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We establish two new direct product theorems for the randomized query complexity of Boolean functions. The first shows that computing $n$ copies of a function $f$, even with a small success probability of $\gamma^n$, requires $\Theta(n)$…

Computational Complexity · Computer Science 2025-12-10 Shalev Ben-David , Eric Blais

We provide a type theoretic treatment of the paper "On Tarski's fixed point theorem" by Giovanni Curi. There are benefits to having a type theoretic formulation apart from routine implementation in a proof assistant. By taking advantage of…

Logic · Mathematics 2024-02-21 Ian Ray

Quantum algorithms for graph problems are considered, both in the adjacency matrix model and in an adjacency list-like array model. We give almost tight lower and upper bounds for the bounded error quantum query complexity of Connectivity,…

Quantum Physics · Physics 2016-12-30 Christoph Durr , Mark Heiligman , Peter Hoyer , Mehdi Mhalla

We show that, contrary to the commonly held view, there is a natural and optimal compactness theorem for $\mathrm{L}_{\infty\infty}$ which generalizes the usual compactness theorem for first order logic. The key to this result is the switch…

Logic · Mathematics 2025-07-29 Juan M Santiago Suárez , Matteo Viale

We show that for any constant $c>0$, any (two-sided error) adaptive algorithm for testing monotonicity of Boolean functions must have query complexity $\Omega(n^{1/2-c})$. This improves the $\tilde\Omega(n^{1/3})$ lower bound of [CWX17] and…

Computational Complexity · Computer Science 2025-11-10 Mark Chen , Xi Chen , Hao Cui , William Pires , Jonah Stockwell

We study the convergence of random function iterations for finding an invariant measure of the corresponding Markov operator. We call the problem of finding such an invariant measure the stochastic fixed point problem. This generalizes…

Functional Analysis · Mathematics 2022-03-24 Neal Hermer , D. Russell Luke , Anja Sturm

The problem of finding a local minimum of a black-box function is central for understanding local search as well as quantum adiabatic algorithms. For functions on the Boolean hypercube {0,1}^n, we show a lower bound of Omega(2^{n/4}/n) on…

Quantum Physics · Physics 2007-05-23 Scott Aaronson

In the Token Sliding problem we are given a graph $G$ and two independent sets $I_s$ and $I_t$ in $G$ of size $k \geq 1$. The goal is to decide whether there exists a sequence $\langle I_1, I_2, \ldots, I_\ell \rangle$ of independent sets…

Computational Complexity · Computer Science 2022-05-03 Valentin Bartier , Nicolas Bousquet , Jihad Hanna , Amer E. Mouawad , Sebastian Siebertz

We establish a number of new sufficient conditions for the existence of global (defined on the entire time axis) solutions of nonlinear nonautonomous systems by means of the Wazewski topological principle. The systems under consideration…

Classical Analysis and ODEs · Mathematics 2010-10-11 Volodymyr Lagoda , Igor Parasyuk

Methods for proving functional limit laws are developed for sequences of stochastic processes which allow a recursive distributional decomposition either in time or space. Our approach is an extension of the so-called contraction method to…

Probability · Mathematics 2015-09-10 Ralph Neininger , Henning Sulzbach

Motivated by the mode estimation problem of an unknown multivariate probability density function, we study the problem of identifying the point with the minimum k-th nearest neighbor distance for a given dataset of n points. We study the…

Machine Learning · Statistics 2020-10-27 Anirudh Singhal , Subham Pirojiwala , Nikhil Karamchandani

The spatial search problem consists in minimizing the number of steps required to find a given site in a network, under the restriction that only oracle queries or translations to neighboring sites are allowed. In this paper, a quantum…

Quantum Physics · Physics 2012-05-18 G. Abal , R. Donangelo , F. L. Marquezino , R. Portugal

A convergence analysis is developed for the regularized Newton method for training neural networks (NNs) in the overparameterized limit. As the number of hidden units tends to infinity, the NN training dynamics converge in probability to…

Machine Learning · Computer Science 2026-05-21 Konstantin Riedl , Konstantinos Spiliopoulos , Justin Sirignano

We consider maps defined on the interior of a normal, closed cone in a real Banach space that are nonexpansive with respect to Thompson's metric. With mild compactness assumptions, we prove that the Krasnoselskii iterates of such maps…

Functional Analysis · Mathematics 2023-08-15 Brian Lins

The probabilistic satisfiability of a logical expression is a fundamental concept known as the partition function in statistical physics and field theory, an evaluation of a related graph's Tutte polynomial in mathematics, and the…

Discrete Mathematics · Computer Science 2022-06-09 Stephen Eubank , Madhurima Nath , Yihui Ren , Abhijin Adiga

We investigate the Stochastic Krasnoselskii-Mann iterations for expected nonexpansive fixed-point problems in a real Hilbert space. We establish convergence guarantees under significantly weaker assumptions on the variance than those…

Optimization and Control · Mathematics 2026-05-12 Daniel Cortild , Coralia Cartis

We study the Steiner Tree problem on unit disk graphs. Given a $n$ vertex unit disk graph $G$, a subset $R\subseteq V(G)$ of $t$ vertices and a positive integer $k$, the objective is to decide if there exists a tree $T$ in $G$ that spans…

Computational Geometry · Computer Science 2020-04-21 Sujoy Bhore , Paz Carmi , Sudeshna Kolay , Meirav Zehavi

The rotation search problem aims to find a 3D rotation that best aligns a given number of point pairs. To induce robustness against outliers for rotation search, prior work considers truncated least-squares (TLS), which is a non-convex…

Optimization and Control · Mathematics 2022-07-22 Liangzu Peng , Mahyar Fazlyab , René Vidal

Minimizing a convex, quadratic objective of the form $f_{\mathbf{A},\mathbf{b}}(x) := \frac{1}{2}x^\top \mathbf{A} x - \langle \mathbf{b}, x \rangle$ for $\mathbf{A} \succ 0 $ is a fundamental problem in machine learning and optimization.…

Machine Learning · Computer Science 2019-04-17 Max Simchowitz

Let $\mathscr{F}_{n,d}$ be the class of all functions $f:\{-1,1\}^n\to[-1,1]$ on the $n$-dimensional discrete hypercube of degree at most $d$. In the first part of this paper, we prove that any (deterministic or randomized) algorithm which…

Machine Learning · Computer Science 2024-10-23 Alexandros Eskenazis , Paata Ivanisvili , Lauritz Streck