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Traceability, the ability to trace relevant software artifacts to support reasoning about the quality of the software and its development process, plays a crucial role in requirements and software engineering, particularly for…

Software Engineering · Computer Science 2024-05-20 Jin L. C. Guo , Jan-Philipp Steghöfer , Andreas Vogelsang , Jane Cleland-Huang

Provenance is information about the origin, derivation, ownership, or history of an object. It has recently been studied extensively in scientific databases and other settings due to its importance in helping scientists judge data validity,…

Programming Languages · Computer Science 2008-12-03 James Cheney , Umut Acar , Amal Ahmed

Number sequences defined by a linear recursion relation are studied by means of generating functions. Indices of the terms in the recursion relation have arbitrary differenses. In addition to formulas for the nth term an algorithm is…

Number Theory · Mathematics 2016-04-04 Bengt Månsson

We review elementary properties of random matrices and discuss widely used mathematical methods for both hermitian and nonhermitian random matrix ensembles. Applications to a wide range of physics problems are summarized. This paper…

High Energy Physics - Phenomenology · Physics 2007-05-23 M. A. Stephanov , J. J. M. Verbaarschot , T. Wettig

This tutorial introduces a new and powerful set of techniques variously called "neural machine translation" or "neural sequence-to-sequence models". These techniques have been used in a number of tasks regarding the handling of human…

Computation and Language · Computer Science 2017-03-07 Graham Neubig

Neural codes are collections of binary strings motivated by patterns of neural activity. In this paper, we study algorithmic and enumerative aspects of convex neural codes in dimension 1 (i.e. on a line or a circle). We use the theory of…

Combinatorics · Mathematics 2017-02-23 Zvi Rosen , Yan X. Zhang

I start by reviewing some basic properties of random graphs. I then consider the role of random walks in complex networks and show how they may be used to explain why so many long tailed distributions are found in real data sets. The key…

Statistical Mechanics · Physics 2012-12-11 T. S. Evans

Reservoir Computing Networks (RCNs) belong to a group of machine learning techniques that project the input space non-linearly into a high-dimensional feature space, where the underlying task can be solved linearly. Popular variants of RCNs…

Machine Learning · Computer Science 2022-05-31 Peter Steiner , Azarakhsh Jalalvand , Simon Stone , Peter Birkholz

A classical knot is described by a one-stroke trajectory with entanglements of a string. The replica method appears as a powerful tool in statistical mechanics for a polymer or self-avoiding walk. We consider this replica N to 0 limit in…

Mathematical Physics · Physics 2023-03-09 Shinobu Hikami

There is increasing interest within the research community in the design and use of recursive probability models. Although there still remains concern about computational complexity costs and the fact that computing exact solutions can be…

Artificial Intelligence · Computer Science 2013-01-14 Daniel Pless , George Luger

We desribe how we extend R with an external C++ code library by using the Rcpp package. Our working example uses the recent machine learning library and application 'Corels' providing optimal yet easily interpretable rule lists…

Computation · Statistics 2019-11-18 Dirk Eddelbuettel

Large matrices arise in many machine learning and data analysis applications, including as representations of datasets, graphs, model weights, and first and second-order derivatives. Randomized Numerical Linear Algebra (RandNLA) is an area…

Machine Learning · Computer Science 2024-06-21 Michał Dereziński , Michael W. Mahoney

The meaning of a sentence is a function of the relations that hold between its words. We instantiate this relational view of semantics in a series of neural models based on variants of relation networks (RNs) which represent a set of…

Computation and Language · Computer Science 2018-11-27 Lei Yu , Cyprien de Masson d'Autume , Chris Dyer , Phil Blunsom , Lingpeng Kong , Wang Ling

This paper proposes a framework dedicated to the construction of what we call discrete elastic inner product allowing one to embed sets of non-uniformly sampled multivariate time series or sequences of varying lengths into inner product…

Machine Learning · Computer Science 2012-06-28 Pierre-François Marteau , Nicolas Bonnel , Gilbas Ménier

Computing modular coincidences can show whether a given substitution system, which is supported on a point lattice in R^d, consists of model sets or not. We prove the computatibility of this problem and determine an upper bound for the…

Metric Geometry · Mathematics 2008-03-11 D. Frettlöh , B. Sing

We define generalized de Bruijn words as those words having a Burrows-Wheeler transform that is a concatenation of permutations of the alphabet. We show that generalized de Bruijn words are in 1-to-1 correspondence with Hamiltonian cycles…

Combinatorics · Mathematics 2025-07-30 Gabriele Fici , Estéban Gabory

Recurrent Neural Networks (RNNs) with attention mechanisms have obtained state-of-the-art results for many sequence processing tasks. Most of these models use a simple form of encoder with attention that looks over the entire sequence and…

Graphs are used in many disciplines to model the relationships that exist between objects in a complex discrete system. Researchers may wish to compare a network of interest to a "typical" graph from a family (or ensemble) of graphs which…

Combinatorics · Mathematics 2025-08-08 Catherine Greenhill

Riddles are concise linguistic puzzles that describe an object or idea through indirect, figurative, or playful clues. They are a longstanding form of creative expression, requiring the solver to interpret hints, recognize patterns, and…

Computation and Language · Computer Science 2026-01-28 Niharika Sri Parasa , Chaitali Diwan , Srinath Srinivasa

Matrices are two-dimensional data structures allowing one to conceptually organize information. For example, adjacency matrices are useful to store the links of a network; correlation matrices are simple ways to arrange gene co-expression…

Disordered Systems and Neural Networks · Physics 2022-09-29 Flaviano Morone
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