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Submodular function minimization (SFM) and matroid intersection are fundamental discrete optimization problems with applications in many fields. It is well known that both of these can be solved making $\mathrm{poly}(N)$ queries to a…

Data Structures and Algorithms · Computer Science 2021-11-16 Deeparnab Chakrabarty , Yu Chen , Sanjeev Khanna

Dawar and Wilsenach (ICALP 2020) introduce the model of symmetric arithmetic circuits and show an exponential separation between the sizes of symmetric circuits for computing the determinant and the permanent. The symmetry restriction is…

Computational Complexity · Computer Science 2024-09-02 Anuj Dawar , Gregory Wilsenach

Submodular maximization is a general optimization problem with a wide range of applications in machine learning (e.g., active learning, clustering, and feature selection). In large-scale optimization, the parallel running time of an…

Data Structures and Algorithms · Computer Science 2023-04-11 Matthew Fahrbach , Vahab Mirrokni , Morteza Zadimoghaddam

Motivated by the challenge of nonstationarity in sequential decision making, we study Online Convex Optimization (OCO) under the coupling of two problem structures: the domain is unbounded, and the comparator sequence $u_1,\ldots,u_T$ is…

Machine Learning · Computer Science 2023-10-27 Zhiyu Zhang , Ashok Cutkosky , Ioannis Ch. Paschalidis

In recent years, finding new satisfiability algorithms for various circuit classes has been a very active line of research. Despite considerable progress, we are still far away from a definite answer on which circuit classes allow fast…

Computational Complexity · Computer Science 2013-06-19 Stefan Schneider

We present quantum circuits for comparison and increment operations that achieve an asymptotically optimal gate count of $\Theta(n)$ and depth of $\Theta(\log n)$ over the Clifford+Toffoli gate set, while using a provably minimal number of…

Quantum Physics · Physics 2026-03-16 Vivien Vandaele

We consider a model of computation motivated by possible limitations on quantum computers. We have a linear array of n wires, and we may perform operations only on pairs of adjacent wires. Our goal is to build a circuits that perform…

Quantum Physics · Physics 2007-05-23 Samuel A. Kutin , David Petrie Moulton , Lawren M. Smithline

We establish new correlation bounds and pseudorandom generators for a collection of computation models. These models are all natural generalizations of structured low-degree $F_2$-polynomials that we did not have correlation bounds for…

Computational Complexity · Computer Science 2025-01-07 Vinayak M. Kumar

We give the first super-polynomial separation in the power of bounded-depth boolean formulas vs. circuits. Specifically, we consider the problem Distance $k(n)$ Connectivity, which asks whether two specified nodes in a graph of size $n$ are…

Computational Complexity · Computer Science 2013-12-03 Benjamin Rossman

We consider the problem of finding a near ground state of a $p$-spin model with Rademacher couplings by means of a low-depth circuit. As a direct extension of the authors' recent work [Gamarnik, Jagannath, Wein 2020], we establish that any…

Computational Complexity · Computer Science 2022-01-25 David Gamarnik , Aukosh Jagannath , Alexander S. Wein

A long-standing open question in the algorithms and complexity literature is whether there exist sorting circuits of size $o(n \log n)$. A recent work by Asharov, Lin, and Shi (SODA'21) showed that if the elements to be sorted have short…

Data Structures and Algorithms · Computer Science 2021-11-09 Wei-Kai Lin , Elaine Shi

We propose a new method for proving lower bounds on quantum query algorithms. Instead of a classical adversary that runs the algorithm with one input and then modifies the input, we use a quantum adversary that runs the algorithm with a…

Quantum Physics · Physics 2007-05-23 Andris Ambainis

Algorithm evaluation and comparison are fundamental questions in machine learning and statistics -- how well does an algorithm perform at a given modeling task, and which algorithm performs best? Many methods have been developed to assess…

Statistics Theory · Mathematics 2025-11-25 Yuetian Luo , Rina Foygel Barber

We initiate the study of generalized AC0 circuits comprised of negations and arbitrary unbounded fan-in gates that only need to be constant over inputs of Hamming weight $\ge k$, which we denote GC0$(k)$. The gate set of this class includes…

Computational Complexity · Computer Science 2023-05-23 Vinayak M. Kumar

$\newcommand{\ACz}{\mathbf{AC}^0}$ H\r{a}stad showed that any De Morgan formula (composed of AND, OR and NOT gates) shrinks by a factor of $\tilde{O}(p^{2})$ under a random restriction that leaves each variable alive independently with…

Computational Complexity · Computer Science 2024-12-09 Yuval Filmus , Or Meir , Avishay Tal

We investigate the complexity of uniform OR circuits and AND circuits of polynomial-size and depth. As their name suggests, OR circuits have OR gates as their computation gates, as well as the usual input, output and constant (0/1) gates.…

Computational Complexity · Computer Science 2013-09-06 Niall Murphy , Damien Woods

Arithmetic circuits are a natural well-studied model for computing multivariate polynomials over a field. In this paper, we study planar arithmetic circuits. These are circuits whose underlying graph is planar. In particular, we prove an…

Computational Complexity · Computer Science 2025-09-16 C. Ramya , Pratik Shastri

We provide an $\Omega(log(n))$ lower bound for the depth of any quantum circuit generating the unique groundstate of Kitaev's spherical code. No circuit-depth lower bound was known before on this code in the general case where the gates can…

Quantum Physics · Physics 2018-10-10 Dorit Aharonov , Yonathan Touati

In this paper, we study the structure of set-multilinear arithmetic circuits and set-multilinear branching programs with the aim of showing lower bound results. We define some natural restrictions of these models for which we are able to…

Computational Complexity · Computer Science 2015-11-10 V. Arvind , S. Raja

We study lower bounds on adaptive sensing algorithms for recovering low rank matrices using linear measurements. Given an $n \times n$ matrix $A$, a general linear measurement $S(A)$, for an $n \times n$ matrix $S$, is just the inner…

Data Structures and Algorithms · Computer Science 2024-02-21 Praneeth Kacham , David P Woodruff