Research team debuts the first deterministic streaming algorithms for non-monotone submodular maximization, delivering superior approximation ratios with minimal memory and real-time throughput on ...

The travelling salesman problem (TSP) remains one of the most challenging NP‐hard problems in combinatorial optimisation, with significant implications for logistics, network design and route planning ...

Learn how to implement the Adadelta optimization algorithm from scratch in Python. This tutorial explains the math behind ...

Learn how to implement the K-Nearest Neighbors (KNN) algorithm from scratch in Python! This tutorial covers the theory, ...

Graph cover problems form a critical area within discrete optimisation and theoretical computer science, addressing the challenge of selecting subsets of vertices (or edges) that satisfy predetermined ...

An Ensemble Learning Tool for Land Use Land Cover Classification Using Google Alpha Earth Foundations Satellite Embeddings ...

First-order derivatives: n additional function calls are needed. Second-order derivatives based on gradient calls, when the "grd" module is specified (Dennis and Schnabel 1983): n additional gradient ...

James Chen, CMT is an expert trader, investment adviser, and global market strategist. Gordon Scott has been an active investor and technical analyst or 20+ years. He is a Chartered Market Technician ...

Abstract: This paper presents a digital low-dropout regulator (DLDO) architecture employing the improved successive approximation logic algorithm as its control strategy. The algorithm is combined ...

MorphIt is a novel algorithm for approximating robot morphology using spherical primitives that balances geometric accuracy with computational efficiency. Unlike existing approaches that rely on ...

Abstract: This paper investigates the device activity detection problem in a massive multiple-input multiple-output system for near-field communications. In this setup, active devices transmit their ...