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Strong functors and monads are ubiquitous in Computer Science. More recently, comonads have demonstrated their use in structuring context-dependent notions of computation. However, the dualisation of ``being strong'' property passed somehow…

Logic in Computer Science · Computer Science 2025-09-17 Adriana Balan , Silviu-George Pantelimon

Envy-freeness is one of the most prominent fairness concepts in the allocation of indivisible goods. Even though trivial envy-free allocations always exist, rich literature shows this is not true when one additionally requires some…

Computer Science and Game Theory · Computer Science 2025-02-19 Robert Bredereck , Andrzej Kaczmarczyk , Junjie Luo , Bin Sun

A naive theory of additive perturbations on a continuous probability distribution is presented. We propose a new privatization mechanism based on a naive theory of a perturbation on a probability using wavelets, such as a noise perturbs the…

Signal Processing · Electrical Eng. & Systems 2023-04-21 Helio M. de Oliveira , Raydonal Ospina , Victor Leiva , Carlos Martin-Barreiro , Christophe Chesneau

Attribution-based explanation techniques capture key patterns to enhance visual interpretability; however, these patterns often lack the granularity needed for insight in fine-grained tasks, particularly in cases of model misclassification,…

Artificial Intelligence · Computer Science 2025-11-12 Lintong Zhang , Kang Yin , Seong-Whan Lee

A common approach to evaluating the significance of a collection of $p$-values combines them with a pooling function, in particular when the original data are not available. These pooled $p$-values convert a sample of $p$-values into a…

Methodology · Statistics 2023-11-15 Chris Salahub , Wayne Oldford

We study a new notion of reduction between structures called enumerable functors related to the recently investigated notion of computable functors. Our main result shows that enumerable functors and effective interpretability with the…

Logic · Mathematics 2017-08-11 Dino Rossegger

A recent literature considers causal inference using noisy proxies for unobserved confounding factors. The proxies are divided into two sets that are independent conditional on the confounders. One set of proxies are `negative control…

Econometrics · Economics 2021-10-11 Ben Deaner

We extend to multiplicative lattices a theorem of Anderson and Roitman characterizing the cancellation ideals of a commutative ring.

Commutative Algebra · Mathematics 2026-01-23 Tiberiu Dumitrescu

In computational social choice, the distortion of a voting rule quantifies the degree to which the rule overcomes limited preference information to select a socially desirable outcome. This concept has been investigated extensively, but…

Computer Science and Game Theory · Computer Science 2023-12-11 Yannai A. Gonczarowski , Gregory Kehne , Ariel D. Procaccia , Ben Schiffer , Shirley Zhang

A great many tools have been developed for supervised classification, ranging from early methods such as linear discriminant analysis through to modern developments such as neural networks and support vector machines. A large number of…

Statistics Theory · Mathematics 2007-06-13 David J. Hand

Recent work has raised concerns on the risk of spurious correlations and unintended biases in statistical machine learning models that threaten model robustness and fairness. In this paper, we propose a simple and intuitive regularization…

Machine Learning · Computer Science 2021-10-05 Zhao Wang , Kai Shu , Aron Culotta

We define a reasonably well-behaved class of ultraimaginaries, i.e.\ classes modulo invariant equivalence relations, called {\em tame}, and establish some basic simplicity-theoretic facts. We also show feeble elimination of supersimple…

Logic · Mathematics 2014-03-24 Frank Olaf Wagner

Transcendental functions, such as exponentials and logarithms, appear in a broad array of computational domains: from simulations in curvilinear coordinates, to interpolation, to machine learning. Unfortunately they are typically expensive…

Computational Physics · Physics 2022-06-22 Jonah M. Miller , Joshua C. Dolence , Daniel Holladay

Motivated by the problem of constructing bijective maps with low differential uniformity, we introduce the notion of permutation resemblance of a function, which looks to measure the distance a given map is from being a permutation. We…

Information Theory · Computer Science 2023-02-08 Li-An Chen , Robert S. Coulter

To a function with values in the power set of a pre--ordered, separated locally convex space a family of scalarizations is given which completely characterizes the original function. A concept of a Legendre--Fenchel conjugate for set-valued…

Optimization and Control · Mathematics 2014-05-30 Carola Schrage

In open-ended environments, autonomous learning agents must set their own goals and build their own curriculum through an intrinsically motivated exploration. They may consider a large diversity of goals, aiming to discover what is…

Artificial Intelligence · Computer Science 2026-01-30 Cédric Colas , Pierre Fournier , Olivier Sigaud , Mohamed Chetouani , Pierre-Yves Oudeyer

We recently described a formalism for reasoning with if-then rules that re expressed with different levels of firmness [18]. The formalism interprets these rules as extreme conditional probability statements, specifying orders of magnitude…

Artificial Intelligence · Computer Science 2013-03-25 Moises Goldszmidt , Judea Pearl

Under the formalism of annealed averaging of the partition function, a type of random multifractal measures with their multipliers satisfying exponentially distributed is investigated in detail. Branching emerges in the curve of generalized…

Adaptation and Self-Organizing Systems · Physics 2009-10-31 Wei-Xing Zhou , Zun-Hong yu

Dantzig and Eaves claimed that fundamental duality theorems of linear programming were a trivial consequence of Fourier elimination. Another property of Fourier elimination is considered here, regarding the existence of implicit equalities…

Discrete Mathematics · Computer Science 2019-08-23 Jean-Louis Lassez

In this paper, we present a dual representation of the influence functions, whose computational complexity scales with dataset size rather than model size. Both analytically and experimentally, we show that this representation can be an…

Machine Learning · Computer Science 2026-05-13 Zhenhuan Sun , Shahrokh Valaee