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...
Abstract--Functional verification is one of the major bottlenecks in system-on-chip design due to the combined effects of increasing complexity and lack of automated techniques for...
Abstract. A brief overview is given of recent results on theory revision with queries for propositional formulas, such as monotone and unate DNF, Horn formulas, read-once formulas,...
The use of Mercer kernel methods in statistical learning theory provides for strong learning capabilities, as seen in kernel principal component analysis and support vector machin...
Abstract. This paper shows how multi-dimensional functions, describing the operation of complex equipment, can be learned. The functions are points in a shape space, each produced ...