Browsing by Title
Now showing items 3040-3059 of 6408
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Laser-based Diagnostics and Numerical Simulations of Syngas Combustion in a Trapped Vortex Combustor
(2017-11-16)Syngas consisting mainly of a mixture of carbon monoxide, hydrogen and other diluents, is an important fuel for power generation applications since it can be obtained from both biomass and coal gasification. Clean coal ... -
Lattice Boltzmann Relaxation Scheme for Compressible Flows
(2018-03-09)Lattice Boltzmann Method has been quite successful for incompressible flows. Its extension for compressible (especially supersonic and hypersonic) flows has attracted lot of attention in recent time. There have been ... -
Lattice Boltzmann Relaxation Schemes for High Speed Flows
The lattice Boltzmann method (LBM) has emerged as a highly efficient model for the simulation of incompressible flows in the last few decades. Its extension to compressible flows is hindered by the fact that 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 ... -
Layered Metal Dichalcogenides-Based Hybrid Devices for Resistive Sensing
During the past few decades, photodetectors (PDs) are being regarded as the crucial components of many photonic devices which are being used in various important applications. However, the PDs based on the traditional bulk ... -
Layered Oxides And Phosphates Of Bismuth: New Structural Types And Related Properties
(Indian Institute of Science, 2007-05-22)The thesis entitled "Layered Oxides and Phosphates of Bismuth: New Structural Types and Related Properties" consists of three parts and six chapters. It begins with an introductory note providing a brief overview of the ... -
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 Across Domains: Applications to Text-based Person Search and Multi-Source Domain Adaptation
With rapid development in technology and ubiquitous presence of diverse types of sensors, a large amount of data from different modalities (e.g., text, audio, images etc.) describing the same person/ object/event has ... -
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 Compact Architectures for Deep Neural Networks
(2018-05-22)Deep neural networks with millions of parameters are at the heart of many state of the art computer vision models. However, recent works have shown that models with much smaller number of parameters can often perform just ... -
Learning Decentralized Goal-Based Vector Quantization
(2012-05-04) -
Learning Dynamic Prices In Electronic Markets
(2011-04-19) -
Learning Filters, Filterbanks, Wavelets and Multiscale Representations
The problem of filter design is ubiquitous. Frequency selective filters are used in speech/audio processing, image analysis, convolutional neural networks for tasks such as denoising, deblurring/deconvolution, enhancement, ... -
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 ... -
Learning Robust Support Vector Machine Classifiers With Uncertain Observations
(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
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 to Perceive Humans From Appearance and Pose
Analyzing humans and their activities takes a central role in computer vision. This requires machine learning models to encapsulate both the diverse poses and appearances exhibited by humans. Estimating the 3D poses of ...