27 citations · 65 across the 10 of their papers we have counts for
4 papers · 1 filter
A framework for predicting, interpreting, and improving Learning Outcomes
Chintan Donda, Sayan Dasgupta, Soma S Dhavala +2
It has long been recognized that academic success is a result of both cognitive and non-cognitive dimensions acting together. Consequently, any intelligent learning platform design…
AdaSwarm: Augmenting Gradient-Based optimizers in Deep Learning with Swarm Intelligence
Rohan Mohapatra, Snehanshu Saha, Carlos A. Coello Coello +3
This paper introduces AdaSwarm, a novel gradient-free optimizer which has similar or even better performance than the Adam optimizer adopted in neural networks. In order to support…
LALR: Theoretical and Experimental validation of Lipschitz Adaptive Learning Rate in Regression and Neural Networks
Snehanshu Saha, Tejas Prashanth, Suraj Aralihalli +3
We propose a theoretical framework for an adaptive learning rate policy for the Mean Absolute Error loss function and Quantile loss function and evaluate its effectiveness for regr…
A Framework for Democratizing AI
Shakkeel Ahmed, Ravi S. Mula, Soma S. Dhavala
Machine Learning and Artificial Intelligence are considered an integral part of the Fourth Industrial Revolution. Their impact, and far-reaching consequences, while acknowledged, a…