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ICALP
2009
Springer
14 years 7 months ago
Learning Halfspaces with Malicious Noise
We give new algorithms for learning halfspaces in the challenging malicious noise model, where an adversary may corrupt both the labels and the underlying distribution of examples....
Adam R. Klivans, Philip M. Long, Rocco A. Servedio
TCS
2010
13 years 5 months ago
Active learning in heteroscedastic noise
We consider the problem of actively learning the mean values of distributions associated with a finite number of options. The decision maker can select which option to generate t...
András Antos, Varun Grover, Csaba Szepesv&a...
COCO
2010
Springer
149views Algorithms» more  COCO 2010»
13 years 10 months ago
The Gaussian Surface Area and Noise Sensitivity of Degree-d Polynomial Threshold Functions
Abstract. We prove asymptotically optimal bounds on the Gaussian noise sensitivity of degree-d polynomial threshold functions. These bounds translate into optimal bounds on the Gau...
Daniel M. Kane
COGSCI
2004
142views more  COGSCI 2004»
13 years 7 months ago
Characterizing perceptual learning with external noise
Performance in perceptual tasks often improves with practice. This effect is known as `perceptual learning,' and it has been the source of a great deal of interest and debate...
Jason M. Gold, Allison B. Sekuler, Partrick J. Ben...
FOCS
2006
IEEE
14 years 1 months ago
Hardness of Learning Halfspaces with Noise
Learning an unknown halfspace (also called a perceptron) from labeled examples is one of the classic problems in machine learning. In the noise-free case, when a halfspace consist...
Venkatesan Guruswami, Prasad Raghavendra