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Double machine learning is a statistical method for leveraging complex black-box models to construct approximately unbiased treatment effect estimates given observational data with high-dimensional covariates, under the assumption of a…

Machine Learning · Statistics 2022-06-03 Nitai Fingerhut , Matteo Sesia , Yaniv Romano

Mixup is a highly successful technique to improve generalization of neural networks by augmenting the training data with combinations of random pairs. Selective mixup is a family of methods that apply mixup to specific pairs, e.g. only…

Machine Learning · Computer Science 2023-06-06 Damien Teney , Jindong Wang , Ehsan Abbasnejad

Clustering is a widely used technique in data mining applications for discovering patterns in underlying data. Most traditional clustering algorithms are limited to handling datasets that contain either numeric or categorical attributes.…

Artificial Intelligence · Computer Science 2007-05-23 Zengyou He , Xiaofei Xu , Shengchun Deng

The last decade has seen a revolution in the theory and application of machine learning and pattern recognition. Through these advancements, variable ranking has emerged as an active and growing research area and it is now beginning to be…

Computer Vision and Pattern Recognition · Computer Science 2017-06-20 Giorgio Roffo

In this paper, we present several improvements in the parallelization of the in-place merge algorithm, which merges two contiguous sorted arrays into one with an O(T) space complexity (where T is the number of threads). The approach divides…

Distributed, Parallel, and Cluster Computing · Computer Science 2020-05-27 Berenger Bramas , Quentin Bramas

Many production-grade algorithms benefit from combining an asymptotically efficient algorithm for solving big problem instances, by splitting them into smaller ones, and an asymptotically inefficient algorithm with a very small…

Data Structures and Algorithms · Computer Science 2017-04-14 Margarita Markina , Maxim Buzdalov

A new fast algorithm for clustering and classification of large collections of text documents is introduced. The new algorithm employs the bipartite graph that realizes the word-document matrix of the collection. Namely, the modularity of…

Information Retrieval · Computer Science 2011-05-31 Grigory Pivovarov , Sergei Trunov

There has been surprisingly little work on algorithms for sorting strings on distributed-memory parallel machines. We develop efficient algorithms for this problem based on the multi-way merging principle. These algorithms inspect only…

Distributed, Parallel, and Cluster Computing · Computer Science 2020-01-24 Timo Bingmann , Peter Sanders , Matthias Schimek

Given a sequence of $n$ numbers and $k$ parallel First-in-First-Out (FIFO) queues, how close can one bring the sequence to sorted order? It is known that $k$ queues suffice to sort the sequence if the Longest Decreasing Subsequence (LDS) of…

Data Structures and Algorithms · Computer Science 2025-09-17 Andreas Karrenbauer , Kurt Mehlhorn , Pranabendu Misra , Paolo Luigi Rinaldi , Anna Twelsiek , Alireza Haqi , Siavash Rahimi Shateranloo

Sorting is a foundational problem in computer science that is typically employed on sequences or total orders. More recently, a more general form of sorting on partially ordered sets (or posets), where some pairs of elements are…

Data Structures and Algorithms · Computer Science 2022-06-03 Jishnu Roychoudhury , Jatin Yadav

Spike sorting plays an irreplaceable role in understanding brain codes. Traditional spike sorting technologies perform feature extraction and clustering separately after spikes are well detected. However, it may often cause many additional…

Signal Processing · Electrical Eng. & Systems 2020-11-23 Libo Huang , Lu Gan , Bingo Wing-Kuen Ling

Clustering is a fundamental analysis tool aiming at classifying data points into groups based on their similarity or distance. It has found successful applications in all natural and social sciences, including biology, physics, economics,…

Information Retrieval · Computer Science 2021-02-24 Wen-Bo Xie , Yan-Li Lee , Cong Wang , Duan-Bing Chen , Tao Zhou

In-place associative integer sorting technique was developed, improved and specialized for distinct integers. The technique is suitable for integer sorting. Hence, given a list S of n integers S[0...n-1], the technique sorts the integers in…

Data Structures and Algorithms · Computer Science 2012-10-08 A. Emre Cetin

In this paper, we present a framework based on a simple data structure and parameterized algorithms for the problems of finding items in an unsorted list of linearly ordered items based on their rank (selection) or value (search). As a…

Data Structures and Algorithms · Computer Science 2009-09-30 Ankur Gupta , Anna Kispert , Jonathan P. Sorenson

Several algorithms have been developed over the years to perform join operation which is executed frequently and affects the efficiency of the database system. Some of these efforts prove that join performance mainly depends on the…

Databases · Computer Science 2022-03-24 Norah Asiri , Rasha Alsulim

Sorting is an essential operation which is widely used and is fundamental to some very basic day to day utilities like searches, databases, social networks and much more. Optimizing this basic operation in terms of complexity as well as…

Data Structures and Algorithms · Computer Science 2021-07-06 Peeyush Kumar , Ayushe Gangal , Sunita Kumari , Sunita Tiwari

In this master thesis we analyze the complexity of sorting a set of strings. It was shown that the complexity of sorting strings can be naturally expressed in terms of the prefix trie induced by the set of strings. The model of computation…

Data Structures and Algorithms · Computer Science 2014-08-26 Igor Stassiy

A sorted set (or map) is one of the most used data types in computer science. In addition to standard set operations, like Insert, Remove, and Contains, it can provide set-set operations such as Union,Intersection, and Difference. Each of…

Distributed, Parallel, and Cluster Computing · Computer Science 2023-06-27 Ilya Kokorin , Vitaly Aksenov , Alena Martsenyuk

Purpose: Simulation-based digital twins represent an effort to provide high-accuracy real-time insights into operational physical processes. However, the computation time of many multi-physical simulation models is far from real-time. It…

Computational Engineering, Finance, and Science · Computer Science 2024-07-08 Maximilian Kannapinn , Michael Schäfer , Oliver Weeger

Sorting is one of the most basic algorithms, and developing highly parallel sorting programs is becoming increasingly important in high-performance computing because the number of CPU cores per node in modern supercomputers tends to…

Distributed, Parallel, and Cluster Computing · Computer Science 2023-09-08 Tomoyuki Tokuue , Tomoaki Ishiyama