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    Capacity Computation and Coding for Input-Constrained Channels 

    Rameshwar, Arvind V
    The setting of the transmission of information over noisy, binary-input, memoryless channels is today well-understood, owing to the work of several information theorists, beginning with Claude Shannon. It is known that it ...

    Group Testing: A Probably Approximately Correct Analysis and Recovery Algorithms for pooled RT-qPCR 

    Bharadwaja, Sameera H
    The goal of group testing, also called pool testing, is to successfully identify a set of k defectives from a population of n items using only m (< n) group tests. In each group test, a subset of the n items is tested ...

    Compression for Distributed Optimization and Timely Updates 

    Mayekar, Prathamesh
    The goal of this thesis is to study the compression problems arising in distributed computing systematically. In the first part of the thesis, we study gradient compression for distributed first-order optimization. We ...

    Support Recovery from Linear Measurements: Tradeoffs in the Measurement-Constrained Regime 

    Ramesh, Lekshmi
    In this thesis, we study problems under the theme of discovering joint sparsity structure in a set of high-dimensional data samples from linear measurements. Our primary focus is on the regime where the number of samples ...

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    AuthorBharadwaja, Sameera H (1)Mayekar, Prathamesh (1)Ramesh, Lekshmi (1)Rameshwar, Arvind V (1)Subject
    Information Theory (4)
    TECHNOLOGY (4)
    Capacity Computation (1)Coding Schemes (1)Combinatorial Orthogonal Matching Pursuit (1)Covid-19 (1)decoding algorithms (1)Definite Defectives (1)Federated Learning (1)Finite-State Channels (1)... View MoreHas File(s)Yes (4)

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