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Let $f : \{0,1\}^n \times \{0,1\}^n \rightarrow \{0,1\}$ be a 2-party function. For every product distribution $\mu$ on $\{0,1\}^n \times \{0,1\}^n$, we show that $$\mathsf{CC}^\mu_{0.49}(f) = O\left(\left(\log \mathsf{prt}_{1/8}(f) \cdot…

Computational Complexity · Computer Science 2020-05-08 Prahladh Harsha , Rahul Jain , Jaikumar Radhakrishnan

We provide simple but surprisingly useful direct product theorems for proving lower bounds on online algorithms with a limited amount of advice about the future. As a consequence, we are able to translate decades of research on randomized…

Data Structures and Algorithms · Computer Science 2016-08-22 Jesper W. Mikkelsen

The Direct Product encoding of a string $a\in \{0,1\}^n$ on an underlying domain $V\subseteq \binom{n}{k}$, is a function DP$_V(a)$ which gets as input a set $S\in V$ and outputs $a$ restricted to $S$. In the Direct Product Testing Problem,…

Computational Complexity · Computer Science 2019-01-21 Elazar Goldenberg , Karthik C. S.

We consider a robust variant of the classical $k$-median problem, introduced by Anthony et al. \cite{AnthonyGGN10}. In the \emph{Robust $k$-Median problem}, we are given an $n$-vertex metric space $(V,d)$ and $m$ client sets $\set{S_i…

Data Structures and Algorithms · Computer Science 2013-09-19 Sayan Bhattacharya , Parinya Chalermsook , Kurt Mehlhorn , Adrian Neumann

The most widely used algorithm for floating point complex division, known as Smith's method, may fail more often than expected. This document presents two improved complex division algorithms. We present a proof of the robustness of the…

Mathematical Software · Computer Science 2012-10-18 Michael Baudin , Robert L. Smith

We show that, under a standard hardness assumption, there is no computationally efficient algorithm that given $n$ samples from an unknown distribution can give valid answers to $n^{3+o(1)}$ adaptively chosen statistical queries. A…

Machine Learning · Computer Science 2014-08-08 Moritz Hardt , Jonathan Ullman

We design an efficient sampling algorithm to generate samples from the hardcore model on random regular bipartite graphs as long as $\lambda \lesssim \frac{1}{\sqrt{\Delta}}$, where $\Delta$ is the degree. Combined with recent work of…

Data Structures and Algorithms · Computer Science 2026-04-24 Nicholas Kocurek , Shayan Oveis Gharan , Dante Tjowasi

We obtain a computational realization of the strong approximation theorem. That is, we develop algorithms to compute all congruence quotients modulo rational primes of a finitely generated Zariski dense group $H \leq \mathrm{SL}(n,…

Group Theory · Mathematics 2019-05-08 Alla Detinko , Dane Flannery , Alexander Hulpke

We describe and prove correctness of two practical algorithms for finding indecomposable summands of finitely generated modules over a finitely generated k-algebra R. The first algorithm applies in the (multi)graded case, which enables the…

Commutative Algebra · Mathematics 2026-05-28 Devlin Mallory , Mahrud Sayrafi

The hardcore model is a model of lattice gas systems which has received much attention in statistical physics, probability theory and theoretical computer science. It is the probability distribution over independent sets $I$ of a graph…

Computational Complexity · Computer Science 2010-06-01 Allan Sly

This letter presents a novel approach for \mbox{efficiently} computing time-index powered weighted sums of the form $\sum_{n=0}^{N-1} n^{K} v[n]$ using cascaded accumulators. Traditional direct computation requires $K{\times}N$ general…

Signal Processing · Electrical Eng. & Systems 2026-03-10 Deijany Rodriguez Linares , Oksana Moryakova , Håkan Johansson

Generating data from discrete distributions is important for a number of application domains including text, tabular data, and genomic data. Several groups have recently used random $k$-satisfiability ($k$-SAT) as a synthetic benchmark for…

Machine Learning · Computer Science 2026-03-24 Alankrita Bhatt , Mukur Gupta , Germain Kolossov , Andrea Montanari

An average-case variant of the $k$-SUM conjecture asserts that finding $k$ numbers that sum to 0 in a list of $r$ random numbers, each of the order $r^k$, cannot be done in much less than $r^{\lceil k/2 \rceil}$ time. On the other hand, in…

Cryptography and Security · Computer Science 2024-03-15 Itai Dinur , Nathan Keller , Ohad Klein

Data replication is used in distributed systems to maintain up-to-date copies of shared data across multiple computers in a network. However, despite decades of research, algorithms for achieving consistency in replicated systems are still…

Distributed, Parallel, and Cluster Computing · Computer Science 2017-08-30 Victor B. F. Gomes , Martin Kleppmann , Dominic P. Mulligan , Alastair R. Beresford

This paper revisits the problem of computing empirical cumulative distribution functions (ECDF) efficiently on large, multivariate datasets. Computing an ECDF at one evaluation point requires $\mathcal{O}(N)$ operations on a dataset…

Data Structures and Algorithms · Computer Science 2021-09-21 Nicolas Langrené , Xavier Warin

We obtain a strong invariance principle for nonconventional sums and applying this result we derive for them a version of the law of iterated logarithm, as well as an almost sure central limit theorem. Among motivations for such results are…

Probability · Mathematics 2012-09-11 Yuri Kifer

We show that if k-SUM is hard, in the sense that the standard algorithm is essentially optimal, then a variant of the SETH called the Primal Treewidth SETH is true. Formally: if there is an $\varepsilon>0$ and an algorithm which solves SAT…

Computational Complexity · Computer Science 2025-10-16 Michael Lampis

The problem of group extension can be divided into two sub-problems. The first is to find all the possible extensions of $H$ by $K$. The second is to find the different ways a group $G$ can arise as an extension of $H$ by $K$. Here we prove…

Group Theory · Mathematics 2007-05-23 Ayoub Joseph

Probabilistic programs are typically normal-looking programs describing posterior probability distributions. They intrinsically code up randomized algorithms and have long been at the heart of modern machine learning and approximate…

Programming Languages · Computer Science 2023-02-14 Lutz Klinkenberg , Tobias Winkler , Mingshuai Chen , Joost-Pieter Katoen

While probability theory is normally applied to external environments, there has been some recent interest in probabilistic modeling of the outputs of computations that are too expensive to run. Since mathematical logic is a powerful tool…

Artificial Intelligence · Computer Science 2016-10-10 Scott Garrabrant , Benya Fallenstein , Abram Demski , Nate Soares