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» Online Learning: Beyond Regret
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COLT
2010
Springer
13 years 5 months ago
Robust Selective Sampling from Single and Multiple Teachers
We present a new online learning algorithm in the selective sampling framework, where labels must be actively queried before they are revealed. We prove bounds on the regret of ou...
Ofer Dekel, Claudio Gentile, Karthik Sridharan
CE
2008
128views more  CE 2008»
13 years 7 months ago
Beyond threaded discussion: Representational guidance in asynchronous collaborative learning environments
Although most online learning environments are predominately text based, researchers have argued that representational support for the conceptual structure of a problem would addr...
Daniel D. Suthers, Ravi K. Vatrapu, Richard Medina...
CORR
2011
Springer
178views Education» more  CORR 2011»
12 years 11 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
ICASSP
2010
IEEE
13 years 7 months ago
Distributed learning in cognitive radio networks: Multi-armed bandit with distributed multiple players
—We consider a cognitive radio network with distributed multiple secondary users, where each user independently searches for spectrum opportunities in multiple channels without e...
Keqin Liu, Qing Zhao
NC
2002
196views Neural Networks» more  NC 2002»
13 years 7 months ago
Beyond second-order statistics for learning: A pairwise interaction model for entropy estimation
Second order statistics have formed the basis of learning and adaptation due to its appeal and analytical simplicity. On the other hand, in many realistic engineering problems requ...
Deniz Erdogmus, José Carlos Príncipe...