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Related papers: Introduction to Set Shaping Theory

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Given the importance of the claim, we want to start by exposing the following consideration: this claim comes out more than a year after the article "Practical applications of Set Shaping Theory in Huffman coding" which reports the program…

Information Theory · Computer Science 2024-01-02 Aida Koch , Alix Petit , Christian Schmidt , Adrain Vdberg , Logan Lewis

The purpose of this paper is to give a survey on the notions of distance between subsets either of a metric space or of a measure space, including definitions, a classification, and a discussion of the best-known distance functions, which…

Functional Analysis · Mathematics 2018-08-09 A. Conci , C. S. Kubrusly

We propose learning flexible but interpretable functions that aggregate a variable-length set of permutation-invariant feature vectors to predict a label. We use a deep lattice network model so we can architect the model structure to…

Machine Learning · Computer Science 2018-06-04 Andrew Cotter , Maya Gupta , Heinrich Jiang , James Muller , Taman Narayan , Serena Wang , Tao Zhu

Many examples of zeta functions in number theory and combinatorics are special cases of a construction in homotopy theory known as a decomposition space. This article aims to introduce number theorists to the relevant concepts in homotopy…

Number Theory · Mathematics 2023-10-23 Andrew Kobin

In this paper we propose a new wavelet transform applicable to functions defined on graphs, high dimensional data and networks. The proposed method generalizes the Haar-like transform proposed in [1], and it is defined via a hierarchical…

Computer Vision and Pattern Recognition · Computer Science 2015-05-20 Idan Ram , Michael Elad , Israel Cohen

Many random growth models have the property that the set of discovered sites, scaled properly, converges to some deterministic set as time grows. Such results are known as shape theorems. Typically, not much is known about the shapes. For…

Machine Learning · Statistics 2020-06-26 Sebastian Rosengren

The shapelet transform is a form of feature extraction for time series, in which a time series is described by its similarity to each of a collection of `shapelets'. However it has previously suffered from a number of limitations, such as…

Machine Learning · Computer Science 2020-06-01 Patrick Kidger , James Morrill , Terry Lyons

We provide a qualitative review of flux compactifications of string theory, focusing on broad physical implications and statistical methods of analysis.

High Energy Physics - Theory · Physics 2008-11-26 Frederik Denef , Michael R. Douglas , Shamit Kachru

String theory is the most promising candidate theory for a unified description of all fundamental forces exist in the nature. It provides a mathematical framework that combine quantum theory with Einstein's general theory of relativity. But…

General Physics · Physics 2012-09-26 S. Sahoo

In a nutshell, submodular functions encode an intuitive notion of diminishing returns. As a result, submodularity appears in many important machine learning tasks such as feature selection and data summarization. Although there has been a…

Data Structures and Algorithms · Computer Science 2018-03-19 Marko Mitrovic , Moran Feldman , Andreas Krause , Amin Karbasi

We propose a general formalism of iterated random functions with semigroup property, under which exact and approximate Bayesian posterior updates can be viewed as specific instances. A convergence theory for iterated random functions is…

Machine Learning · Statistics 2013-11-05 Arash A. Amini , XuanLong Nguyen

Type IIB string theory admits a BPS configuration in which three strings (of different type) meet at a point. Using this three string configuration we construct a string network and study its properties. In particular we prove supersymmetry…

High Energy Physics - Theory · Physics 2009-10-30 Ashoke Sen

The Euler characteristic transform (ECT) is a simple to define yet powerful representation of shape. The idea is to encode an embedded shape using sub-level sets of a a function defined based on a given direction, and then returning the…

Computational Geometry · Computer Science 2023-10-17 Elizabeth Munch

Deep neural networks trained in an end-to-end manner are proven to be efficient in a wide range of machine learning tasks. However, there is one drawback of end-to-end learning: The learned features and information are implicitly…

Machine Learning · Computer Science 2024-06-07 Canlin Zhang , Xiuwen Liu

The theory of sequences, supported by many SMT solvers, can model program data types including bounded arrays and lists. Sequences are parameterized by the element data type and provide operations such as accessing elements, concatenation,…

Programming Languages · Computer Science 2025-09-09 Denghang Hu , Taolue Chen , Philipp Rümmer , Fu Song , Zhilin Wu

Amidst all candidates of physics beyond the Standard Model, string theory provides a unique proposal for incorporating gauge and gravitational interactions. In string theory, a four-dimensional theory that unifies quantum mechanics and…

High Energy Physics - Theory · Physics 2024-09-30 Fernando Marchesano , Gary Shiu , Timo Weigand

Size-Change Termination is an increasingly-popular technique for verifying program termination. These termination proofs are deduced from an abstract representation of the program in the form of "size-change graphs". We present algorithms…

Logic in Computer Science · Computer Science 2015-07-01 Amir M. Ben-Amram , Chin Soon Lee

This paper provides a complete suite of axioms for a version of set theory that I call Explication. Explication borrows from the two most prominent existing systems of set theory. Explication starts with class variables. After several…

Logic · Mathematics 2017-09-14 Ernest Akemann

We provide a formal introduction into the classic theorems of general topology and its axiomatic foundations in set theory. Starting from ZFC, the exposition in this first part includes relation and order theory as well as a construction of…

History and Overview · Mathematics 2013-06-26 Felix Nagel

Size-Change Termination (SCT) is a method of proving program termination based on the impossibility of infinite descent. To this end we use a program abstraction in which transitions are described by Monotonicity Constraints over (abstract)…

Logic in Computer Science · Computer Science 2015-07-01 Amir M. Ben-Amram