Now showing items 301-320 of 561

    • P3 : An Effective Technique for Partitioned Path Profiling 

      Afraz, Mohammed
      Acyclic path profile is an abstraction of dynamic control flow paths of procedures and has been found to be useful in a wide spectrum of activities. Unfortunately, the runtime overhead of obtaining such a profile can be ...
    • Constant-rate Non-malleable Codes and their Applications 

      Obbattu, Sai Lakshmi Bhavana
      Non-malleable codes(NMC) introduced by Dziembowski, Pietrzak and Wichs in ITCS 2010, provide powerful security guarantees where error-correcting codes can not provide any guarantee: a decoding of tampered codeword is ...
    • Model Extraction Defense using Modified Variational Autoencoder 

      Gupta, Yash
      Machine Learning as a Service (MLaaS) exposes machine learning (ML) models that are trained on confidential datasets to users in the form of an Application Programming Interface (API). Since the MLaaS models are deployed ...
    • FA RCU: Fault Aware Read-Copy-Update 

      Dubey, Abhishek
      Deferred freeing is the fundamental technique used in Read-Copy-Update (RCU) synchronization technique where reclamation of resources is deferred until the completion of all active RCU read-side critical sections. We observe ...
    • Novel Neural Architecture for Multi-Hop Question Answering 

      Bhargav, G P Shrivatsa
      Natural language understanding has been one of the key drivers responsible for advancing the eld of AI. To this end, automated Question Answering (QA) has served as an effective way of measuring the language understanding ...
    • Model Extraction and Active Learning 

      Shukla, Aditya
      Machine learning models are increasingly being offered as a service by big companies such as Google, Microsoft and Amazon. They use Machine Learning as a Service (MLaaS) to expose these machine learning models to the ...
    • Modeling and Adaptive Scheduling Strategies for Distributed Graph Algorithms 

      Dindokar, Ravikant Devidas
      Graph processing at scales of millions-billions of vertices and edges has become common to solve real-world problems in domains like social networks, smart cities and genomics. Distributed "Big Data" platforms for graph ...
    • Model Checking Temporal Properties of Presburger Counter Systems 

      Kommineni, Vasanta Lakshmi
      Counter systems are a well-known and powerful modeling notation for specifying infnite state systems. In this thesis we target the problem of checking temporal properties of counter systems. We address three predominant ...
    • Deep Learning for Bug Localization and Program Repair 

      Gupta, Rahul
      In this thesis, we focus on the problem of program debugging and present novel deep learning based techniques for bug-localization and program repair. Deep learning techniques have been successfully applied to a variety ...
    • Deep Learning with Minimal Supervision 

      Pandey, Gaurav
      Abstract In recent years, deep neural networks have achieved extraordinary performance on supervised learning tasks. Convolutional neural networks (CNN) have vastly improved the state of the art for most computer vision ...
    • Geometric and Topological Methods for Biomolecular Visualization 

      Masood, Talha Bin
      Biomolecules like proteins are the basic building blocks of living systems. It has been observed that the structure of a biomolecule plays an important role in defining its function. In this thesis, we describe novel ...
    • An Improved Lower Bound for Multi-r-ic Depth Four Circuits as a Function of the Number of Input Variables 

      Hegde, Sumant
      In this work we study the multi-r-ic formula model introduced by [KS15c] and improve upon the lower bound for multi-r-ic depth four circuits given in [KST16b], when viewed as a function of the number of input variables ...
    • Approximation Algorithms for Geometric Packing and Covering Problems 

      Roy, Aniket Basu
      We study a host of geometric optimization problems that are NP-hard and design polynomial time approximation algorithms for them. More precisely, we are given a family of geometric objects and a point set, mostly in the ...
    • Deep Learning Models for Few-shot and Metric Learning 

      Mehrotra, Akshay
      Deep neural network-based models have achieved unprecedented performance levels over many tasks in the traditional supervised setting and scale well with large quantities of data. On the other hand, improving performance ...
    • Utilizing Worker Groups And Task Dependencies in Crowdsourcing 

      Ojha, Prakhar
      Crowdsourcing has emerged as a convenient mechanism to collect human judgments on a variety of tasks, ranging from document and image classification to scientific experimentation. However, in recent times crowdsourcing has ...
    • Heterogeneity Aware Shared DRAM Cache for Integrated Heterogeneous Architectures 

      Patil, Adarsh
      Integrated Heterogeneous System (IHS) processors pack throughput-oriented GPGPUs along-side latency-oriented CPUs on the same die sharing certain resources, e.g., shared last level cache, network-on-chip (NoC), and the ...
    • Fully Resilient Non-Interactive ID-Based Hierarchical Key Agreement 

      Tiwari, Mayank
      Non-Interactive Key Agreement (NIKA) is a cryptographic primitive which allows two parties to agree on a shared secret key without any interaction. Identity-based Non-Interactive Key Agreement (ID-NIKA) allows each party ...
    • An Exploratory Framework for Cyclone Identification and Tracking 

      Valsangkar, Akash Anil
      Analyzing depressions plays an important role in meteorology, especially in the study of cyclones. In particular, the study of the temporal evolution of cyclones requires a robust depression tracking framework. To cope ...
    • Computing Contour Tress for 2D Piecewise Polynomial Functions 

      Nucha, Girijanandan
      Contour trees are extensively used in scalar field analysis. The contour tree is a data structure that tracks the evolution of level set topology in a scalar field. Scalar fields are typically available as samples at ...
    • New Models and Methods for Formation and Analysis of Social Networks 

      Dhamal, Swapnil
      Social networks are an inseparable part of human lives, and play a major role in a wide range of activities in our day-to-day as well as long-term lives. The rapid growth of online social networks has enabled people to ...