In this work we give two new constructions of $\epsilon$-biased
generators. Our first construction answers an open question of
Dodis and Smith, and our second construction
significantly extends a result of Mossel et al.
In particular we obtain the following results:

1. We construct a family of asymptotically good binary ... more >>>

Around 2002, Leonid Gurvits gave a striking randomized algorithm to approximate the permanent of an n×n matrix A. The algorithm runs in O(n^2/?^2) time, and approximates Per(A) to within ±?||A||^n additive error. A major advantage of Gurvits's algorithm is that it works for arbitrary matrices, not just for nonnegative matrices. ... more >>>

Random walks in expander graphs and their various derandomizations (e.g., replacement/zigzag product) are invaluable tools from pseudorandomness. Recently, Ta-Shma used s-wide replacement walks in his breakthrough construction of a binary linear code almost matching the Gilbert-Varshamov bound (STOC 2017). Ta-Shma’s original analysis was entirely linear algebraic, and subsequent developments have ... more >>>

We construct a family of binary codes of relative distance $\frac{1}{2}-\varepsilon$ and rate $\varepsilon^{2} \cdot 2^{-\log^{\alpha}(1/\varepsilon)}$ for $\alpha \approx \frac{1}{2}$ that are decodable, probabilistically, in near linear time. This improves upon the rate of the state-of-the-art near-linear time decoding near the GV bound due to Jeronimo, Srivastava, and Tulsiani, who ... more >>>

Time efficient decoding algorithms for error correcting codes often require linear space. However, locally decodable codes yield more efficient randomized decoders that run in time $n^{1+o(1)}$ and space $n^{o(1)}$. In this work we focus on deterministic decoding.
Gronemeier showed that any non-adaptive deterministic decoder for a good code running ... more >>>

We survey recent and classical results and techniques concerning binary codes in the large distance (or, high-noise) regime, and the closely related notion of $\varepsilon$-balanced codes. Our (hopefully small-biased) column will mainly discuss encoding, and decoding from adversarial errors.

A previous version of this text originally appeared as an ACM ... more >>>