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Related papers: Strongly refuting all semi-random Boolean CSPs

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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

Semi-bent Boolean functions are interesting from a cryptographic standpoint, since they possess several desirable properties such as having a low and flat Walsh spectrum, which is useful to resist linear cryptanalysis. In this paper, we…

Cellular Automata and Lattice Gases · Physics 2020-05-19 Luca Mariot , Martina Saletta , Alberto Leporati , Luca Manzoni

We characterize the points that satisfy Birkhoff's ergodic theorem under certain computability conditions in terms of algorithmic randomness. First, we use the method of cutting and stacking to show that if an element x of the Cantor space…

Logic · Mathematics 2012-06-14 Johanna N. Y. Franklin , Henry Towsner

We consider the problem of approximately solving constraint satisfaction problems with arity $k > 2$ ($k$-CSPs) on instances satisfying certain expansion properties, when viewed as hypergraphs. Random instances of $k$-CSPs, which are also…

Data Structures and Algorithms · Computer Science 2019-07-19 Vedat Levi Alev , Fernando Granha Jeronimo , Madhur Tulsiani

In this work, we consider the fundamental problem of deriving quantitative bounds on the probability that a given assertion is violated in a probabilistic program. We provide automated algorithms that obtain both lower and upper bounds on…

Programming Languages · Computer Science 2020-12-02 Jinyi Wang , Yican Sun , Hongfei Fu , Krishnendu Chatterjee , Amir Kafshdar Goharshady

In this paper, we prove that with high probability, random Reed-Solomon codes approach the half-Singleton bound - the optimal rate versus error tradeoff for linear insdel codes - with linear-sized alphabets. More precisely, we prove that,…

Information Theory · Computer Science 2024-07-11 Roni Con , Zeyu Guo , Ray Li , Zihan Zhang

This paper explores a fine-grained version of the Watrous conjecture, including the randomized and quantum algorithms with success probabilities arbitrarily close to $1/2$. Our contributions include the following: i) An analysis of the…

Computational Complexity · Computer Science 2023-10-24 Supartha Podder , Penghui Yao , Zekun Ye

We give a spectral algorithm for decomposing overcomplete order-4 tensors, so long as their components satisfy an algebraic non-degeneracy condition that holds for nearly all (all but an algebraic set of measure $0$) tensors over…

Machine Learning · Computer Science 2022-03-08 Samuel B. Hopkins , Tselil Schramm , Jonathan Shi

It has often been claimed in recent papers that one can find a degree d Sum-of-Squares proof if one exists via the Ellipsoid algorithm. In [O17], Ryan O'Donnell notes this widely quoted claim is not necessarily true. He presents an example…

Computational Complexity · Computer Science 2017-02-20 Prasad Raghavendra , Benjamin Weitz

Constraint satisfaction problems (CSPs) are ubiquitous in theoretical computer science. We study the problem of StrongCSPs, i.e. instances where a large induced sub-instance has a satisfying assignment. More formally, given a CSP instance…

Data Structures and Algorithms · Computer Science 2022-05-24 Suprovat Ghoshal , Anand Louis

This paper shows that, if we could examine the entire history of a hidden variable, then we could efficiently solve problems that are believed to be intractable even for quantum computers. In particular, under any hidden-variable theory…

Quantum Physics · Physics 2007-05-23 Scott Aaronson

In this paper we study stochastic quasi-Newton methods for nonconvex stochastic optimization, where we assume that noisy information about the gradients of the objective function is available via a stochastic first-order oracle (SFO). We…

Optimization and Control · Mathematics 2017-05-23 Xiao Wang , Shiqian Ma , Donald Goldfarb , Wei Liu

In semidefinite programming a proposed optimal solution may be quite poor in spite of having sufficiently small residual in the optimality conditions. This issue may be framed in terms of the discrepancy between forward error (the…

Optimization and Control · Mathematics 2019-08-14 Stefan Sremac , Hugo J. Woerdeman , Henry Wolkowicz

We study randomized algorithms for constrained optimization, in abstract frameworks that include, in strictly increasing generality: convex programming; LP-type problems; violator spaces; and a setting we introduce, consistent spaces. Such…

Computational Geometry · Computer Science 2019-06-04 Kenneth L. Clarkson , Bernd Gärtner , Johannes Lengler , May Szedlak

We investigate the impact of modifying the constraining relations of a Constraint Satisfaction Problem (CSP) instance, with a fixed template, on the set of solutions of the instance. More precisely we investigate sensitive instances: an…

Logic in Computer Science · Computer Science 2020-05-04 Libor Barto , Marcin Kozik , Johnson Tan , Matt Valeriote

We define tests of boolean functions which distinguish between linear (or quadratic) polynomials, and functions which are very far, in an appropriate sense, from these polynomials. The tests have optimal or nearly optimal trade-offs between…

Combinatorics · Mathematics 2007-05-23 Alex Samorodnitsky

We give a {\em deterministic} algorithm for approximately computing the fraction of Boolean assignments that satisfy a degree-$2$ polynomial threshold function. Given a degree-2 input polynomial $p(x_1,\dots,x_n)$ and a parameter $\eps >…

Computational Complexity · Computer Science 2013-11-28 Anindya De , Ilias Diakonikolas , Rocco A. Servedio

The quantum k-Local Hamiltonian problem is a natural generalization of classical constraint satisfaction problems (k-CSP) and is complete for QMA, a quantum analog of NP. Although the complexity of k-Local Hamiltonian problems has been well…

Quantum Physics · Physics 2021-11-16 Ojas Parekh , Kevin Thompson

We revisit the problem of computing submatrices of the Cram\'er-Rao bound (CRB), which lower bounds the variance of any unbiased estimator of a vector parameter $\vth$. We explore iterative methods that avoid direct inversion of the Fisher…

Information Theory · Computer Science 2015-06-04 Paul Tune

Consider nonzero vectors $a_{1},\dots,a_{n}\in\mathbb{C}^{k}$, independent Rademacher random variables $\xi_{1},\dots,\xi_{n}$, and a set $S\subseteq\mathbb{C}^{k}$. What upper bounds can we prove on the probability that the random sum…

Combinatorics · Mathematics 2025-06-02 Alexandr Grebennikov , Matthew Kwan