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For high dimensional data, where P features for N objects (P >> N) are represented in an NxP matrix X, we describe a clustering algorithm based on the normalized left Gram matrix, G = XX'/P. Under certain regularity conditions, the rows in…

Machine Learning · Statistics 2022-02-17 Shahina Rahman , Valen E. Johnson , Suhasini Subba Rao

Equivalence testing, a fundamental problem in the field of distribution testing, seeks to infer if two unknown distributions on $[n]$ are the same or far apart in the total variation distance. Conditional sampling has emerged as a powerful…

Data Structures and Algorithms · Computer Science 2024-03-08 Diptarka Chakraborty , Sourav Chakraborty , Gunjan Kumar , Kuldeep S. Meel

This article introduces an adaptive sorting algorithm that can relocate elements accurately by substituting their values into a function which we name it the guessing function. We focus on building this function which is the mapping…

Data Structures and Algorithms · Computer Science 2007-05-23 Sheng Bao , De-Shun Zheng

Fix a finite group $G$. We study the computational complexity of counting problems of the following flavor: given a group $\Gamma$, count the number of homomorphisms $\Gamma \to G$. Our first result establishes that this problem is…

Group Theory · Mathematics 2026-04-22 Eric Samperton , Armin Weiß

As the scope of machine learning broadens, we observe a recurring theme of algorithmic monoculture: the same systems, or systems that share components (e.g. training data), are deployed by multiple decision-makers. While sharing offers…

Machine Learning · Computer Science 2022-11-28 Rishi Bommasani , Kathleen A. Creel , Ananya Kumar , Dan Jurafsky , Percy Liang

This paper defines the notion of analogical dissimilarity between four objects, with a special focus on objects structured as sequences. Firstly, it studies the case where the four objects have a null analogical dissimilarity, i.e. are in…

Machine Learning · Computer Science 2014-01-16 Laurent Miclet , Sabri Bayoudh , Arnaud Delhay

We consider deterministic and {\em randomized} quantum algorithms simulating $e^{-iHt}$ by a product of unitary operators $e^{-iA_jt_j}$, $j=1,...,N$, where $A_j\in\{H_1,...,H_m\}$, $H=\sum_{i=1}^m H_i$ and $t_j > 0$ for every $j$.…

Quantum Physics · Physics 2009-10-22 Chi Zhang

We present several new examples of speed-ups obtainable by quantum algorithms in the context of property testing. First, motivated by sampling algorithms, we consider probability distributions given in the form of an oracle $f:[n]\to[m]$.…

Quantum Physics · Physics 2010-05-13 Sourav Chakraborty , Eldar Fischer , Arie Matsliah , Ronald de Wolf

Compared with constraint satisfaction problems, counting problems have received less attention. In this paper, we survey research works on the problems of counting the number of solutions to constraints. The constraints may take various…

Artificial Intelligence · Computer Science 2020-12-29 Jian Zhang , Cunjing Ge , Feifei Ma

Homomorphism is a key mapping technique between graphs that preserves their structure. Given a graph and a pattern, the subgraph homomorphism problem involves finding a mapping from the pattern to the graph, ensuring that adjacent vertices…

Artificial Intelligence · Computer Science 2025-12-18 Shuyang Guo , Wenjin Xie , Ping Lu , Ting Deng , Richong Zhang , Jianxin Li , Xiangping Huang , Zhongyi Liu

Genetic algorithms are considered as an original way to solve problems, probably because of their generality and of their "blind" nature. But GAs are also unusual since the features of many implementations (among all that could be thought…

Artificial Intelligence · Computer Science 2011-08-24 Jean-Louis Dessalles

Given a loop or more generally 1-cycle $r$ of size L on a closed two-dimensional manifold or surface, represented by a triangulated mesh, a question in computational topology asks whether or not it is homologous to zero. We frame and tackle…

Quantum Physics · Physics 2023-07-26 Nhat A. Nghiem , Xianfeng David Gu , Tzu-Chieh Wei

We consider a refinement of the partition function of graph homomorphisms and present a quasi-polynomial algorithm to compute it in a certain domain. As a corollary, we obtain quasi-polynomial algorithms for computing partition functions…

Combinatorics · Mathematics 2015-08-04 Alexander Barvinok , Pablo Soberón

Homomorphic encryption is a powerful cryptographic tool that enables secure computations on the private data. It evaluates any function for any operation securely on the encrypted data without knowing its corresponding plaintext. For…

Cryptography and Security · Computer Science 2025-09-18 Giovanni Giuseppe Grimaldi

We study the problem of fairly allocating $m$ indivisible goods to $n$ agents, where agents may have different preferences over the goods. In the traditional setting, agents' valuations are provided as inputs to the algorithm. In this…

Computer Science and Game Theory · Computer Science 2025-08-05 Xiaolin Bu , Zihao Li , Shengxin Liu , Jiaxin Song , Biaoshuai Tao

Experimental comparisons of performance represent an important aspect of research on optimization algorithms. In this work we present a methodology for defining the required sample sizes for designing experiments with desired statistical…

Neural and Evolutionary Computing · Computer Science 2018-10-16 Felipe Campelo , Fernanda Takahashi

This paper introduces a novel quantum algorithm that is able to classify a hierarchy of classes of imbalanced Boolean functions. The fundamental characteristic of imbalanced Boolean functions is that the proportion of elements in their…

One of the most basic computational problems is the task of finding a desired item in an ordered list of N items. While the best classical algorithm for this problem uses log_2 N queries to the list, a quantum computer can solve the problem…

Quantum Physics · Physics 2007-05-23 Andrew M. Childs , Andrew J. Landahl , Pablo A. Parrilo

This paper describes an algorithm for the computation of FIRST and FOLLOW sets for use with feature-theoretic grammars in which the value of the sets consists of pairs of feature-theoretic categories. The algorithm preserves as much…

cmp-lg · Computer Science 2008-02-03 Arturo Trujillo

Hyperparameters play a critical role in machine learning. Hyperparameter tuning can make the difference between state-of-the-art and poor prediction performance for any algorithm, but it is particularly challenging for structure learning…

Machine Learning · Computer Science 2024-02-21 Damian Machlanski , Spyridon Samothrakis , Paul Clarke