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    • Division of Electrical, Electronics, and Computer Science (EECS)
    • Browsing Division of Electrical, Electronics, and Computer Science (EECS) by Title
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    • Division of Electrical, Electronics, and Computer Science (EECS)
    • Browsing Division of Electrical, Electronics, and Computer Science (EECS) by Title
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    Browsing Division of Electrical, Electronics, and Computer Science (EECS) by Title

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    Now showing items 676-695 of 1316

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      • Label Efficient and Generalizable No-reference Video Quality Assessment 

        Mitra, Shankhanil
        No-reference (NR) video quality assessment (VQA) refers to the study of the quality of degraded videos without the need for reference pristine videos. The problem has wide applications ranging from the quality assessment ...
      • Lambda Bipolar Transistor (LBT) in Static Random Access Memory Cell 

        Sarkar, Manju (Indian Institute of Science, 2005-07-07)
        With a view to reduce the number of components in a Static Random Access Memory (SRAM) cell, the feasibility of use of Lambda Bipolar Transistor (LBT)in the bistable element of the cell has been explored under the present ...
      • Language Identification Through Acoustic Sub-Word Units 

        Sai Jayram, A K V (2011-09-26)
      • Language Support for Exploiting Software Structure Specifications 

        Kumar, Bharath M (Indian Institute of Science, 2005-02-16)
        Precise specification of the architecture and design of software is a good practice. Such specifications contain a lot of information about the software that can potentially be exploited by tools, to reduce redundancy ...
      • Language Support For Testing CORBA Based Applications 

        Vardhan, K Ananda (Indian Institute of Science, 2005-12-07)
        Component Based Development has emerged as economical, reusable, scalable way of developing enterprise as well as embedded software applications. Testing distributed component based systems is difficult when third party ...
      • Large Data Clustering And Classification Schemes For Data Mining 

        Babu, T Ravindra (2009-03-20)
        Data Mining deals with extracting valid, novel, easily understood by humans, potentially useful and general abstractions from large data. A data is large when number of patterns, number of features per pattern or both are ...
      • Large Scale Graph Processing in a Distributed Environment 

        Upadhyay, Nitesh (2018-05-25)
        Graph algorithms are ubiquitously used across domains. They exhibit parallelism, which can be exploited on parallel architectures, such as multi-core processors and accelerators. However, real world graphs are massive in ...
      • Large Scale Implementation Of The Block Lanczos Algorithm 

        Srikanth, Cherukupally (2010-08-16)
        Large sparse matrices arise in many applications, especially in the major problems of Cryptography of factoring integers and computing discrete logarithms. We focus attention on such matrices called sieve matrices generated ...
      • Large Time Behaviour and Metastability in Mean-Field Interacting Particle Systems 

        Yasodharan, Sarath Ampadi
        This thesis studies the large time behaviour and metastability in weakly interacting Markov processes with jumps. Our motivation is to quantify the large time behaviour of various networked systems that arise in practice. The ...
      • Large-Scale Integer And Polynomial Computations : Efficient Implementation And Applications 

        Amberker, B B (2012-05-03)
      • Lattice Codes for Secure Communication and Secret Key Generation 

        Vatedka, Shashank (2018-05-22)
        In this work, we study two problems in information-theoretic security. Firstly, we study a wireless network where two nodes want to securely exchange messages via an honest-but-curious bidirectional relay. There is no ...
      • A Learnable Distillation Approach For Model-agnostic Explainability With Multimodal Applications 

        Bhattacharya, Debarpan
        Deep neural networks are the most widely used examples of sophisticated mapping functions from feature space to class labels. In the recent years, several high impact decisions in domains such as finance, healthcare, law ...
      • Learning Algorithms Using Chance-Constrained Programs 

        Jagarlapudi, Saketha Nath (2010-07-08)
        This thesis explores Chance-Constrained Programming (CCP) in the context of learning. It is shown that chance-constraint approaches lead to improved algorithms for three important learning problems — classification with ...
      • Learning Decentralized Goal-Based Vector Quantization 

        Gupta, Piyush (2012-05-04)
      • Learning Dynamic Prices In Electronic Markets 

        Venkata Lakshmipathi Raju, CH (2011-04-19)
      • 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 ...
      • Learning Non-linear Mappings from Data with Applications to Priority-based Clustering, Prediction, and Detection 

        Machireddy, Amrutha
        With the volume of data generated in today's internet-of-things, learning algorithms to extract and understand the underlying relations between the various attributes of data have gained momentum. This thesis is focused ...
      • Learning Robust Support Vector Machine Classifiers With Uncertain Observations 

        Bhadra, Sahely (2015-08-19)
        The central theme of the thesis is to study linear and non linear SVM formulations in the presence of uncertain observations. The main contribution of this thesis is to derive robust classfiers from partial knowledge of ...
      • 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 ...
      • Learning Tournament Solutions from Preference-based Multi-Armed Bandits 

        Siddartha, Y R
        We consider the dueling bandits problem, a sequential decision task where the goal is to learn to pick `good' arms out of an available pool by actively querying for and observing relative preferences between selected pairs ...

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