental Clustering Algorithm
— Clustering is a pivotal building block in many data mining applications and in machine learning in general. Most clustering algorithms in the literature pertain to off-line (or...
Steven Young, Itamar Arel, Thomas P. Karnowski, De...
CSMR
2002
IEEE
15 years 7 months ago
Evolution of a Software Component - Experiences with a Network Editor Component
Even though the benefits of component-based software development are widely accepted, they are easily overestimated. To provide a firmer basis for the general discussion we descri...
Jyrki Akkanen, Attila Kiss, Jukka K. Nurminen
118
Voted
ICRA
2002
IEEE
128views Robotics» more  ICRA 2002»
15 years 7 months ago
Generation of a Task Model by Integrating Multiple Observations of Human Demonstrations
This paper describes a new approach on how to teach a robot everyday manipulation tasks under the “Learning from Observation” framework. Most of the approaches so far assume t...
Koichi Ogawara, Jun Takamatsu, Hiroshi Kimura, Kat...
WETICE
2002
IEEE
15 years 7 months ago
A Flexible Architecture for Collaborative Browsing
Collaborative Browsing is a new and promising research area whose purpose is to provide new collaboration schemes among users browsing the Web. To become an efficient collaboratio...
Guillermo de Jesús Hoyos-Rivera, Roberta Li...