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The deployment and training of neural networks on edge computing devices pose many challenges. The low memory nature of edge devices is often one of the biggest limiting factors encountered in the deployment of large neural network models.…

Machine Learning · Computer Science 2023-06-01 Burak Bartan , Haoming Li , Harris Teague , Christopher Lott , Bistra Dilkina

The problem of detecting and removing redundant constraints is fundamental in optimization. We focus on the case of linear programs (LPs), given by $d$ variables with $n$ inequality constraints. A constraint is called \emph{redundant}, if…

Data Structures and Algorithms · Computer Science 2016-10-11 Komei Fukuda , May Szedlak

We consider a high-dimensional random constrained optimization problem in which a set of binary variables is subjected to a linear system of equations. The cost function is a simple linear cost, measuring the Hamming distance with respect…

Disordered Systems and Neural Networks · Physics 2022-11-23 Alfredo Braunstein , Louise Budzynski , Stefano Crotti , Federico Ricci-Tersenghi

Assuming we are in a Word-RAM model with word size $w$, we show that we can construct in $o(w)$ time an error correcting code with a constant relative positive distance that maps numbers of $w$ bits into $\Theta(w)$-bit numbers, and such…

Data Structures and Algorithms · Computer Science 2014-09-16 Djamal Belazzougui

Given n elements with nonnegative integer weights w1,..., wn and an integer capacity C, we consider the counting version of the classic knapsack problem: find the number of distinct subsets whose weights add up to at most the given…

Data Structures and Algorithms · Computer Science 2010-08-11 Daniel Stefankovic , Santosh Vempala , Eric Vigoda

We give sublinear-time approximation algorithms for some optimization problems arising in machine learning, such as training linear classifiers and finding minimum enclosing balls. Our algorithms can be extended to some kernelized versions…

Machine Learning · Computer Science 2010-10-22 Kenneth L. Clarkson , Elad Hazan , David P. Woodruff

Four algorithms for propositional forgetting are compared. The first performs all possible resolutions and deletes the clauses containing a variable to forget. The second forgets a variable at time by resolving and then deleting all clauses…

Logic in Computer Science · Computer Science 2022-04-14 Paolo Liberatore

In the last decade remarkable progress has been made in development of suitable proof techniques for analysing randomised search heuristics. The theoretical investigation of these algorithms on classes of functions is essential to the…

Neural and Evolutionary Computing · Computer Science 2020-10-22 Frank Neumann , Mojgan Pourhassan , Carsten Witt

A prefix normal word is a binary word with the property that no substring has more 1s than the prefix of the same length. This class of words is important in the context of binary jumbled pattern matching. In this paper we present an…

Data Structures and Algorithms · Computer Science 2014-06-23 Péter Burcsi , Gabriele Fici , Zsuzsanna Lipták , Frank Ruskey , Joe Sawada

Logical forgetting may take exponential time in general, but it does not when its input is a single-head propositional definite Horn formula. Single-head means that no variable is the head of multiple clauses. An algorithm to make a formula…

Artificial Intelligence · Computer Science 2020-12-21 Paolo Liberatore

We study the complexity of query answering using views in a probabilistic XML setting, identifying large classes of XPath queries -- with child and descendant navigation and predicates -- for which there are efficient (PTime) algorithms. We…

Databases · Computer Science 2012-08-02 Bogdan Cautis , Evgeny Kharlamov

We study variable time search, a form of quantum search where queries to different items take different time. Our first result is a new quantum algorithm that performs variable time search with complexity $O(\sqrt{T}\log n)$ where…

Quantum Physics · Physics 2023-08-04 Andris Ambainis , Martins Kokainis , Jevgēnijs Vihrovs

Given a sample covariance matrix, we examine the problem of maximizing the variance explained by a linear combination of the input variables while constraining the number of nonzero coefficients in this combination. This is known as sparse…

Artificial Intelligence · Computer Science 2011-11-10 Alexandre d'Aspremont , Francis Bach , Laurent El Ghaoui

For a fixed arbitrary matrix depending on $n$ variables, one may ask whether a Prenex Normal Form (PNF) implies another. A RAM algorithm running in linear time is presented and shown to be asymptotically optimal.

Data Structures and Algorithms · Computer Science 2025-04-23 Adam Wang

This note is an attempt to unconditionally prove the existence of weak one way functions (OWF). Starting from a provably intractable decision problem $L_D$ (whose existence is nonconstructively assured from the well-known discrete…

Computational Complexity · Computer Science 2023-07-19 Stefan Rass

In this paper we propose a framework to analyze iterative first-order optimization algorithms for time-varying convex optimization. We assume that the temporal variability is caused by a time-varying parameter entering the objective, which…

Optimization and Control · Mathematics 2026-03-05 Fabian Jakob , Andrea Iannelli

We study optimization problems that are neither approximable in polynomial time (at least with a constant factor) nor fixed parameter tractable, under widely believed complexity assumptions. Specifically, we focus on Maximum Independent…

Data Structures and Algorithms · Computer Science 2008-10-29 Marek Cygan , Lukasz Kowalik , Marcin Pilipczuk , Mateusz Wykurz

We give algorithms with running time $2^{O({\sqrt{k}\log{k}})} \cdot n^{O(1)}$ for the following problems. Given an $n$-vertex unit disk graph $G$ and an integer $k$, decide whether $G$ contains (1) a path on exactly/at least $k$ vertices,…

Data Structures and Algorithms · Computer Science 2017-04-25 Fedor V. Fomin , Daniel Lokshtanov , Fahad Panolan , Saket Saurabh , Meirav Zehavi

Given a set of numbers, the $k$-SUM problem asks for a subset of $k$ numbers that sums to zero. When the numbers are integers, the time and space complexity of $k$-SUM is generally studied in the word-RAM model; when the numbers are reals,…

Data Structures and Algorithms · Computer Science 2016-05-25 Andrea Lincoln , Virginia Vassilevska Williams , Joshua R. Wang , R. Ryan Williams

We consider dynamic programming problems with a large time horizon, and give sufficient conditions for the existence of the uniform value. As a consequence, we obtain an existence result when the state space is precompact, payoffs are…

Optimization and Control · Mathematics 2009-04-20 Jérôme Renault