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In what follows, we pose two general conjectures about decompositions of homogeneous polynomials as sums of powers. The first one (suggested by G. Ottaviani) deals with the generic k-rank of complex-valued forms of any degree divisible by k…

Algebraic Geometry · Mathematics 2019-02-07 Samuel Lundqvist , Alessandro Oneto , Bruce Reznick , Boris Shapiro

In this paper, we investigate the relative power of several conjectures that attracted recently lot of interest. We establish a connection between the Network Coding Conjecture (NCC) of Li and Li and several data structure like problems…

Computational Complexity · Computer Science 2021-02-19 Pavel Dvořák , Michal Koucký , Karel Král , Veronika Slívová

Rank-constrained optimization problems have received an increasing intensity of interest recently, because many optimization problems in communications and signal processing applications can be cast into a rank-constrained optimization…

Information Theory · Computer Science 2015-05-20 Hao Yu , Vincent K. N. Lau

We study several variants of decomposing a symmetric matrix into a sum of a low-rank positive semidefinite matrix and a diagonal matrix. Such decompositions have applications in factor analysis and they have been studied for many decades.…

Optimization and Control · Mathematics 2023-10-02 Levent Tunçel , Stephen A. Vavasis , Jingye Xu

We consider the problem of exact low-rank matrix completion from a geometric viewpoint: given a partially filled matrix M, we keep the positions of specified and unspecified entries fixed, and study how the minimal completion rank depends…

Statistics Theory · Mathematics 2019-09-24 Daniel Irving Bernstein , Grigoriy Blekherman , Rainer Sinn

The problem of determining whether a probabilistic program terminates almost surely (i.e.~with probability one) is undecidable, and actually $\Pi^0_2$-complete. For this reason, a growing literature has explored classes of programs for…

Logic in Computer Science · Computer Science 2026-05-01 Ugo Dal Lago , Guido Fiorillo , Paolo Pistone

The substantial computational demands of modern large-scale deep learning present significant challenges for efficient training and deployment. Recent research has revealed a widespread phenomenon wherein deep networks inherently learn…

Machine Learning · Computer Science 2026-02-04 Laura Balzano , Tianjiao Ding , Benjamin D. Haeffele , Soo Min Kwon , Qing Qu , Peng Wang , Zhangyang Wang , Can Yaras

Complexity is an interdisciplinary concept which, first of all, addresses the question of how order emerges out of randomness. For many reasons matrices provide a very practical and powerful tool in approaching and quantifying the related…

Soft Condensed Matter · Physics 2008-12-18 S. Drozdz , J. Kwapien , J. Speth , M. Wojcik

Communication of information in complex systems can be considered as major driver of systems evolution. What matters is not the communicated information by itself but rather the meaning that is supplied to the information. However…

Computers and Society · Computer Science 2023-04-28 Inga Ivanova

Ranking data arises in a wide variety of application areas but remains difficult to model, learn from, and predict. Datasets often exhibit multimodality, intransitivity, or incomplete rankings---particularly when generated by humans---yet…

Machine Learning · Computer Science 2019-01-29 Stephen Ragain , Johan Ugander

Substructural logics are formal logical systems that omit familiar structural rules of classical and intuitionistic logic such as contraction, weakening, exchange (commutativity), and associativity. This leads to a resource-sensitive…

Logic in Computer Science · Computer Science 2025-05-01 Nikolaos Galatos , Vitor Greati , Revantha Ramanayake , Gavin St. John

Collaboration networks are studied as an example of growing bipartite networks. These have been previously observed to have structure such as positive correlations between nearest-neighbour degrees. However, a detailed understanding of the…

Physics and Society · Physics 2009-11-11 Matti Peltomaki , Mikko Alava

Compositionality has traditionally been understood as a major factor in productivity of language and, more broadly, human cognition. Yet, recently, some research started to question its status, showing that artificial neural networks are…

Computation and Language · Computer Science 2022-06-13 Michal Auersperger , Pavel Pecina

A regular realizability (RR) problem is testing nonemptiness of intersection of some fixed language (filter) with given regular language. We study here complexity of RR problems. It appears that for any language L there exists RR problem…

Computational Complexity · Computer Science 2013-01-01 Mikhail N. Vyalyi

We discuss the feasibility of the following learning problem: given unmatched samples from two domains and nothing else, learn a mapping between the two, which preserves semantics. Due to the lack of paired samples and without any…

Machine Learning · Computer Science 2020-01-16 Tomer Galanti , Lior Wolf , Sagie Benaim

This paper provides a theoretical and computational justification of the long held claim that of the similarity of the probit and logit link functions often used in binary classification. Despite this widespread recognition of the strong…

Machine Learning · Statistics 2015-02-18 Necla Gunduz , Ernest Fokoue

In communication complexity the input of a function $f:X\times Y\rightarrow Z$ is distributed between two players Alice and Bob. If Alice knows only $x\in X$ and Bob only $y\in Y$, how much information must Alice and Bob share to be able to…

Computational Complexity · Computer Science 2026-04-15 Simon Mackenzie , Abdallah Saffidine

The bidirectional selection between two classes widely emerges in various social lives, such as commercial trading and mate choosing. Until now, the discussions on bidirectional selection in structured human society are quite limited. We…

Physics and Society · Physics 2015-02-23 Bin Zhou , Zhe He , Luo-Luo Jiang , Nian-Xin Wang , Bing-Hong Wang

The linear ordering problem (LOP), which consists in ordering M objects from their pairwise comparisons, is commonly applied in many areas of research. While efforts have been made to devise efficient LOP algorithms, verification of whether…

Machine Learning · Computer Science 2023-05-23 Leszek Szczecinski , Harsh Sukheja

The low-rank approximation is a complexity reduction technique to approximate a tensor or a matrix with a reduced rank, which has been applied to the simulation of high dimensional problems to reduce the memory required and computational…

Computational Physics · Physics 2020-08-26 Zhuogang Peng , Ryan McClarren , Martin Frank