Raghu Vamshi Hemadri

Iteratively Reweighted Minimax-Concave Penalty Minimization for Accurate Low-rank Plus Sparse Matrix Decomposition

Last Updated: 6th Jan 2021

  Low-rank plus sparse matrix decomposition (LSD) is an important problem in computer vision and machine learning. It has been solved using convex relaxations of the matrix rank and `0-pseudo-norm, which are the nuclear norm and `1-norm, respectively. Convex approximations are known to result in biased estimates, to overcome which, nonconvex regularizers such as weighted nuclear-norm minimization and...

ChildrEN SafEty Retrieval (CENSER) System for Retrieval of Kidnapped Children from Brothels in India using the Memory Augmented ScatterNet ResNet Hybrid (MSRHN) Network

Last Updated: 6th Jan 2021

  Human child trafficking has become a global epidemic with over 10 million children forced into labor or prostitution. Children kidnapped from poverty-stricken sections of India have been especially vulnerable due to the lack of initiative from law enforcement agencies to retrieve them. The facial image of the children is...

AEVB-Comm: An Intelligent Communication System based on AEVBs

Last Updated: 6th Jan 2021

  In recent years, applying Deep Learning (DL) techniques emerged as a common practice in the communication system, demonstrating promising results. The present paper proposes a new Convolutional Neural Network (CNN) based Variational Autoencoder (VAE) communication system. The continuous latent space based communication systems confer unprecedented improvement in…

  I am a 2021 B.Tech graduate student at the National Institute of Technology, Warangal, from Electronics and Communication Engineering. I started research in machine learning in my freshman year of UG. My propensity to research led me to take up various internships and research projects during my undergraduate study. I have collaborations at the Indian Institute of Science, Bangalore; the Indian Institute of Technology, Dharwad, and I also worked as a part-time Machine Learning Researcher at Skylark Labs LLC.

  During my projects, I explored various domains of ML including non-convex optimization, Deep Learning, Computer Vision, Deep Reinforcement Learning, and Meta learning. I'm currently seeking positions to pursue MSc or a Ph.D.

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