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Our goal is to provide a review of deep learning methods which provide insight into structured high-dimensional data. Rather than using shallow additive architectures common to most statistical models, deep learning uses layers of…

Machine Learning · Statistics 2023-10-11 Nick Polson , Vadim Sokolov

We propose a general dual ascent framework for Lagrangean decomposition of combinatorial problems. Although methods of this type have shown their efficiency for a number of problems, so far there was no general algorithm applicable to…

Data Structures and Algorithms · Computer Science 2017-01-13 Paul Swoboda , Jan Kuske , Bogdan Savchynskyy

Neural networks are commonly used as models for classification for a wide variety of tasks. Typically, a learned affine transformation is placed at the end of such models, yielding a per-class value used for classification. This classifier…

Machine Learning · Computer Science 2018-03-21 Elad Hoffer , Itay Hubara , Daniel Soudry

Anti-unification refers to the process of generalizing two (or more) goals into a single, more general, goal that captures some of the structure that is common to all initial goals. In general one is typically interested in computing what…

Logic in Computer Science · Computer Science 2020-02-19 Gonzague Yernaux , Wim Vanhoof

We investigate commutator operations on compatible uniformities of an algebra. We present a commutator operation for compatible uniformities of an algebra in a congruence-modular variety which extends the commutator on congruences, and…

Rings and Algebras · Mathematics 2007-05-23 William H. Rowan

This paper is dedicated to the fused trend filtering on a general graph, which is a combination of fused estimator and 1-st order trend filtering on a graph. There are two cases of fusion regularisers studied in this work: anisotropic total…

Statistics Theory · Mathematics 2024-01-11 Vladimir Pastukhov

A unified approach to derive optimal finite differences is presented which combines three critical elements for numerical performance especially for multi-scale physical problems, namely, order of accuracy, spectral resolution and…

Computational Physics · Physics 2019-10-23 Komal Kumari , Raktim Bhattacharya , Diego A. Donzis

In this article we will analyse how to compute the contribution of each input value to its aggregate output in some nonlinear models. Regression and classification applications, together with related algorithms for deep neural networks are…

Machine Learning · Computer Science 2022-07-26 Cosimo Izzo

Probabilistic mixture models have been widely used for different machine learning and pattern recognition tasks such as clustering, dimensionality reduction, and classification. In this paper, we focus on trying to solve the most common…

Machine Learning · Computer Science 2020-04-08 Gustavo A Valencia-Zapata , Daniel Mejia , Gerhard Klimeck , Michael Zentner , Okan Ersoy

An equivalence relation in the set of all square binary matrices is described in this work. It is discussed a combinatoric problem about finding the cardinal number and the elements of the factor set according to this relation. We examine…

Representation Theory · Mathematics 2012-01-09 Krasimir Yordzhev , Hristina Kostadinova

We present a generalization of first-order unification to a term algebra where variable indexing is part of the object language. We exploit variable indexing by associating some sequences of variables ($X_0,\ X_1,\ X_2,\dots$) with a…

Logic in Computer Science · Computer Science 2024-03-12 David M. Cerna

We introduce a unified framework for the study of multilevel mixed integer linear optimization problems and multistage stochastic mixed integer linear optimization problems with recourse. The framework highlights the common mathematical…

Optimization and Control · Mathematics 2021-04-20 Suresh Bolusani , Stefano Coniglio , Ted. K. Ralphs , Sahar Tahernejad

We propose new linear combinations of compositions of a basic second-order scheme with appropriately chosen coefficients to construct higher order numerical integrators for differential equations. They can be considered as a generalization…

Numerical Analysis · Mathematics 2024-04-25 Sergio Blanes , Fernando Casas , Luke Shaw

We show how (well-established) type systems based on non-idempotent intersection types can be extended to characterize termination properties of functional programming languages with pattern matching features. To model such programming…

Programming Languages · Computer Science 2024-08-21 Sandra Alves , Delia Kesner , Miguel Ramos

We extend the homological method of quantization of generalized Drinfeld--Sokolov reductions to affine superalgebras. This leads, in particular, to a unified representation theory of superconformal algebras.

Mathematical Physics · Physics 2014-01-17 Victor G. Kac , Shi-shyr Roan , Minoru Wakimoto

Let $\C$ be a sequence of multisets of subspaces of a vector space $\F_q^k$. We describe a practical algorithm which computes a canonical form and the stabilizer of $\C$ under the group action of the general semilinear group. It allows us…

Information Theory · Computer Science 2013-05-07 Thomas Feulner

We devise a unified framework for the design of canonization algorithms. Using hereditarily finite sets, we define a general notion of combinatorial objects that includes graphs, hypergraphs, relational structures, codes, permutation…

Data Structures and Algorithms · Computer Science 2019-04-09 Pascal Schweitzer , Daniel Wiebking

We describe all weights which are appropriated for the unitarization of linear representations of primitive partially ordered sets of finite type.

Representation Theory · Mathematics 2010-06-16 Roman Grushevoy , Kostyantyn Yusenko

The algebraic intersection type unification problem is an important component in proof search related to several natural decision problems in intersection type systems. It is unknown and remains open whether the algebraic intersection type…

Logic in Computer Science · Computer Science 2023-06-22 Andrej Dudenhefner , Moritz Martens , Jakob Rehof

We use recent results on algorithms for Markov decision problems to show that a canonical form for a generalized P-matrix can be computed, in some important cases, by a strongly polynomial algorithm.

Optimization and Control · Mathematics 2012-05-01 Walter D. Morris