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Found 6 papers, 3 papers with code
Efficient ML Models for Practical Secure Inference
For instance, the model provider could be a diagnostics company that has trained a state-of-the-art DenseNet-121 model for interpreting a chest X-ray and the user could be a patient at a hospital.
Encoding Involutory Invariances in Neural Networks
In certain situations, neural networks are trained upon data that obey underlying symmetries.
A Swarm Variant for the Schrödinger Solver
This paper introduces application of the Exponentially Averaged Momentum Particle Swarm Optimization (EM-PSO) as a derivative-free optimizer for Neural Networks.
Fairly Constricted Multi-Objective Particle Swarm Optimization
It has been well documented that the use of exponentially-averaged momentum (EM) in particle swarm optimization (PSO) is advantageous over the vanilla PSO algorithm.
Automated Detection of Double Nuclei Galaxies using GOTHIC and the Discovery of a Large Sample of Dual AGN
We present a novel algorithm to detect double nuclei galaxies (DNG) called GOTHIC (Graph BOosted iterated HIll Climbing) - that detects whether a given image of a galaxy has two or more closely separated nuclei.
AdaSwarm: Augmenting Gradient-Based optimizers in Deep Learning with Swarm Intelligence
This paper introduces AdaSwarm, a novel gradient-free optimizer which has similar or even better performance than the Adam optimizer adopted in neural networks.
