The hardness vs. randomness paradigm converts a function $f \colon \{0,1\}^n \rightarrow \{0,1\}$ that is hard for circuits of size $s$ into a pseudorandom generator (PRG) $G \colon \{0,1\}^d \to \{0,1\}^{s'}$ that fools circuits of size $s' = s'(s)$. In the application for derandomization, such as proofs of $\mathbf{BPP} = ... more >>>

We provide a unified method for constructing explicit distributions which are difficult for restricted models of computation to generate. Our constructions are based on a new notion of robust extractors, which are extractors that remain sound even when a small number of points violate the min-entropy constraint. Using such objects, ... more >>>

Understanding the power of space-bounded computation with access to catalytic space has been an important theme in complexity theory over the recent years. One of the key algorithmic results in this area is that bipartite maximum matching can be computed in catalytic logspace with a polynomial-time bound, Agarwala and Mertz ... more >>>