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    Signcryption in a Quantum World 

    Puria, Shravan Kumar Parshuram
    With recent advancements and research on quantum computers, it is conjectured that in the foreseeable future, sufficiently large quantum computers will be built to break essentially all public key cryptosystems currently ...

    Learning to Adapt Policies for uSD card 

    Anand, Abhinav
    Machine Learning(ML) for Systems is a new and promising research area where performance of computer systems is optimized using machine learning methods. ML for Systems has outperformed traditional heuristics methods in ...

    Robust Algorithms for recovering planted structures in Semi-random instances 

    Khanna, Yash
    In this thesis, we study algorithms for three fundamental graph problems. These are NP-hard problems which have not been understood completely as there is a signifiicant gap between the algorithmic and the hardness fronts ...

    Deep Learning over Hypergraphs 

    Yadati, Naganand
    Graphs have been extensively used for modelling real-world network datasets, however, they are restricted to pairwise relationships, i.e., each edge connects exactly two vertices. Hypergraphs relax the notion of edges ...

    Security of Post-Quantum Multivariate Blind Signature Scheme: Revisited and Improved 

    Majumdar, Aalo
    Current cryptosystems face an imminent threat from quantum algorithms like Shor's and Grover's, leading us to post-quantum cryptography. Multivariate signatures are prominent in post-quantum cryptography due to their fast, ...

    Modeling and verification of database-accessing applications 

    Chawla, Geetam
    Databases are central to the functioning of most IT-enabled processes and services. In many domains, databases are accessed and updated via applications written in general-purpose lan- guages, as such applications need ...

    MPCLeague: Robust MPC Platform for Privacy-Preserving Machine Learning 

    Ajith, S
    In the modern era of computing, machine learning tools have demonstrated their potential in vital sectors, such as healthcare and finance, to derive proper inferences. The sensitive and confidential nature of the data in ...

    Learning Invariants for Verification of Programs and Control Systems 

    Ezudheen, P
    Deductive verification techniques in the style of Floyd and Hoare have the potential to give us concise, compositional, and scalable proofs of the correctness of various kinds of software systems like programs and control ...

    On Learning and Lower Bound Problems Related to the Iterated Matrix Multiplication Polynomial 

    Nair, Vineet
    The iterated matrix multiplication polynomial (IMM) of width w and length d is the 1x1 entry in the product of d square matrices of size w. The w^2d entries in the d matrices are distinct variables. In this thesis, we study ...

    Algorithms for Fair Decision Making: Provable Guarantees and Applications 

    Biswas, Arpita
    The topic of fair allocation of indivisible items has received significant attention because of its applicability in several real-world settings. This has led to a vast body of work focusing on defining appropriate fairness ...
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    AuthorAfreen, Ahmad (1)Agarwal, Siddharth (1)Aggarwal, Manasvi (1)Agrawal, Nikhil (1)Ajith, S (1)Allabadi, Swati (1)Anand, Abhinav (1)Arora, Himanshu (1)Arote, Prerna (1)Arpith, K (1)... View MoreSubject
    TECHNOLOGY (142)
    Deep Learning (10)Reinforcement Learning (10)Machine Learning (9)Cryptography (6)Markov Decision Processes (5)Natural Language Processing (5)algorithms (4)Artificial Intelligence (4)Graphs (4)... View MoreHas File(s)
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