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CORR
2010
Springer
92views Education» more  CORR 2010»
15 years 6 months ago
Hardness Results for Agnostically Learning Low-Degree Polynomial Threshold Functions
Hardness results for maximum agreement problems have close connections to hardness results for proper learning in computational learning theory. In this paper we prove two hardnes...
Ilias Diakonikolas, Ryan O'Donnell, Rocco A. Serve...
JMLR
2010
143views more  JMLR 2010»
15 years 1 months ago
Rademacher Complexities and Bounding the Excess Risk in Active Learning
Sequential algorithms of active learning based on the estimation of the level sets of the empirical risk are discussed in the paper. Localized Rademacher complexities are used in ...
Vladimir Koltchinskii
NIPS
2000
15 years 8 months ago
Learning Winner-take-all Competition Between Groups of Neurons in Lateral Inhibitory Networks
It has long been known that lateral inhibition in neural networks can lead to a winner-take-all competition, so that only a single neuron is active at a steady state. Here we show...
Xiaohui Xie, Richard H. R. Hahnloser, H. Sebastian...
PATAT
2004
Springer
130views Education» more  PATAT 2004»
16 years 2 days ago
Learning User Preferences in Distributed Calendar Scheduling
Abstract. Within the field of software agents, there has been increasing interest in automating the process of calendar scheduling in recent years. Calendar (or meeting) schedulin...
Jean Oh, Stephen F. Smith
NIPS
2001
15 years 8 months ago
Efficiency versus Convergence of Boolean Kernels for On-Line Learning Algorithms
The paper studies machine learning problems where each example is described using a set of Boolean features and where hypotheses are represented by linear threshold elements. One ...
Roni Khardon, Dan Roth, Rocco A. Servedio