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» On regularization algorithms in learning theory
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ICML
2009
IEEE
16 years 5 months ago
Boosting with structural sparsity
Despite popular belief, boosting algorithms and related coordinate descent methods are prone to overfitting. We derive modifications to AdaBoost and related gradient-based coordin...
John Duchi, Yoram Singer
157
Voted
IJIT
2004
15 years 6 months ago
Design of Gain Scheduled Fuzzy PID Controller
An adaptive fuzzy PID controller with gain scheduling is proposed in this paper. The structure of the proposed gain scheduled fuzzy PID (GS_FPID) controller consists of both fuzzy ...
Leehter Yao, Chin-chin Lin
TIP
2008
169views more  TIP 2008»
15 years 4 months ago
Weakly Supervised Learning of a Classifier for Unusual Event Detection
In this paper, we present an automatic classification framework combining appearance based features and Hidden Markov Models (HMM) to detect unusual events in image sequences. One...
Mark Jager, Christian Knoll, Fred A. Hamprecht
NIPS
2007
15 years 6 months ago
The Tradeoffs of Large Scale Learning
This contribution develops a theoretical framework that takes into account the effect of approximate optimization on learning algorithms. The analysis shows distinct tradeoffs for...
Léon Bottou, Olivier Bousquet
ICPR
2010
IEEE
15 years 8 months ago
Localized Multiple Kernel Regression
Multiple kernel learning (MKL) uses a weighted combination of kernels where the weight of each kernel is optimized during training. However, MKL assigns the same weight to a kerne...
Mehmet Gönen, Ethem Alpaydin