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08/19/2023
To prune or not to prune : A chaos-causality approach to principled pruning of dense neural networks
Reducing the size of a neural network (pruning) by removing weights with...
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04/25/2023
Decoupling Quantile Representations from Loss Functions
The simultaneous quantile regression (SQR) technique has been used to es...
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04/07/2023
Correcting Model Misspecification via Generative Adversarial Networks
Machine learning models are often misspecified in the likelihood, which ...
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02/17/2023
Quantile LSTM: A Robust LSTM for Anomaly Detection In Time Series Data
Anomalies refer to the departure of systems and devices from their norma...
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09/09/2022
Investigation of a Machine learning methodology for the SKA pulsar search pipeline
The SKA pulsar search pipeline will be used for real time detection of p...
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06/19/2022
LogGENE: A smooth alternative to check loss for Deep Healthcare Inference Tasks
High-throughput Genomics is ushering a new era in personalized health ca...
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05/08/2022
Hamiltonian Monte Carlo Particle Swarm Optimizer
We introduce the Hamiltonian Monte Carlo Particle Swarm Optimizer (HMC-P...
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09/06/2021
Postulating Exoplanetary Habitability via a Novel Anomaly Detection Method
A profound shift in the study of cosmology came with the discovery of th...
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04/10/2021
A Swarm Variant for the Schrödinger Solver
This paper introduces application of the Exponentially Averaged Momentum...
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04/10/2021
Fairly Constricted Particle Swarm Optimization
We have adapted the use of exponentially averaged momentum in PSO to mul...
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05/19/2020
AdaSwarm: A Novel PSO optimization Method for the Mathematical Equivalence of Error Gradients
This paper tackles the age-old question of derivative free optimization ...
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05/18/2020
Parsimonious Computing: A Minority Training Regime for Effective Prediction in Large Microarray Expression Data Sets
Rigorous mathematical investigation of learning rates used in back-propa...
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10/06/2019
ChaosNet: A Chaos based Artificial Neural Network Architecture for Classification
Inspired by chaotic firing of neurons in the brain, we propose ChaosNet ...
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06/01/2019
Evolution of Novel Activation Functions in Neural Network Training with Applications to Classification of Exoplanets
We present analytical exploration of novel activation functions as conse...
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02/20/2019
A novel adaptive learning rate scheduler for deep neural networks
Optimizing deep neural networks is largely thought to be an empirical pr...
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06/06/2018
SBAF: A New Activation Function for Artificial Neural Net based Habitability Classification
We explore the efficacy of using a novel activation function in Artifici...
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05/18/2018
ALVEC: Auto-scaling by Lotka Volterra Elastic Cloud: A QoS aware Non Linear Dynamical Allocation Model
Elasticity in resource allocation is still a relevant problem in cloud c...
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05/09/2018
Time Reversed Delay Differential Equation Based Modeling Of Journal Influence In An Emerging Area
A recent independent study resulted in a ranking system which ranked Ast...
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04/21/2018
Use of NoSQL database and visualization techniques to analyze massive scholarly article data from journals
Visualization of the massive data is a challenging endeavor. Extracting ...
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04/13/2018
Machine Learning in Astronomy: A Case Study in Quasar-Star Classification
We present the results of various automated classification methods, base...
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03/13/2018
Model Visualization in understanding rapid growth of a journal in an emerging area
A recent independent study resulted in a ranking system which ranked Ast...
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03/06/2018