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» A Framework for Multiple-Instance Learning
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ICPR
2008
IEEE
14 years 9 months ago
A discrete-time parallel update algorithm for distributed learning
We present a distributed machine learning framework based on support vector machines that allows classification problems to be solved iteratively through parallel update algorithm...
Christian Bauckhage, Tansu Alpcan
ICRA
2007
IEEE
110views Robotics» more  ICRA 2007»
14 years 2 months ago
A Reinforcement Learning Approach to Lift Generation in Flapping MAVs: Experimental Results
— In [17] we proposed an RL framework for control of flapping-wing MAVs. The algorithm has been discussed and simulation results using a quasi-steady model showed initial promis...
Mehran Motamed, Joseph Yan
ICML
2009
IEEE
14 years 8 months ago
Robust feature extraction via information theoretic learning
In this paper, we present a robust feature extraction framework based on informationtheoretic learning. Its formulated objective aims at simultaneously maximizing the Renyi's...
Xiaotong Yuan, Bao-Gang Hu
PCI
2005
Springer
14 years 1 months ago
Unsupervised Learning of Multiple Aspects of Moving Objects from Video
A popular framework for the interpretation of image sequences is based on the layered model; see e.g. Wang and Adelson [8], Irani et al. [2]. Jojic and Frey [3] provide a generativ...
Michalis K. Titsias, Christopher K. I. Williams
EUSFLAT
2003
13 years 9 months ago
Fuzzy models for prediction based on random set semantics
In this paper we propose a random set framework for learning linguistic models for prediction problems. We show how we can model prediction problems based on learning linguistic p...
Nicholas J. Randon, Jonathan Lawry