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We construct the non-standard complex (and real) numbers using the ultrapower method in the spirit of Cauchy's construction of the real numbers. We show that the non-standard complex numbers are a non-archimedean, algebraically closed…

Classical Analysis and ODEs · Mathematics 2008-10-10 Raymond Cavalcante

Multiple-choice question (MCQ) benchmarks have been a standard evaluation practice for measuring LLMs' ability to reason and answer knowledge-based questions. Through a synthetic NonsenseQA benchmark, we observe that different LLMs exhibit…

Computation and Language · Computer Science 2026-02-20 Mateusz Nowak , Xavier Cadet , Peter Chin

This is a gentle introduction to Colombeau nonlinear generalized functions, a generalization of the concept of distributions such that distributions can freely be multiplied. It is intended to physicists and applied mathematicians who…

Mathematical Physics · Physics 2008-10-06 Andre Gsponer

In this paper, nonstandard multistep methods are considered. It is shown that under some (sufficient and necessary) conditions, these methods attain the same order as their standard counterparts - to prove this statement, a nonstandard…

Numerical Analysis · Mathematics 2026-01-19 Bálint Takács

Low-rank approximation is a fundamental technique in modern data analysis, widely utilized across various fields such as signal processing, machine learning, and natural language processing. Despite its ubiquity, the mechanics of low-rank…

Machine Learning · Computer Science 2024-08-13 Jun Lu

This paper investigates the structure of fully nonlinear equations and their applications to geometric problems. We solve some fully nonlinear version of the Loewner-Nirenberg and Yamabe problems. Notably, we introduce Morse theory…

Analysis of PDEs · Mathematics 2025-03-25 Rirong Yuan

The consideration of nonstandard models of the real numbers and the definition of a qualitative ordering on those models provides a generalization of the principle of maximization of expected utility. It enables the decider to assign…

Computer Science and Game Theory · Computer Science 2007-05-23 Daniel Lehmann

Word embeddings are ubiquitous in NLP and information retrieval, but it is unclear what they represent when the word is polysemous. Here it is shown that multiple word senses reside in linear superposition within the word embedding and…

Computation and Language · Computer Science 2018-12-10 Sanjeev Arora , Yuanzhi Li , Yingyu Liang , Tengyu Ma , Andrej Risteski

We define a notion which contains numerous basic notions of Analysis as special cases, for example limit, continuity, differential, Riemann and Lebesgue integral, root and exponential functions. Properties like additivity or linearity of…

Classical Analysis and ODEs · Mathematics 2015-07-07 Matthias Mossburger

Statistically equivalent blocks are not frequently considered in the context of nonparametric two-sample hypothesis testing. Despite the limited exposure, this paper shows that a number of classical nonparametric hypothesis tests can be…

Methodology · Statistics 2025-06-11 Chase Holcombe

These lecture notes provide an informal introduction to the theory of nonnegative polynomials and sums of squares. We highlight the history and some recent developments, especially the new connections with classical (complex) algebraic…

Algebraic Geometry · Mathematics 2021-06-01 Grigoriy Blekherman , Jannik Wesner

These lectures provide an introduction to supersymmetry phenomenology. They include an overview of the Minimal Supersymmetric Standard Model. The notion of soft breaking is explained, constraints on the standard soft breaking parameters are…

High Energy Physics - Phenomenology · Physics 2007-05-23 Michael Dine

Semi-supervised learning is a setting in which one has labeled and unlabeled data available. In this survey we explore different types of theoretical results when one uses unlabeled data in classification and regression tasks. Most methods…

Machine Learning · Computer Science 2020-07-31 Alexander Mey , Marco Loog

Analysis of non-asymptotic estimation error and structured statistical recovery based on norm regularized regression, such as Lasso, needs to consider four aspects: the norm, the loss function, the design matrix, and the noise model. This…

Machine Learning · Statistics 2015-12-01 Arindam Banerjee , Sheng Chen , Farideh Fazayeli , Vidyashankar Sivakumar

While norm-based and leverage-score-based methods have been extensively studied for identifying "important" data points in linear models, analogous tools for nonlinear models remain significantly underdeveloped. By introducing the concept…

Machine Learning · Computer Science 2025-05-20 Prakash Palanivelu Rajmohan , Fred Roosta

These lecture notes for a graduate course cover generalized derivative concepts useful in deriving necessary optimality conditions and numerical algorithms for nondifferentiable optimization problems in inverse problems, imaging, and…

Optimization and Control · Mathematics 2022-03-16 Christian Clason

This study introduces a prescriptive annotation benchmark grounded in humanities research to ensure consistent, unbiased labeling of offensive language, particularly for casual and non-mainstream language uses. We contribute two newly…

Computation and Language · Computer Science 2024-10-18 Xinmeng Hou

We introduce constructive and classical systems for nonstandard arithmetic and show how variants of the functional interpretations due to Goedel and Shoenfield can be used to rewrite proofs performed in these systems into standard ones.…

Logic · Mathematics 2012-07-20 Benno van den Berg , Eyvind Briseid , Pavol Safarik

Bootstrapping and other resampling methods are increasingly appearing in the textbooks and curricula of courses that introduce undergraduate students to statistical methods. In order to teach the bootstrap well, students and instructors…

Other Statistics · Statistics 2024-05-30 Njesa Totty , James Molyneux , Claudio Fuentes

An appeal for symmetry is made to build established notions of specific representation and specific nonlinearity of measurement (often called model error) into a canonical linear regression model. Additive components are derived from the…

Applications · Statistics 2021-10-19 Richard E. Danielson
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