53 citations · 65 across the 6 of their papers we have counts for
6 papers
A Survey on Multi-Objective based Parameter Optimization for Deep Learning
Mrittika Chakraborty, Wreetbhas Pal, Sanghamitra Bandyopadhyay +1
Deep learning models form one of the most powerful machine learning models for the extraction of important features. Most of the designs of deep neural models, i.e., the initializa…
IV-GNN : Interval Valued Data Handling Using Graph Neural Network
Sucheta Dawn, Sanghamitra Bandyopadhyay
Graph Neural Network (GNN) is a powerful tool to perform standard machine learning on graphs. To have a Euclidean representation of every node in the Non-Euclidean graph-like data,…
Predicting potential drug targets and repurposable drugs for COVID-19 via a deep generative model for graphs
Sumanta Ray, Snehalika Lall, Anirban Mukhopadhyay +2
Coronavirus Disease 2019 (COVID-19) has been creating a worldwide pandemic situation. Repurposing drugs, already shown to be free of harmful side effects, for the treatment of COVI…
Decomposition in Decision and Objective Space for Multi-Modal Multi-Objective Optimization
Monalisa Pal, Sanghamitra Bandyopadhyay
Multi-modal multi-objective optimization problems (MMMOPs) have multiple subsets within the Pareto-optimal Set, each independently mapping to the same Pareto-Front. Prevalent multi…
A Many Objective Optimization Approach for Transfer Learning in EEG Classification
Monalisa Pal, Sanghamitra Bandyopadhyay, Saugat Bhattacharyya
In Brain-Computer Interfacing (BCI), due to inter-subject non-stationarities of electroencephalogram (EEG), classifiers are trained and tested using EEG from the same subject. When…
conLSH: Context based Locality Sensitive Hashing for Mapping of noisy SMRT Reads
Angana Chakraborty, Sanghamitra Bandyopadhyay
Single Molecule Real-Time (SMRT) sequencing is a recent advancement of Next Gen technology developed by Pacific Bio (PacBio). It comes with an explosion of long and noisy reads dem…