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 ...
Deep Learning with Yacine on MSN
Adadelta optimizer explained – Python tutorial for beginners & pros
Learn how to implement the Adadelta optimization algorithm from scratch in Python. This tutorial explains the math behind ...
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 ...
Deep Learning with Yacine on MSN
Nadam optimizer explained: Python tutorial for beginners & pros
Learn how to implement the Nadam optimizer from scratch in Python. This tutorial walks you through the math behind Nadam, ...
Abstract: Identifying positive influence dominating set (PIDS) with the smallest cardinality can produce positive effect with the minimal cost on a social network. The purpose of this article is to ...
An Ensemble Learning Tool for Land Use Land Cover Classification Using Google Alpha Earth Foundations Satellite Embeddings ...
Abstract: The increasing penetration of renewable generation in power systems poses a significant challenge due to its strong uncertainty. Satisfying security under any realization of the uncertainty ...
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 ...
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