After layoffs at Recursion, the company’s CEO writes about taking inspiration from an unexpected source: “The Art of Racing ...

A general algorithm to solve linear and nonlinear inverse problems, based on recursive neural networks, is discussed in this work. The procedure will be applied to physical chemical problems modeled ...

This repository contains the problem instances and source code used in the article Recursive McCormick Linearization of Multilinear Programs, authored by David Bergman, Carlos Cardonha, Arvind U.

Developed for optimizing complex search operations, this algorithm leverages a unique recursive approach ... By reducing the time complexity of finding row minima from quadratic to linear, SMAWK ...

The algorithm converges extremely rapidly. There are some recursive algorithms that make good use of the divide and conquer technique. In fact, recursion is based on two key problem solving concepts - ...

The authors proposed Recursive Feature Machines (RFMs) as an algorithm that explicitly performs feature ... focusing on the class of overparameterized problems arising in sparse linear regression and ...

Abstract: A recursive algorithm is developed for solving the algebraic equations comprising the solution of the optimal static output feedback control problem of singularly perturbed linear systems.

The origin of numerous significant algorithmic developments such as the simplex method, graph sparsification ... to ensure the overall recursion reduces the graph size in each step, which is essential ...