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Browsing Electronics and Communication Engineering by Author "Majumdar, Angshul (Advisor)"

Browsing Electronics and Communication Engineering by Author "Majumdar, Angshul (Advisor)"

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  • Analysis dictionary learning for classification 
    Bhattacharjee, Protim; Majumdar, Angshul (Advisor) (2016-09-13)
    Data classification is the core of leading technologies today. With the explosion of data through mobility and growth of the Internet, analysis and classification of data is the immediate process after acquisition. Most ...
  • Class-wise deep dictionary learning 
    Khurana, Prerna; Majumdar, Angshul (Advisor) (2016-09-13)
    In this work we propose a classification framework called class-wise deep dictionary learning (CWDDL). For each class, multiple levels of dictionaries are learnt using features from the previous level as inputs (for first ...
  • A computational approach to assist healthcare professionals in selecting antibacterial drugs to treat bacterial infections 
    Chatterjee, Sayantika; Majumdar, Angshul (Advisor) (IIIT-Delhi, 2023-05)
    The reproducibility of experiments has been a long-standing obstruction for farther scientific evolution. Computational methods are being involved to accelerate and to economize drug discovery and the development process. ...
  • Deep dictionary learning 
    Tariyal, Snigdha; Majumdar, Angshul (Advisor) (2016-09-13)
    This Thesis focuses on combining the two well researched concepts of representation learning – Dictionary Learning and Deep Learning. These two learning paradigms have been known for long. Ever since, plethora of papers ...
  • Deep dictionary learning 
    Singhal, Vanika; Majumdar, Angshul (Advisor) (IIIT-Delhi, 2019-08)
    Currently there are three basic frameworks in deep learning - stacked autoencoders (SAE), deep belief network (DBN) and convolutional neural network (CNN); SAE and DBN can be applied to arbitrary inputs but CNN can only ...
  • Latent factor models for collaborative filtering 
    Gogna, Anuprriya; Majumdar, Angshul (Advisor) (IIIT-Delhi, 2017-04)
    The enormous growth in online availability of information content has made Recommender Systems (RS) an integral part of most online portals and e-commerce sites. Most websites and service portals, be it movie rental services, ...
  • Learning algorithms for non intrusive load monitoring 
    Singh, Shikha; Majumdar, Angshul (Advisor) (IIIT-Delhi, 2022-07)
    Non-Intrusive Load Monitoring (NILM), also known as Energy Disaggregation, is the process of segregating a building’s total electricity consumption into its appliances by appliance consumption from the smart meter data. ...
  • Regularized autoencoders 
    Gupta, Kavya; Majumdar, Angshul (Advisor) (2016-11-09)
    Autoencoders are Neural Networks trained in order to map input to its output. Autoencoders are designed to enable the network to copy input to output as close as possible. Following this, the network will be able to learn ...
  • Robust autoencoders 
    Mehta, Janki; Majumdar, Angshul (Advisor) (2016-09-13)
    An autoencoder is an artificial neural network used for learning efficient codings. The aim of an autoencoder is to learn a representation of data, which can then be used for better classification or any such application. ...

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