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Despite the success of machine learning applications in science, industry, and society in general, many approaches are known to be non-robust, often relying on spurious correlations to make predictions. Spuriousness occurs when some…

Computer Vision and Pattern Recognition · Computer Science 2021-06-04 Chun-Hao Chang , George Alexandru Adam , Anna Goldenberg

This paper provides a new and more direct proof of the assertion that a Turing computable function of the natural numbers is primitive recursive if and only if the time complexity of the corresponding Turing machine is bounded by a…

Formal Languages and Automata Theory · Computer Science 2025-10-22 Daniel G. Schwartz

A unified approach to quintessence and inflation is investigated with the use of a single scalar field. It is argued that successful potentials have to approximate a combination of exponential and inverse power-law decline in the limit of…

Astrophysics · Physics 2007-05-23 Konstantinos Dimopoulos

Building on the results of Craig, van Ittersum, and Ono, we provide a refined understanding of MacMahon's partition functions and their variants, including their quasi-modular properties and new prime-detecting expressions.

Number Theory · Mathematics 2025-02-05 Soon-Yi Kang , Toshiki Matsusaka , Gyucheol Shin

In recent years, there has been increasing interest in explanation methods for neural model predictions that offer precise formal guarantees. These include abductive (respectively, contrastive) methods, which aim to compute minimal subsets…

Machine Learning · Computer Science 2023-05-03 Ouns El Harzli , Bernardo Cuenca Grau , Ian Horrocks

This paper proposes a novel and insightful activation method termed FPLUS, which exploits mathematical power function with polar signs in form. It is enlightened by common inverse operation while endowed with an intuitive meaning of…

Computer Vision and Pattern Recognition · Computer Science 2021-11-30 Boxi Duan

A new type of dependent thinning for point processes in continuous space is proposed, which leverages the advantages of determinantal point processes defined on finite spaces and, as such, is particularly amenable to statistical, numerical,…

Machine Learning · Computer Science 2019-06-19 Bartłomiej Błaszczyszyn , Paul Keeler

In a variety of applications, including nonparametric instrumental variable (NPIV) analysis, proximal causal inference under unmeasured confounding, and missing-not-at-random data with shadow variables, we are interested in inference on a…

We prove estimates for the level of distribution of the M\"obius function, von Mangoldt function, and divisor functions in squarefree progressions in the ring of polynomials over a finite field. Each level of distribution converges to $1$…

Number Theory · Mathematics 2022-07-12 Will Sawin

In [5], [6] and [8], the authors gave some modular forms over $\Gamma^0(2)$. In this note, we proceed with the study of cancellation formulas relating to the modular forms.

Differential Geometry · Mathematics 2023-10-11 Siyao Liu , Yong Wang

Predictive mean matching (PMM) is a popular imputation strategy that imputes missing values by borrowing observed values from other cases with similar expectations. We show that, unlike other imputation strategies, PMM is not guaranteed to…

Methodology · Statistics 2025-07-01 Paul T. von Hippel

Despite the remarkable success of deep neural networks, significant concerns have emerged about their robustness to adversarial perturbations to inputs. While most attacks aim to ensure that these are imperceptible, physical perturbation…

Machine Learning · Computer Science 2020-10-09 Liang Tong , Minzhe Guo , Atul Prakash , Yevgeniy Vorobeychik

This paper is concerned with the study of the consistency of a variational method for probability measure quantization, deterministically realized by means of a minimizing principle, balancing power repulsion and attraction potentials. The…

Functional Analysis · Mathematics 2013-10-07 Massimo Fornasier , Jan-Christian Hütter

While data are the primary fuel for machine learning models, they often suffer from missing values, especially when collected in real-world scenarios. However, many off-the-shelf machine learning models, including artificial neural network…

Over the last two decades, submodular function maximization has been the workhorse of many discrete optimization problems in machine learning applications. Traditionally, the study of submodular functions was based on binary function…

Machine Learning · Computer Science 2022-05-18 Loay Mualem , Moran Feldman

Current pooling rules for multiply imputed data assume infinite populations. In some situations this assumption is not feasible as every unit in the population has been observed, potentially leading to over-covered population estimates. We…

Statistics Theory · Mathematics 2014-10-01 Gerko Vink , Stef van Buuren

We show that a general miraculous cancellation formula, the divisibility of certain characteristic numbers and some other topologiclal results are con- sequences of the modular invariance of elliptic operators on loop spaces. Previously we…

High Energy Physics - Theory · Physics 2011-07-19 Kefeng Liu

We prove structural results for measure preserving systems, called Furstenberg systems, naturally associated with bounded multiplicative functions. We show that for all pretentious multiplicative functions these systems always have rational…

Number Theory · Mathematics 2025-08-13 Nikos Frantzikinakis , Mariusz Lemańczyk , Thierry de la Rue

In this paper, we study a class of functions defined recursively on the set of natural numbers in terms of the greatest common divisor algorithm of two numbers and requiring a minimality condition. These functions are permutations, products…

Number Theory · Mathematics 2025-12-08 Amit Kumar Basistha , Eugen J. Ionascu

The "significance filter" refers to focusing exclusively on statistically significant results. Since frequentist properties such as unbiasedness and coverage are valid only before the data have been observed, there are no guarantees if we…

Methodology · Statistics 2020-09-22 Erik van Zwet , Eric Cator
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