Submodular maximization is a significant area of interest in combinatorial optimization, with numerous real-world applications. A research team led by Xiaoming SUN from the State Key Lab of Processors ...

Service intelligence startup Neuron7 Inc. said today it has come up with a solution to solve the reliability challenges that prevent enterprises from adopting artificial intelligence agents. That ...

Learn the Adagrad optimization algorithm, how it works, and how to implement it from scratch in Python for machine learning models. #Adagrad #Optimization #Python Trump administration looking to sell ...

There is a new sorting algorithm a deterministic O(m log2/3 n)-time algorithm for single-source shortest paths (SSSP) on directed graphs with real non-negative edge weights in the comparison-addition ...

Abstract: Traditional DDPG algorithm experience replay is limited by the fixed replay buffer capacity, which cannot meet the demand for multi-feature data with the improvement of the learning ability ...

Learn how the Adadelta optimization algorithm really works by coding it from the ground up in Python. Perfect for ML enthusiasts who want to go beyond the black box! Florida State Bracing for Hefty ...

1 Energy, Materials and Methods Research Laboratory, National High Polytechnic School of Douala, Douala, Cameroon. 2 National Advanced School of Engineering, University of Yaounde I, Yaounde, Cameroon ...