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ECAI
2000
Springer
13 years 11 months ago
Learning Efficiently with Neural Networks: A Theoretical Comparison between Structured and Flat Representations
Abstract. We are interested in the relationship between learning efficiency and representation in the case of supervised neural networks for pattern classification trained by conti...
Marco Gori, Paolo Frasconi, Alessandro Sperduti
NIPS
2008
13 years 9 months ago
Clustered Multi-Task Learning: A Convex Formulation
In multi-task learning several related tasks are considered simultaneously, with the hope that by an appropriate sharing of information across tasks, each task may benefit from th...
Laurent Jacob, Francis Bach, Jean-Philippe Vert
ICML
2010
IEEE
13 years 8 months ago
Gaussian Processes Multiple Instance Learning
This paper proposes a multiple instance learning (MIL) algorithm for Gaussian processes (GP). The GP-MIL model inherits two crucial benefits from GP: (i) a principle manner of lea...
Minyoung Kim, Fernando De la Torre
CVPR
2006
IEEE
14 years 9 months ago
Incremental learning of object detectors using a visual shape alphabet
We address the problem of multiclass object detection. Our aims are to enable models for new categories to benefit from the detectors built previously for other categories, and fo...
Andreas Opelt, Axel Pinz, Andrew Zisserman
CHI
2002
ACM
14 years 8 months ago
Movement model, hits distribution and learning in virtual keyboarding
In a ten-session experiment, six participants practiced typing with an expanding rehearsal method on an optimized virtual keyboard. Based on a large amount of in-situ performance ...
Shumin Zhai, Alison E. Sue, Johnny Accot