A seminal result in learning theory characterizes the PAC learnability of binary classes
through the Vapnik-Chervonenkis dimension. Extending this characterization to the general …

Stochastic convex optimization is one of the most well-studied models for learning in modern
machine learning. Nevertheless, a central fundamental question in this setup remained …

A collection of sets displays a proximity gap with respect to some property if for every set in
the collection, either (i) all members are δ-close to the property in relative Hamming distance …

Concretely efficient interactive oracle proofs (IOPs) are of interest due to their applications to
scaling blockchains, their minimal security assumptions, and their potential future-proof …

We prove a function field version of Chowla's conjecture on the autocorrelation of the
Mobius function in the limit of a large finite field.

… Dan Carmon Dan Carmon … In Carmon & Rudnick [1], an upper bound on |C(α 1 ,…,α r ;n)|
was established for fields of odd characteristic, demonstrating that Inline Formula holds for …

Given disjoint sets S, S'⊆ 𝔽 q of size n and a function f: S→ 𝔽 q, where 𝔽 q is a finite field,
the low-degree extension (LDE) of f to S'is the function f': S'→ 𝔽 q obtained by restricting the …

For smooth finite fields $F_q$ (ie, when $q-1$ factors into small primes) the Fast Fourier
Transform (FFT) leads to the fastest known algebraic algorithms for many basic polynomial …

Common sense suggests that consumers make more satisfying decisions as they consider
their options more closely. Yet we argue that such close consideration can have undesirable …

The discovery of formulas involving mathematical constants such as $\pi $ and $ e $ had a
great impact on various fields of science and mathematics. However, such discoveries have …