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CORR
2010
Springer
141views Education» more  CORR 2010»
13 years 8 months ago
Agnostic Active Learning Without Constraints
We present and analyze an agnostic active learning algorithm that works without keeping a version space. This is unlike all previous approaches where a restricted set of candidate...
Alina Beygelzimer, Daniel Hsu, John Langford, Tong...
SIGMOD
1998
ACM
95views Database» more  SIGMOD 1998»
13 years 7 months ago
Unbundling Active Functionality
Abstract New application areas or new technical innovations expect from database management systems more and more new functionality. However, adding functions to the DBMS as an int...
Stella Gatziu, Arne Koschel, Günter von B&uum...
NN
2000
Springer
167views Neural Networks» more  NN 2000»
13 years 7 months ago
Blind signal processing by the adaptive activation function neurons
The aim of this paper is to study an Information Theory based learning theory for neural units endowed with adaptive activation functions. The learning theory has the target to fo...
Simone Fiori
ISBI
2006
IEEE
14 years 8 months ago
Reconstruction of functional activations in diffuse optical imaging
We propose a new algorithm for the estimation of functional activations in diffuse optical imaging. Our approach considers the activations to be support limited. We simultaneously...
Mathews Jacob, Vlad Toronov, Yoram Bresler, Xiaofe...
ICML
2005
IEEE
14 years 8 months ago
Active learning for Hidden Markov Models: objective functions and algorithms
Hidden Markov Models (HMMs) model sequential data in many fields such as text/speech processing and biosignal analysis. Active learning algorithms learn faster and/or better by cl...
Brigham Anderson, Andrew Moore