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CORR
2011
Springer
178views Education» more  CORR 2011»
14 years 5 months ago
Online Learning: Stochastic and Constrained Adversaries
Learning theory has largely focused on two main learning scenarios. The first is the classical statistical setting where instances are drawn i.i.d. from a fixed distribution and...
Alexander Rakhlin, Karthik Sridharan, Ambuj Tewari
CORR
2008
Springer
173views Education» more  CORR 2008»
15 years 1 months ago
Decomposition Principles and Online Learning in Cross-Layer Optimization for Delay-Sensitive Applications
In this paper, we propose a general cross-layer optimization framework in which we explicitly consider both the heterogeneous and dynamically changing characteristics of delay-sens...
Fangwen Fu, Mihaela van der Schaar
IADIS
2004
15 years 3 months ago
Detecting Unauthorized Use in Online Journal Archives: A Case Study
JSTOR is a not-for-profit online library containing a full back-run of digitized versions of a large number of academic journals. In order to help defray costs for maintaining the...
Paul Seligman, Sean W. Smith
116
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ICPR
2010
IEEE
15 years 7 months ago
On-Line Random Naive Bayes for Tracking
—Randomized learning methods (i.e., Forests or Ferns) have shown excellent capabilities for various computer vision applications. However, it was shown that the tree structure in...
Martin Godec, Christian Leistner, Amir Saffari, Ho...
NIPS
2003
15 years 3 months ago
Online Passive-Aggressive Algorithms
We present a family of margin based online learning algorithms for various prediction tasks. In particular we derive and analyze algorithms for binary and multiclass categorizatio...
Shai Shalev-Shwartz, Koby Crammer, Ofer Dekel, Yor...