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AAAI
2007
15 years 9 months ago
Learning by Combining Observations and User Edits
We introduce a new collaborative machine learning paradigm in which the user directs a learning algorithm by manually editing the automatically induced model. We identify a generi...
Vittorio Castelli, Lawrence D. Bergman, Daniel Obl...
COLT
2008
Springer
15 years 8 months ago
Learning Coordinate Gradients with Multi-Task Kernels
Coordinate gradient learning is motivated by the problem of variable selection and determining variable covariation. In this paper we propose a novel unifying framework for coordi...
Yiming Ying, Colin Campbell
ICML
2009
IEEE
16 years 7 months ago
Learning nonlinear dynamic models
We present a novel approach for learning nonlinear dynamic models, which leads to a new set of tools capable of solving problems that are otherwise difficult. We provide theory sh...
John Langford, Ruslan Salakhutdinov, Tong Zhang
ICML
2007
IEEE
16 years 7 months ago
A bound on the label complexity of agnostic active learning
We study the label complexity of pool-based active learning in the agnostic PAC model. Specifically, we derive general bounds on the number of label requests made by the A2 algori...
Steve Hanneke
ICML
2005
IEEE
16 years 7 months ago
Why skewing works: learning difficult Boolean functions with greedy tree learners
We analyze skewing, an approach that has been empirically observed to enable greedy decision tree learners to learn "difficult" Boolean functions, such as parity, in the...
Bernard Rosell, Lisa Hellerstein, Soumya Ray, Davi...