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Related papers: Decomposition Complexity

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Reasoning with defeasible and conflicting knowledge in an argumentative form is a key research field in computational argumentation. Reasoning under various forms of uncertainty is both a key feature and a challenging barrier for automated…

Artificial Intelligence · Computer Science 2024-07-09 Andrei Popescu , Johannes P. Wallner

The functional decomposition of polynomials has been a topic of great interest and importance in pure and computer algebra and their applications. The structure of compositions of (suitably normalized) polynomials f=g(h) over finite fields…

Commutative Algebra · Mathematics 2010-05-11 Joachim von zur Gathen , Mark Giesbrecht , Konstantin Ziegler

This paper addresses the decomposition of biochemical networks into functional modules that preserve their dynamic properties upon interconnection with other modules, which permits the inference of network behavior from the properties of…

Molecular Networks · Quantitative Biology 2014-12-03 Hari Sivakumar , Stephen R. Proulx , João P. Hespanha

Nonparametric extension of tensor regression is proposed. Nonlinearity in a high-dimensional tensor space is broken into simple local functions by incorporating low-rank tensor decomposition. Compared to naive nonparametric approaches, our…

Machine Learning · Statistics 2016-03-09 Masaaki Imaizumi , Kohei Hayashi

We consider a general concept of composition and decomposition of objects, and discuss a few natural properties one may expect from a reasonable choice thereof. It will be demonstrated how this leads to multiplication and co- multiplication…

Combinatorics · Mathematics 2010-08-30 P. Blasiak

In this survey we discuss the notion of combinatorial interpretation in the context of Algebraic Combinatorics and related areas. We approach the subject from the Computational Complexity perspective. We review many examples, state a…

Combinatorics · Mathematics 2022-09-14 Igor Pak

One of the main issues in computing a tensor decomposition is how to choose the number of rank-one components, since there is no finite algorithms for determining the rank of a tensor. A commonly used approach for this purpose is to find a…

Computer Vision and Pattern Recognition · Computer Science 2023-09-15 Claudio Turchetti

We introduce and analyze the problem of the compilation of decision models from a decision-theoretic perspective. The techniques described allow us to evaluate various configurations of compiled knowledge given the nature of evidential…

Artificial Intelligence · Computer Science 2013-04-08 David Heckerman , John S. Breese , Eric J. Horvitz

This paper investigates the problem of decomposition with respect to outputs for Boolean control networks (BCNs). First, with the linear expression of BCNs and the matrix semi-tensor product, some algebraic equivalent conditions for the…

Optimization and Control · Mathematics 2014-07-09 Yunlei Zou , Jiandong Zhu

The tensor decomposition addressed in this paper may be seen as a generalisation of Singular Value Decomposition of matrices. We consider general multilinear and multihomogeneous tensors. We show how to reduce the problem to a truncated…

Algebraic Geometry · Mathematics 2012-10-17 Alessandra Bernardi , Jerome Brachat , Pierre Comon , Bernard Mourrain

We give algorithms to compute decompositions of a given polynomial, or more generally mixed tensor, as sum of rank one tensors, and to establish whether such a decomposition is unique. In particular, we present methods to compute the…

Algebraic Geometry · Mathematics 2021-07-12 Antonio Laface , Alex Massarenti , Rick Rischter

We survey an abstract theory of connectivity, based on symmetric submodular set functions. We start by developing Robertson and Seymour's fundamental duality between branch decompositions (related to the better-known tree decompositions)…

Discrete Mathematics · Computer Science 2016-05-24 Martin Grohe

Tensor decomposition is an important technique for capturing the high-order interactions among multiway data. Multi-linear tensor composition methods, such as the Tucker decomposition and the CANDECOMP/PARAFAC (CP), assume that the complex…

Machine Learning · Statistics 2016-11-04 Bin Liu , Zenglin Xu , Yingming Li

The paper introduces two new aggregation functions to encode structural knowledge from tree-structured data. They leverage the Canonical and Tensor-Train decompositions to yield expressive context aggregation while limiting the number of…

Machine Learning · Computer Science 2020-08-14 Daniele Castellana , Davide Bacciu

Compositionality is thought to be a key component of language, and various compositional benchmarks have been developed to empirically probe the compositional generalization of existing sequence processing models. These benchmarks often…

Machine Learning · Computer Science 2024-05-07 Parikshit Ram , Tim Klinger , Alexander G. Gray

This paper studies the problem of reconstructing binary matrices that are only accessible through few evaluations of their discrete X-rays. Such question is prominently motivated by the demand in material science for developing a tool for…

Combinatorics · Mathematics 2007-05-23 Alberto Del Lungo , Andrea Frosini , Maurice Nivat , Laurent Vuillon

Several theorems and conjectures in communication complexity state or speculate that the complexity of a matrix in a given communication model is controlled by a related analytic or algebraic matrix parameter, e.g., rank, sign-rank,…

Computational Complexity · Computer Science 2024-01-29 Hamed Hatami , Pooya Hatami

Given a reference computer, Kolmogorov complexity is a well defined function on all binary strings. In the standard approach, however, only the asymptotic properties of such functions are considered because they do not depend on the…

Machine Learning · Computer Science 2007-05-23 Andrei N. Soklakov

Basic problems of complex systems are outlined with an emphasis on irreducibility and dynamic many-to-many correspondences. We discuss the importance of a constructive approach to artificial reality and the significance of an internal…

adap-org · Physics 2009-10-22 Kunihiko Kaneko , Ichiro Tsuda

Modern program verifiers use logic-based encodings of the verification problem that are discharged by a back end reasoning engine. However, instances of such encodings for large programs can quickly overwhelm these back end solvers. Hence,…

Logic in Computer Science · Computer Science 2016-07-18 Peter Schrammel