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The article presents a study of the Particle Swarm optimization method for scheduling problem. To improve the method's performance a restriction of particles' velocity and an evolutionary meta-optimization were realized. The approach…

Neural and Evolutionary Computing · Computer Science 2020-06-22 Pavel Matrenin , Viktor Sekaev

We have preliminary results on the parallelization of a Tree-Code for evaluating gravitational forces in N-body astrophysical systems. For our Cray T3D/CRAFT implementation, we have obtained an encouraging speed-up behavior, which reaches a…

Astrophysics · Physics 2007-05-23 R. Capuzzo-Dolcetta , P. Miocchi

The performance and accuracy of a GRAPE-3 system for collisionless N-body simulations is discussed. After a description of the hardware configurations available to us at Marseille, and the usefulness of on-line analysis, we concentrate on…

Astrophysics · Physics 2009-10-30 E. Athanassoula , A. Bosma , J. -C. Lambert , J. Makino

The induction of additional randomness in parallel and sequential ensemble methods has proven to be worthwhile in many aspects. In this manuscript, we propose and examine a novel random tree depth injection approach suitable for sequential…

Machine Learning · Statistics 2020-09-15 Tobias Markus Krabel , Thi Ngoc Tien Tran , Andreas Groll , Daniel Horn , Carsten Jentsch

This paper investigates the execution of tree-shaped task graphs using multiple processors. Each edge of such a tree represents some large data. A task can only be executed if all input and output data fit into memory, and a data can only…

Distributed, Parallel, and Cluster Computing · Computer Science 2014-10-02 Lionel Eyraud-Dubois , Loris Marchal , Oliver Sinnen , Frédéric Vivien

In particle simulations, the weights of particles determine how many physical particles they represent. Adaptively adjusting these weights can greatly improve the efficiency of the simulation, without creating severe nonphysical artifacts.…

Computational Physics · Physics 2014-11-05 Jannis Teunissen , Ute Ebert

{\em Reoptimization} is a setting in which we are given an (near) optimal solution of a problem instance and a local modification that slightly changes the instance. The main goal is that of finding an (near) optimal solution of the…

Data Structures and Algorithms · Computer Science 2018-05-01 Davide Bilò

Traditional algorithms for detecting differences in source code focus on differences between lines. As such, little can be learned about abstract changes that occur over time within a project. Structural differencing on the program's…

Software Engineering · Computer Science 2013-07-09 Jason Dagit , Matthew Sottile

In this paper, we review hyperparameter optimization methods for machine learning models, with a particular focus on the Adaptive Tree-Structured Parzen Estimator (ATPE) algorithm. We propose several modifications to ATPE and assess their…

Machine Learning · Computer Science 2025-02-04 Szymon Sieradzki , Jacek Mańdziuk

We consider the coordinated vehicle platooning problem on a tree network with time constraints while the routes of vehicles are given. The problem is to coordinate the departure time of each vehicle to enable platoon formation hence…

Optimization and Control · Mathematics 2024-11-25 Fengqiao Luo

We give an algorithm to enumerate the results on trees of monadic second-order (MSO) queries represented by nondeterministic tree automata. After linear time preprocessing (in the input tree), we can enumerate answers with linear delay (in…

Databases · Computer Science 2019-08-28 Antoine Amarilli , Pierre Bourhis , Stefan Mengel , Matthias Niewerth

In this letter we describe the pseudoparticle multipole method (P2M2), a new method to express multipole expansion by a distribution of pseudoparticles. We can use this distribution of particles to calculate high order terms in both the…

Astrophysics · Physics 2009-10-31 Atsushi Kawai , Junichiro Makino

Probabilistic programming languages and other machine learning applications often require samples to be generated from a categorical distribution where the probability of each one of $n$ categories is specified as a parameter. If the…

Data Structures and Algorithms · Computer Science 2019-06-28 Daniel Tang

Coded distributed computing has been considered as a promising technique which makes large-scale systems robust to the "straggler" workers. Yet, practical system models for distributed computing have not been available that reflect the…

Information Theory · Computer Science 2019-01-17 Muah Kim , Jy-yong Sohn , Jaekyun Moon

In online video platforms, accurate watch time prediction has become a fundamental and challenging problem in video recommendation. Previous research has revealed that the accuracy of watch time prediction highly depends on both the…

Information Retrieval · Computer Science 2025-08-26 Xiaokai Chen , Xiao Lin , Changcheng Li , Peng Jiang

Performance analysis has always been an afterthought during the application development process, focusing on application correctness first. The learning curve of the existing static and dynamic analysis tools are steep, which requires…

Machine Learning · Computer Science 2021-04-23 Nathan Pinnow , Tarek Ramadan , Tanzima Z. Islam , Chase Phelps , Jayaraman J. Thiagarajan

The method of choice for integrating the equations of motion of the general N-body problem has been to use an individual time step scheme. For the sake of efficiency, block time steps have been the most popular, where all time step sizes…

Astrophysics · Physics 2009-11-11 Junichiro Makino , Piet Hut , Murat Kaplan , Hasan Saygin

Counterfactual explanations are usually generated through heuristics that are sensitive to the search's initial conditions. The absence of guarantees of performance and robustness hinders trustworthiness. In this paper, we take a…

Machine Learning · Computer Science 2021-06-28 Axel Parmentier , Thibaut Vidal

Classifier evasion consists in finding for a given instance $x$ the nearest instance $x'$ such that the classifier predictions of $x$ and $x'$ are different. We present two novel algorithms for systematically computing evasions for tree…

Machine Learning · Computer Science 2016-05-30 Alex Kantchelian , J. D. Tygar , Anthony D. Joseph

The analysis of source code through machine learning techniques is an increasingly explored research topic aiming at increasing smartness in the software toolchain to exploit modern architectures in the best possible way. In the case of…

Machine Learning · Computer Science 2020-12-15 Emanuele Parisi , Francesco Barchi , Andrea Bartolini , Giuseppe Tagliavini , Andrea Acquaviva
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