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mohanbhandari's Projects

adversarial-attack icon adversarial-attack

https://drive.google.com/drive/folders/1qdhLbKky2YvSC_9OTcAkLr-4uN5BZYDW?usp=sharing

eneryindexintroducedtoadam icon eneryindexintroducedtoadam

The adjustment of learning rate(η), bias and different other parameters during back propagation are crucial for the performance of machine learning based algorithms. In support for better performance, by utilizing the exponential decay of past gradi- ents and their squares, Adam Optimization technique tries to tune different learning parameters. Still, the algorithm lacks involvement and calculations of frequently oc- curring features in individual neurons of the network which play significant role in adjusting the learning rate for the performance improvement of the algorithms. The study focuses on Energy Index Based Optimization Method which introduces the significance of frequently occurring features in Adam Optimization. Energy model of neuron is designed to calculate the energy index being based on the frequency of feature and Energy Index is calculated. Energy Index was taken into account along with Adam Optimizer. The performance of energy introduced Adam optimizer was experimented on Logistic Regression, Multi-Layer Perceptron and Support Vector Machine

hate-speech-detection-survey icon hate-speech-detection-survey

Trained Neural Networks (LSTM, HybridCNN/LSTM, PyramidCNN, Transformers, etc.) & comparison for the task of Hate Speech Detection on the OLID Dataset (Tweets).

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