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We propose a novel approach for estimating the difficulty and transferability of supervised classification tasks. Unlike previous work, our approach is solution agnostic and does not require or assume trained models. Instead, we estimate…

Machine Learning · Computer Science 2019-08-23 Anh T. Tran , Cuong V. Nguyen , Tal Hassner

Complexity is a multi-faceted phenomenon, involving a variety of features including disorder, nonlinearity, and self-organisation. We use a recently developed rigorous framework for complexity to understand measures of complexity. We…

Adaptation and Self-Organizing Systems · Physics 2020-09-22 Karoline Wiesner , James Ladyman

We study a complex valued version of the Sobolev inequalities and its relationship to compactness of the d-bar-Neumann operator. For this purpose we use an abstract characterization of compactness derived from a general description of…

Complex Variables · Mathematics 2014-09-10 Friedrich Haslinger

Data classification techniques partition the data or feature space into smaller sub-spaces, each corresponding to a specific class. To classify into subspaces, physical features e.g., distance and distributions are utilized. This approach…

Machine Learning · Computer Science 2025-03-11 Josimar Chire , Khalid Mahmood , Zhao Liang

The gradual patterns that model the complex co-variations of attributes of the form "The more/less X, The more/less Y" play a crucial role in many real world applications where the amount of numerical data to manage is important, this is…

Machine Learning · Computer Science 2020-05-25 Michaël Chirmeni Boujike , Jerry Lonlac , Norbert Tsopze , Engelbert Mephu Nguifo

In this paper, we deal with the classification complexity of continuous (Devaney) chaotic systems in dimensions $0,1$ and $\infty$ using the framework of invariant descriptive set theory. We identify the complexity in dimensions $0$ and…

Dynamical Systems · Mathematics 2026-04-22 Benjamin Vejnar

We consider strongly-convex-strongly-concave saddle-point problems with general non-bilinear objective and different condition numbers with respect to the primal and the dual variables. First, we consider such problems with smooth composite…

Optimization and Control · Mathematics 2021-06-15 Vladislav Tominin , Yaroslav Tominin , Ekaterina Borodich , Dmitry Kovalev , Alexander Gasnikov , Pavel Dvurechensky

In modern science the efficient numerical treatment of high-dimensional problems becomes more and more important. A fundamental insight of the theory of information-based complexity (IBC for short) is that the computational hardness of a…

Numerical Analysis · Mathematics 2013-05-20 Markus Weimar

We prove a complexity dichotomy theorem for all non-negative weighted counting Constraint Satisfaction Problems (CSP). This caps a long series of important results on counting problems including unweighted and weighted graph homomorphisms…

Computational Complexity · Computer Science 2010-12-30 Jin-Yi Cai , Xi Chen , Pinyan Lu

Advancements in mathematical programming have made it possible to efficiently tackle large-scale real-world problems that were deemed intractable just a few decades ago. However, provably optimal solutions may not be accepted due to the…

Optimization and Control · Mathematics 2023-12-22 Kevin-Martin Aigner , Marc Goerigk , Michael Hartisch , Frauke Liers , Arthur Miehlich

We consider the problem of integration of d-variate analytic functions defined on the unit cube with directional derivatives of all orders bounded by 1. We prove that the Clenshaw Curtis Smolyak algorithm leads to weak tractability of the…

Numerical Analysis · Mathematics 2014-04-23 Aicke Hinrichs , Erich Novak , Mario Ullrich

Classical approach of solvability problem has shed much light on what we can solve and what we cannot solve mathematically. Starting with quadratic equation, we know that we can solve it by the quadratic formula which uses square root.…

Geophysics · Physics 2012-12-07 August Lau , Chuan Yin

In this paper, we continue our research on the algorithmic aspects of Halpern and Pearl's causes and explanations in the structural-model approach. To this end, we present new characterizations of weak causes for certain classes of causal…

Artificial Intelligence · Computer Science 2013-01-07 Thomas Eiter , Thomas Lukasiewicz

In this paper we investigate the complexity of abduction, a fundamental and important form of non-monotonic reasoning. Given a knowledge base explaining the world's behavior it aims at finding an explanation for some observed manifestation.…

Computational Complexity · Computer Science 2010-06-28 Nadia Creignou , Johannes Schmidt , Michael Thomas

In the article, within the framework of the Boolean Satisfiability problem (SAT), the problem of estimating the hardness of specific Boolean formulas w.r.t. a specific complete SAT solving algorithm is considered. Based on the well-known…

Artificial Intelligence · Computer Science 2023-12-19 Daniil Chivilikhin , Artem Pavlenko , Alexander Semenov

Persistent cycles, especially the minimal ones, are useful geometric features functioning as augmentations for the intervals in a purely topological persistence diagram (also termed as barcode). In our earlier work, we showed that computing…

Computational Geometry · Computer Science 2020-02-18 Tamal K. Dey , Tao Hou , Sayan Mandal

The purpose of this paper is to characterize weak supercyclicity for Hilbert-space contractions, which is shown to be equivalent to characterizing weak supercyclicity for unitary operators$.$ This is naturally motivated by an open question…

Functional Analysis · Mathematics 2020-10-27 C. S. Kubrusly , P. C. M. Vieira

We show that the minimal discrepancy of a point set in the $d$-dimensional unit cube with respect to Orlicz norms can exhibit both polynomial and weak tractability. In particular, we show that the $\psi_\alpha$-norms of exponential Orlicz…

Numerical Analysis · Mathematics 2020-02-10 Josef Dick , Aicke Hinrichs , Friedrich Pillichshammer , Joscha Prochno

With the rapid popularization of big data, the dichotomy between tractable and intractable problems in big data computing has been shifted. Sublinear time, rather than polynomial time, has recently been regarded as the new standard of…

Computational Complexity · Computer Science 2021-12-01 Xiangyu Gao , Jianzhong Li , Dongjing Miao

We study the randomized $n$-th minimal errors (and hence the complexity) of vector valued mean computation, which is the discrete version of parametric integration. The results of the present paper form the basis for the complexity analysis…

Numerical Analysis · Mathematics 2023-06-26 Stefan Heinrich