Computer Science and Automation (CSA): Recent submissions
Now showing items 41-60 of 377
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Improved Algorithms for Variants of Bin Packing and Knapsack
We study variants of two classical optimization problems: Bin Packing and Knapsack. Both bin packing and knapsack fall under the regime of "Packing and Covering Problems". In bin packing, we are given a set of input items, ... -
Performance Characterization and Optimizations of Traditional ML Applications
Even in the era of Deep Learning based methods, traditional machine learning methods with large data sets continue to attract significant attention. However, we find an apparent lack of a detailed performance characterization ... -
Operating System Support for Efficient Virtual Memory
Computers rely on the virtual memory abstraction to simplify programming, portability, physical memory management and ensure isolation among co-running applications. However, it creates a layer of indirection in the ... -
Explainable and Efficient Neural Models for Natural Language to Bash Command Translation
One of the key goals of Natural Language Processing is to make computers understand natural language. Semantic Parsing has been one of the driving tasks for Natural Language Understanding. It is formally defined as the ... -
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 ... -
2-Level Page Tables (2-LPT): A Building Block for Efficient Address Translation in Virtualized Environments
Efficient address translation mechanisms are gaining more and more attention as the virtual address range of the processors keeps expanding and the demand for machine virtualization increases with cloud and data center-based ... -
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 ... -
Reinforcement Learning Algorithms for Off-Policy, Multi-Agent Learning and Applications to Smart Grids
Reinforcement Learning (RL) algorithms are a popular class of algorithms for training an agent to learn desired behavior through interaction with an environment whose dynamics is unknown to the agent. RL algorithms ... -
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 ... -
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 ... -
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) ... -
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. ... -
Security of Post-Quantum Multivariate Blind Signature Scheme: Revisited and Improved
Current cryptosystems face an imminent threat from quantum algorithms like Shor's and Grover's, leading us to post-quantum cryptography. Multivariate signatures are prominent in post-quantum cryptography due to their fast, ... -
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 ... -
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 ... -
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 ... -
A Syntactic Neural Model For Question Decomposition
Question decomposition along with single-hop Question Answering (QA) system serve as useful modules in developing multi-hop Question Answering systems, mainly because the resulting QA system is interpretable and has been ... -
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 ... -
Extending Program Analysis Techniques to Web Applications and Distributed Systems
Web-based applications and distributed systems are ubiquitous and indispensable today. These systems use multiple parallel machines for greater functionality, and efficient and reliable computation. At the same time they ... -
Statistical Network Analysis: Community Structure, Fairness Constraints, and Emergent Behavior
Networks or graphs provide mathematical tools for describing and analyzing relational data. They are used in biology to model interactions between proteins, in economics to identify trade alliances among countries, in ...