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Transfer Learning is an area of statistics and machine learning research that seeks answers to the following question: how do we build successful learning algorithms when the data available for training our model is qualitatively different…

Machine Learning · Computer Science 2022-11-09 Brandon Tse Wei Chow

I present the Automated Line Fitting Algorithm, ALFA, a new code which can fit emission line spectra of arbitrary wavelength coverage and resolution, fully automatically. In contrast to traditional emission line fitting methods which…

Solar and Stellar Astrophysics · Physics 2016-01-20 Roger Wesson

Supercomputers worldwide provide the necessary infrastructure for groundbreaking research. However, most supercomputers are not designed equally due to different desired figure of merit, which is derived from the computational bounds of the…

Distributed, Parallel, and Cluster Computing · Computer Science 2022-09-07 Re'em Harel , Matan Rusanovsky , Ron Wagner , Harel Levin , Gal Oren

We propose a method for adaptive nonlinear sequential modeling of vector-time series data. Data is modeled as a nonlinear function of past values corrupted by noise, and the underlying non-linear function is assumed to be approximately…

Methodology · Statistics 2017-10-11 Qiuyi Han , Jie Ding , Edoardo Airoldi , Vahid Tarokh

Tasks in the aerospace industry heavily rely on searching and reusing large volumes of technical documents, yet there is no public information retrieval (IR) benchmark that reflects the terminology- and query-intent characteristics of this…

Information Retrieval · Computer Science 2026-01-08 Bongmin Kim

This document is an introduction to the Matlab package SDLS (Semi-Definite Least-Squares) for solving least-squares problems over convex symmetric cones. The package is shortly presented through the addressed problem, a sketch of the…

Optimization and Control · Mathematics 2007-09-18 Didier Henrion , Jerome Malick

The purpose of this report is in examining the generalization performance of Support Vector Machines (SVM) as a tool for pattern recognition and object classification. The work is motivated by the growing popularity of the method that is…

Machine Learning · Computer Science 2014-12-16 Eugene Borovikov

This paper studies complexity of recognition of classes of bounded configurations by a generalization of conventional cellular automata (CA) -- finite dynamic cellular automata (FDCA). Inspired by the CA-based models of biological and…

Computational Complexity · Computer Science 2007-05-23 Maxim Makatchev

Program understanding is an important aspect in Software Maintenance and Reengineering. Understanding the program is related to execution behaviour and relationship of variable involved in the program. The task of finding all statements in…

Software Engineering · Computer Science 2011-08-08 N. Sasirekha , A. Edwin Robert , Dr. M. Hemalatha

The polynomial spline collocation method is proposed for solution of Volterra integral equations of the first kind with special piecewise continuous kernels. The Gauss-type quadrature formula is used to approximate integrals during the…

Numerical Analysis · Mathematics 2021-11-24 A. Tynda , S. Noeiaghdam , D. Sidorov

The paper reports on a computer algebra program LSSS (Linear Selective Systems Solver) for solving linear algebraic systems with rational coefficients. The program is especially efficient for very large sparse systems that have a solution…

Symbolic Computation · Computer Science 2011-09-14 Thomas Wolf , Eberhard Schruefer , Kenneth Webster

This paper presents a classification of Cellular Automata rules based on its properties at the nth iteration. Elaborate computer program has been designed to get the nth iteration for arbitrary 1-D or 2-D CA rules. Studies indicate that the…

Computing the theta series of an arbitrary lattice, and more specifically a related quantity known as the flatness factor, has been recently shown to be important for lattice code design in various wireless communication setups. However,…

Information Theory · Computer Science 2020-06-23 Amaro Barreal , Mohamed Taoufiq Damir , Ragnar Freij-Hollanti , Camilla Hollanti

We propose a novel neural network architecture for visual saliency detections, which utilizes neurophysiologically plausible mechanisms for extraction of salient regions. The model has been significantly inspired by recent findings from…

Computer Vision and Pattern Recognition · Computer Science 2015-04-13 Natalia Efremova , Sergey Tarasenko

Choosing a shrinkage method can be done by selecting a penalty from a list of pre-specified penalties or by constructing a penalty based on the data. If a list of penalties for a class of linear models is given, we provide comparisons based…

Methodology · Statistics 2022-01-10 Dean Dustin , Bertrand Clarke , Jennifer Clarke

The cylindrical algebraic decomposition (CAD) is the only complete method used in practice for solving problems like quantifier elimination or SMT solving related to real algebra, despite its doubly exponential complexity. Recent…

In this paper a method is proposed which uses data mining techniques based on rough sets theory to select neighborhood and determine update rule for cellular automata (CA). According to the proposed approach, neighborhood is detected by…

Artificial Intelligence · Computer Science 2014-09-24 Bartlomiej Placzek

In many global Optimization Problems, it is required to evaluate a global point (min or max) in large space that calculation effort is very high. In this paper is presented new approach for optimization problem with subdivision labeling…

Neural and Evolutionary Computing · Computer Science 2013-07-24 Masoumeh Vali

Training Large Language Models (LLMs) from scratch requires immense computational resources, making it prohibitively expensive. Model scaling-up offers a promising solution by leveraging the parameters of smaller models to create larger…

Machine Learning · Computer Science 2025-02-20 Yifei Yang , Zouying Cao , Xinbei Ma , Yao Yao , Libo Qin , Zhi Chen , Hai Zhao

Linear temporal logic (LTL) is a specification language for finite sequences (called traces) widely used in program verification, motion planning in robotics, process mining, and many other areas. We consider the problem of learning LTL…

Artificial Intelligence · Computer Science 2026-01-22 Ritam Raha , Rajarshi Roy , Nathanaël Fijalkow , Daniel Neider