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» Sequential Instance-Based Learning
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ICCV
2003
IEEE
14 years 9 months ago
Weighted and Robust Incremental Method for Subspace Learning
Visual learning is expected to be a continuous and robust process, which treats input images and pixels selectively. In this paper we present a method for subspace learning, which...
Danijel Skocaj, Ales Leonardis
NECO
2008
112views more  NECO 2008»
13 years 7 months ago
Second-Order SMO Improves SVM Online and Active Learning
Iterative learning algorithms that approximate the solution of support vector machines (SVMs) have two potential advantages. First, they allow for online and active learning. Seco...
Tobias Glasmachers, Christian Igel
ICML
2003
IEEE
14 years 8 months ago
Bayes Meets Bellman: The Gaussian Process Approach to Temporal Difference Learning
We present a novel Bayesian approach to the problem of value function estimation in continuous state spaces. We define a probabilistic generative model for the value function by i...
Yaakov Engel, Shie Mannor, Ron Meir
COLT
2006
Springer
13 years 11 months ago
Online Learning with Constraints
In this paper, we study a sequential decision making problem. The objective is to maximize the total reward while satisfying constraints, which are defined at every time step. The...
Shie Mannor, John N. Tsitsiklis
IFIP3
2003
114views Education» more  IFIP3 2003»
13 years 9 months ago
Enabling Postgraduate Learning in the Workplace
: This paper describes a research project that was carried out to determine and evaluate the learning environment customisations required to support selfmotivated, able, and experi...
Nicola Beasley, John A. Ford, Nils Tomes