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We reduce the Collatz conjecture to a fixed-modulus, one-bit orbit-mixing problem. Working with the compressed odd-to-odd Collatz map, we prove exact low-depth decomposition formulas at depths K = 3, 4, 5, reducing block-discrepancy terms…

Dynamical Systems · Mathematics 2026-03-30 Edward Y. Chang

The reciprocal function, 1/x, is important for many real-time algorithms. It is used in a large variety of algorithms from areas ranging from iterative estimation to machine learning. Many of these algorithms are iterative in nature and…

Signal Processing · Electrical Eng. & Systems 2020-07-14 Michael Lunglmayr , Oliver Ploder

The famous (3n + 1) or Collatz conjecture has admitted some progress over the last several decades towards the conclusion that the conjecture is true (i.e. that all Collatz sequences will eventually reach a value of one), but has stubbornly…

General Mathematics · Mathematics 2021-03-30 Brian Mohan Gurbaxani

This paper explores a method for solving constrained optimization problems when the derivatives of the objective function are unavailable, while the derivatives of the constraints are known. We allow the objective and constraint function to…

Optimization and Control · Mathematics 2024-02-20 Melody Qiming Xuan , Jorge Nocedal

We consider the robust single-source capacitated facility location problem with uncertainty in customer demands. A cardinality-constrained uncertainty set is assumed for the robust problem. To solve it efficiently, we propose an…

Optimization and Control · Mathematics 2021-03-25 Jaehyeon Ryu , Sungsoo Park

We consider the problem of approximating the solution of variational problems subject to the constraint that the admissible functions must be convex. This problem is at the interface between convex analysis, convex optimization, variational…

Numerical Analysis · Mathematics 2015-03-19 Adam M. Oberman

This paper proposes a formula expression for the well-known Collatz conjecture (or 3x+1 problem), which can pinpoint all the growth points in the orbits of the Collatz map for any natural numbers. The Collatz map $Col: \mathcal{N}+1…

Number Theory · Mathematics 2019-10-02 Longjiang Li

In computer algebra there are different ways of approaching the mathematical concept of functions, one of which is by defining them as solutions of differential equations. We compare different such approaches and discuss the occurring…

Symbolic Computation · Computer Science 2013-06-19 Frédéric Chyzak , James Davenport , Christoph Koutschan , Bruno Salvy

In this paper we consider stochastic composite convex optimization problems with the objective function satisfying a stochastic bounded gradient condition, with or without a quadratic functional growth property. These models include the…

Optimization and Control · Mathematics 2020-03-10 Ion Necoara

The Collatz Conjecture can be stated as: using the reduced Collatz function $C(n) = (3n+1)/2^x$ where $2^x$ is the largest power of 2 that divides $3n+1$, any odd integer $n$ will eventually reach 1 in $j$ iterations such that $C^j(n) = 1$.…

General Mathematics · Mathematics 2019-10-18 Erhan Tezcan

We consider a fractional 0-1 programming problem arising in manufacturing. The problem consists in clustering of machines together with parts processed on these machines into manufacturing cells so that intra-cell processing of parts is…

Data Structures and Algorithms · Computer Science 2016-03-16 Irina Utkina , Mikhail Batsyn , Ekaterina Batsyna

We introduce an algorithm which can be directly used to feasible and optimum search in linear programming. Starting from an initial point the algorithm iteratively moves a point in a direction to resolve the violated constraints. At the…

Optimization and Control · Mathematics 2023-12-05 Denys Shcherbak , Natalya Pya Arnqvist

The arrival of AI techniques in computations, with the potential for hallucinations and non-robustness, has made trustworthiness of algorithms a focal point. However, trustworthiness of the many classical approaches are not well understood.…

Optimization and Control · Mathematics 2023-12-19 Alexander Bastounis , Felipe Cucker , Anders C. Hansen

To estimate the conditional probability functions based on the direct problem setting, V-matrix based method was proposed. We construct V-matrix based constrained quadratic programming problems for which the inequality constraints are…

Machine Learning · Statistics 2018-09-07 Niharika Gauraha , Akshay Chaturvedi

We present a new feasible proximal gradient method for constrained optimization where both the objective and constraint functions are given by the summation of a smooth, possibly nonconvex function and a convex simple function. The…

Optimization and Control · Mathematics 2024-02-01 Digvijay Boob , Qi Deng , Guanghui Lan

We present an alternative proof for the existence of solutions of stochastic functional differential equations satisfying a global Lipschitz condition. The proof is based on an approximation scheme in which the continuous path dependence…

Probability · Mathematics 2017-09-05 Flavia Sancier , Salah Mohammed

Recently, there has been a renewed interest in decomposition-based approaches for evolutionary multiobjective optimization. However, the impact of the choice of the underlying scalarizing function(s) is still far from being well understood.…

Artificial Intelligence · Computer Science 2014-09-22 Bilel Derbel , Dimo Brockhoff , Arnaud Liefooghe , Sébastien Verel

We analyze the stopping-time and cycle structure of the normalized Collatz iteration. Using a recursive description of admissible binary sequences, we show that every integer $m \equiv 3 \pmod{4}$ arises uniquely and derive new bounds for…

General Mathematics · Mathematics 2026-01-28 Daohang Sha

In this paper, we construct an algorithm for minimising piecewise smooth functions for which derivative information is not available. The algorithm constructs a pair of quadratic functions, one on each side of the point with smallest known…

Optimization and Control · Mathematics 2020-12-14 Jonathan Grant-Peters , Raphael Hauser

A block decomposition method is proposed for minimizing a (possibly non-convex) continuously differentiable function subject to one linear equality constraint and simple bounds on the variables. The proposed method iteratively selects a…

Optimization and Control · Mathematics 2019-03-06 Andrea Cristofari
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