Browsing Division of Electrical, Electronics, and Computer Science (EECS) by Title
Now showing items 792-811 of 1531
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Label Efficient and Generalizable No-reference Video Quality Assessment
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 ... -
Labelled clustering and its applications
Clustering is a process of grouping a collection of objects. Clustering approaches can be broadly categorized into conventional and knowledge-based approaches. In a conventional approach, objects are typically represented ... -
Lambda Bipolar Transistor (LBT) in Static Random Access Memory Cell
(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
(2011-09-26) -
Language Support for Exploiting Software Structure Specifications
(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 Exploiting Software Structure Specifications
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 in ... -
Language Support For Testing CORBA Based Applications
(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
(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
(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
(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
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 ... -
Lattice Codes for Secure Communication and Secret Key Generation
(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
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
(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
(2012-05-04) -
Learning Dynamic Prices In Electronic Markets
(2011-04-19) -
Learning From Examples Using Hierarchical Counterfactual Expressions
In this study, we develop algorithms for learning concepts from examples. Learning is the capability that allows a system to improve its performance. It involves the ability to correct errors, learn domain knowledge, ... -
Learning Invariants for Verification of Programs and Control Systems
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
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 ...