S
Swagatam Das
Researcher at Indian Statistical Institute
Publications - 56
Citations - 903
Swagatam Das is an academic researcher from Indian Statistical Institute. The author has contributed to research in topics: Cluster analysis & Optimization problem. The author has an hindex of 6, co-authored 56 publications receiving 431 citations.
Papers
More filters
Proceedings ArticleDOI
Generative Adversarial Minority Oversampling
TL;DR: In this article, a three-player adversarial game between a convex generator, a multi-class classifier network, and a real/fake discriminator is proposed to perform oversampling in deep learning systems.
Journal ArticleDOI
A synergy of the sine-cosine algorithm and particle swarm optimizer for improved global optimization and object tracking
TL;DR: Comparison studies of tracking accuracy and speed of the Hybrid SCA-PSO based tracking framework and other trackers, viz., Particle filter, Mean-shift, Particle swarm optimization, Bat algorithm, Sine Cosine Algorithm (SCA) and Hybrid Gravitational Search Al algorithm (HGSA) is presented.
Book
Metaheuristic Clustering
TL;DR: Academics, scientists as well as engineers engaged in research, development and application of optimization techniques and data mining will find the comprehensive coverage of this book invaluable.
Journal ArticleDOI
A multi-start variable neighbourhood descent algorithm for hybrid flowshop rescheduling
TL;DR: A comprehensive comparison against seven highly efficient algorithms demonstrates the superiority of the Multi-Start Variable Neighbourhood Descent (MSVND) algorithm for HFS rescheduling considering simultaneously three types of dynamic events.
Proceedings ArticleDOI
Improving Differential Evolution through Bayesian Hyperparameter Optimization
TL;DR: The MadDE algorithm as discussed by the authors leverages the power of the multiple adaptation strategy with respect to the control parameters and search mechanisms and is tested on the benchmark functions taken from the CEC 2021 special session & competition on single-objective bound-constrained optimization.