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CVPR
2009
IEEE
16 years 11 months ago
An Instance Selection Approach to Multiple Instance Learning
Multiple-instance Learning (MIL) is a new paradigm of supervised learning that deals with the classification of bags. Each bag is presented as a collection of instances from whi...
Zhouyu Fu (Australian National University), Antoni...
IJCNN
2008
IEEE
15 years 10 months ago
Hybrid learning architecture for unobtrusive infrared tracking support
—The system architecture presented in this paper is designed for helping an aged person to live longer independently in their own home by detecting unusual and potentially hazard...
K. K. Kiran Bhagat, Stefan Wermter, Kevin Burn
MICAI
2007
Springer
15 years 10 months ago
Weighted Instance-Based Learning Using Representative Intervals
Instance-based learning algorithms are widely used due to their capacity to approximate complex target functions; however, the performance of this kind of algorithms degrades signi...
Octavio Gómez, Eduardo F. Morales, Jes&uacu...
FOCS
1999
IEEE
15 years 8 months ago
An Algorithmic Theory of Learning: Robust Concepts and Random Projection
We study the phenomenon of cognitive learning from an algorithmic standpoint. How does the brain effectively learn concepts from a small number of examples despite the fact that e...
Rosa I. Arriaga, Santosh Vempala
COLT
1995
Springer
15 years 7 months ago
Learning with Unreliable Boundary Queries
We introduce a new model for learning with membership queries in which queries near the boundary of a target concept may receive incorrect or “don’t care” responses. In part...
Avrim Blum, Prasad Chalasani, Sally A. Goldman, Do...