Randomness extractors are important tools in cryptography. Their goal is to compress a high-entropy source into a more uniform output. Beyond their theoretical interest, they have ...
Various efforts ([?, ?, ?]) have been made in recent years to derandomize probabilistic algorithms using the complexity theoretic assumption that there exists a problem in E = dti...
Russell Impagliazzo, Ronen Shaltiel, Avi Wigderson
The design of feature spaces for local image descriptors is an important research subject in computer vision due to its applicability in several problems, such as visual classifi...
Randomness extractors convert weak sources of randomness into an almost uniform distribution; the conversion uses a small amount of pure randomness. In algorithmic applications, t...
We present a new technique called balanced randomized tree splitting. It is useful in constructing unknown trees recursively. By applying it we obtain two new results on efficient ...