Browsing Computer Science and Automation (CSA) by thesis submitted date"2021"
Now showing items 1-20 of 27
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Algorithms for Fair Clustering
Many decisions today are taken by various machine learning algorithms, hence it is crucial to accommodate fairness in such algorithms to remove/reduce any kind of bias in the decision. We incorporate fairness in the ... -
Analysis and Methods for Knowledge Graph Embeddings
Knowledge Graphs (KGs) are multi-relational graphs where nodes represent entities, and typed edges represent relationships among entities. These graphs store real-world facts such as (Lionel Messi, plays-for-team, Barcelona) ... -
Approximation Algorithms for Geometric Packing Problems
We study approximation algorithms for the geometric bin packing problem and its variants. In the two-dimensional geometric bin packing problem (2D GBP), we are given n rectangular items and we have to compute an axis-parallel ... -
Deep Learning over Hypergraphs
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 ... -
Design, Implementation, and Analysis of a TLB-based Covert Channel on GPUs
GPUs are now commonly available in most modern computing platforms. They are increasingly being adopted in cloud platforms and data centers due to their immense computing capability. In response to this growth in usage, ... -
Enhancing Coverage and Robustness of Database Generators
Generating synthetic databases that capture essential data characteristics of client databases is a common requirement for enterprise database vendors. This need stems from a variety of use-cases, such as application testing ... -
A Framework for Privacy-Compliant Delivery Drones
We present Privaros, a framework to enforce privacy policies on drones. Privaros is designed for commercial delivery drones, such as the ones that will likely be used by Amazon Prime Air. Such drones visit a number of host ... -
High Performance GPU Tensor Core Code Generation for Matmul using MLIR
State of the art in high-performance deep learning is primarily driven by highly tuned libraries. These libraries are often hand-optimized and tuned by expert programmers using low-level abstractions with significant effort. ... -
Locally Reconstructable Non-malleable Secret Sharing
Non-malleable secret sharing (NMSS) schemes, introduced by Goyal and Kumar (STOC 2018), ensure that a secret m can be distributed into shares m1,...,mn (for some n), such that any t (a parameter <= n) shares can be ... -
Modeling and verification of database-accessing applications
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
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 ... -
Neural Models for Personalized Recommendation Systems with External Information
Personalized recommendation systems use the data generated by user-item interactions (for example, in the form of ratings) to predict different users interests in available items and recommend a set of items or products ... -
New Algorithmic and Hardness Results in Learning, Error Correcting Codes and Constraint Satisfaction Problems
Approximation algorithms are a natural way to deal with the intractability barrier that is inherent in many naturally arising computational problems. However, it is often the case that the task of solving the approximation ... -
Novel First-order Algorithms for Non-smooth Optimization Problems in Machine Learning
This thesis is devoted to designing efficient optimization algorithms for machine learning (ML) problems where the underlying objective function to be optimized is convex but not necessarily differentiable. Such non-smooth ... -
A Novel Neural Network Architecture for Sentiment-oriented Aspect-Opinion Pair Extraction
Over the years, fine-grained opinion mining in online reviews has received great attention from the NLP research community. It involves different tasks such as Aspect Term Extraction (ATE), Opinion Term Extraction (OTE), ... -
Novel Reinforcement Learning Algorithms and Applications to Hybrid Control Design Problems
The thesis is a compilation of two independent works. In the first work, we develop novel weight assignment procedure, which helps us develop several schedule based algorithms. Learning the value function of a given policy ... -
nuKSM: NUMA-aware Memory De-duplication for Multi-socket Servers
An operating system's memory management has multiple goals, e.g. reducing memory access latencies, reducing memory footprint. These goals can conflict with each other when independent subsystems optimize them in silos. ... -
Quantum-Safe Identity-Based Signature Scheme in Multivariate Quadratic Setting
Cryptographic techniques are essential for the security of communication in modern society. Today, nearly all public key cryptographic schemes used in practice are based on the two problems of factoring large integers and ... -
Recovery Algorithms for planted structures in Semi-random models
For many NP-hard problems, the analysis of best-known approximation algorithms yields “poor” worst-case guarantees. However, using various heuristics, the problems can be solved (to some extent) in real-life instances. ... -
Revisiting Statistical Techniques for Result Cardinality Estimation
The Relational Database Management Systems (RDBMS) constitute the backbone of today's information-rich society, providing a congenial environment for handling enterprise data during its entire life cycle of generation, ...