Hardness amplification is the fundamental task of converting a -hard function f : {0, 1}n {0, 1} into a (1/2 - )-hard function Amp(f), where f is -hard if small circuits fail to c...
Local Search problem, which finds a local minimum of a black-box function on a given graph, is of both practical and theoretical importance to combinatorial optimization, complexi...
Discrepancy is a versatile bound in communication complexity which can be used to show lower bounds in the distributional, randomized, quantum, and even unbounded error models of ...
Decision table decomposition is a machine learning approach that decomposes a given decision table into an equivalent hierarchy of decision tables. The approach aims to discover d...
This paper discusses building complex classifiers from a single labeled example and vast number of unlabeled observation sets, each derived from observation of a single process or...