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In this paper, we focus on developing randomized algorithms for the computation of low multilinear rank approximations of tensors based on the random projection and the singular value decomposition. Following the theory of the singular…

Numerical Analysis · Mathematics 2020-03-20 Maolin Che , Yimin Wei , Hong Yan

The tree-width of a multivariate polynomial is the tree-width of the hypergraph with hyperedges corresponding to its terms. Multivariate polynomials of bounded tree-width have been studied by Makowsky and Meer as a new sparsity condition…

Machine Learning · Computer Science 2025-01-15 Karine Chubarian , Johnny Joyce , Gyorgy Turan

This paper investigates the usage of generating functions (GFs) encoding measures over the program variables for reasoning about discrete probabilistic programs. To that end, we define a denotational GF-transformer semantics for…

Logic in Computer Science · Computer Science 2020-07-14 Lutz Klinkenberg , Kevin Batz , Benjamin Lucien Kaminski , Joost-Pieter Katoen , Joshua Moerman , Tobias Winkler

Let $P = \{p(i)\}$ be a measure of strictly positive probabilities on the set of nonnegative integers. Although the countable number of inputs prevents usage of the Huffman algorithm, there are nontrivial $P$ for which known methods find a…

Information Theory · Computer Science 2016-11-17 Michael B. Baer

This paper addresses the challenges faced by algorithms, such as the Firefly Algorithm (FA) and the Genetic Algorithm (GA), in constrained optimization problems. While both algorithms perform well for unconstrained problems, their…

Neural and Evolutionary Computing · Computer Science 2025-01-28 Aswathi Malanthara , Ishaan R Kale

We consider maximization of stochastic monotone continuous submodular functions (CSF) with a diminishing return property. Existing algorithms only guarantee the performance \textit{in expectation}, and do not bound the probability of…

Data Structures and Algorithms · Computer Science 2023-03-22 Evan Becker , Jingdong Gao , Ted Zadouri , Baharan Mirzasoleiman

We give a pseudorandom generator that fools degree-$d$ polynomial threshold functions over $n$-dimensional Gaussian space with seed length $\mathrm{poly}(d)\cdot \log n$. All previous generators had a seed length with at least a $2^d$…

Computational Complexity · Computer Science 2022-02-10 Ryan O'Donnell , Rocco A. Servedio , Li-Yang Tan , Daniel Kane

Genetic algorithms are heuristic optimization techniques inspired by Darwinian evolution, which are characterized by successfully finding robust solutions for optimization problems. Here, we propose a subroutine-based quantum genetic…

Quantum Physics · Physics 2024-06-07 Rubén Ibarrondo , Giancarlo Gatti , Mikel Sanz

Universal induction relies on some general search procedure that is doomed to be inefficient. One possibility to achieve both generality and efficiency is to specialize this procedure w.r.t. any given narrow task. However, complete…

Neural and Evolutionary Computing · Computer Science 2018-09-13 Alexey Potapov , Sergey Rodionov

We examine two different ways of encoding a counting function, as a rational generating function and explicitly as a function (defined piecewise using the greatest integer function). We prove that, if the degree and number of input…

Combinatorics · Mathematics 2015-05-08 Sven Verdoolaege , Kevin Woods

We present an efficient deterministic algorithm which outputs exact expressions in terms of $n$ for the number of monic degree $n$ irreducible polynomials over $\mathbb{F}_{q}$ of characteristic $p$ for which the first $l < p$ coefficients…

Algebraic Geometry · Mathematics 2019-01-09 Robert Granger

Let $f, f_1, \ldots, f_\nV$ be polynomials with rational coefficients in the indeterminates $\bfX=X_1, \ldots, X_n$ of maximum degree $D$ and $V$ be the set of common complex solutions of $\F=(f_1,\ldots, f_\nV)$. We give an algorithm…

Symbolic Computation · Computer Science 2014-05-08 Aurélien Greuet , Mohab Safey El Din

Initial population plays an important role in heuristic algorithms such as GA as it help to decrease the time those algorithms need to achieve an acceptable result. Furthermore, it may influence the quality of the final answer given by…

Neural and Evolutionary Computing · Computer Science 2014-06-19 Erfan Khaji , Amin Satlikh Mohammadi

With the growth of image on the web, research on hashing which enables high-speed image retrieval has been actively studied. In recent years, various hashing methods based on deep neural networks have been proposed and achieved higher…

Computer Vision and Pattern Recognition · Computer Science 2019-05-23 Yosuke Kaga , Masakazu Fujio , Kenta Takahashi , Tetsushi Ohki , Masakatsu Nishigaki

Integration-by-parts reductions of Feynman integrals pose a frequent bottle-neck in state-of-the-art calculations in theoretical particle and gravitational-wave physics, and rely on heuristic approaches for selecting integration-by-parts…

High Energy Physics - Theory · Physics 2025-02-10 Matt von Hippel , Matthias Wilhelm

Feature selection problems have been extensively studied for linear estimation, for instance, Lasso, but less emphasis has been placed on feature selection for non-linear functions. In this study, we propose a method for feature selection…

Machine Learning · Computer Science 2020-07-28 Yutaro Yamada , Ofir Lindenbaum , Sahand Negahban , Yuval Kluger

Consider a subfield of the field of rational functions in several indeterminates. We present an algorithm that, given a set of generators of such a subfield, finds a simple generating set. We provide an implementation of the algorithm and…

Symbolic Computation · Computer Science 2026-03-06 Alexander Demin , Gleb Pogudin

Several new algorithms for deciding emptiness of Boolean combinations of regular languages and of languages of alternating automata (AFA) have been proposed recently, especially in the context of analysing regular expressions and in string…

Formal Languages and Automata Theory · Computer Science 2023-04-12 Tomáš Fiedor , Lukáš Holík , Martin Hruška , Adam Rogalewicz , Juraj Síč , Pavol Vargovčík

Recent years have demonstrated that using random feature maps can significantly decrease the training and testing times of kernel-based algorithms without significantly lowering their accuracy. Regrettably, because random features are…

Machine Learning · Computer Science 2015-04-08 Jiyan Yang , Alex Gittens

In this paper, we consider situations in which a given logical function is realized by a multithreshold threshold function. In such situations, constant functions can be easily obtained from multithreshold threshold functions, and…

Neural and Evolutionary Computing · Computer Science 2013-01-03 Yukihiro Kamada , Kiyonori Miyasaki