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» Adaptive Online Gradient Descent
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NIPS
2008
14 years 11 months ago
Online Metric Learning and Fast Similarity Search
Metric learning algorithms can provide useful distance functions for a variety of domains, and recent work has shown good accuracy for problems where the learner can access all di...
Prateek Jain, Brian Kulis, Inderjit S. Dhillon, Kr...
91
Voted
NIPS
2001
14 years 11 months ago
Online Learning with Kernels
Abstract--Kernel-based algorithms such as support vector machines have achieved considerable success in various problems in batch setting, where all of the training data is availab...
Jyrki Kivinen, Alex J. Smola, Robert C. Williamson
CVIU
2007
154views more  CVIU 2007»
14 years 9 months ago
Smart particle filtering for high-dimensional tracking
Tracking articulated structures like a hand or body within a reasonable time is challenging because of the high dimensionality of the state space. Recently, a new optimization met...
Matthieu Bray, Esther Koller-Meier, Luc J. Van Goo...
92
Voted
ESANN
2006
14 years 11 months ago
Magnification control for batch neural gas
Neural gas (NG) constitutes a very robust clustering algorithm which can be derived as stochastic gradient descent from a cost function closely connected to the quantization error...
Barbara Hammer, Alexander Hasenfuss, Thomas Villma...
85
Voted
PPSN
2010
Springer
14 years 8 months ago
A Natural Evolution Strategy for Multi-objective Optimization
Abstract. The recently introduced family of natural evolution strategies (NES), a novel stochastic descent method employing the natural gradient, is providing a more principled alt...
Tobias Glasmachers, Tom Schaul, Jürgen Schmid...