Now showing items 1-20 of 73

    • Deep representation learning on hypersphere 

      Liu, Weiyang (Georgia Institute of Technology, 2020-07-27)
      How to efficiently learn discriminative deep features is arguably one of the core problems in deep learning, since it can benefit a lot of downstream tasks such as visual recognition, object detection, semantic segmentation, ...
    • Asynchronous Versions of Jacobi, Multigrid, and Chebyshev Solvers 

      Wolfson-Pou, Jordi (Georgia Institute of Technology, 2020-07-06)
      Iterative methods are commonly used for solving large, sparse systems of linear equations on parallel computers. Implementations of parallel iterative solvers contain kernels (e.g., parallel sparse matrix-vector products) ...
    • LEARNING DYNAMIC PROCESSES OVER GRAPHS 

      Trivedi, Rakshit (Georgia Institute of Technology, 2020-07-09)
      Graphs appear as a versatile representation of information across domains spanning social networks, biological networks, transportation networks, molecular structures, knowledge networks, web information network and many ...
    • Large scale machine learning for geospatial problems in computational sustainability 

      Robinson, David Caleb (Georgia Institute of Technology, 2020-05-14)
      The UN laid out 17 Sustainable Development Goals as part of the “The 2030 Agenda for Sustainable Development”. Each goal consists of broad targets - such as increasing the percentage of forested land (indicator 15.1.1) - ...
    • Health Data Mining using Tensor Factorization: Methods and Applications 

      Perros, Ioakeim (Georgia Institute of Technology, 2019-05-16)
      The increasing volume and availability of healthcare and biomedical data is opening up new opportunities for the use of computational methods to improve health. However, the data are diverse, multidimensional and sparse, ...
    • Modeling for inversion in exploration geophysics 

      Louboutin, Mathias (Georgia Institute of Technology, 2020-03-16)
      Seismic inversion, and more generally geophysical exploration, aims at better understanding the earth's subsurface, which is one of today's most important challenges. Firstly, it contains natural resources that are critical ...
    • Software and algorithms for large-scale seismic inverse problems 

      Witte, Philipp Andre (Georgia Institute of Technology, 2020-02-26)
      Seismic imaging and parameter estimation are an import class of inverse problems with practical relevance in resource exploration, carbon control and monitoring systems for geohazards. Seismic inverse problems involve ...
    • Fault-tolerance on near-term quantum computers and subsystem quantum error correcting codes 

      Li, Muyuan (Georgia Institute of Technology, 2020-03-20)
      Large-scale fault-tolerant quantum computers are supposed to provide exponential speedup over many classical algorithms for solving realistic computationally intensive problems. Given that practical quantum computers are ...
    • Learning neural algorithms with graph structures 

      Dai, Hanjun (Georgia Institute of Technology, 2020-01-13)
      Graph structures, like syntax trees, social networks, and programs, are ubiquitous in many real world applications including knowledge graph inference, chemistry and social network analysis. Over the past several decades, ...
    • Towards tighter integration of machine learning and discrete optimization 

      Khalil, Elias (Georgia Institute of Technology, 2019-03-28)
      Discrete Optimization algorithms underlie intelligent decision-making in a wide variety of domains. From airline fleet scheduling to data center resource management and matching in ride-sharing services, decisions are often ...
    • Efficient parallel algorithms for error correction and transcriptome assembly of biological sequences 

      Sachdeva, Vipin (Georgia Institute of Technology, 2018-05-29)
      Next-generation sequencing technologies have led to a big data age in biology. Since the sequencing of the human genome, the primary bottleneck has steadily moved from collection to storage and analysis of the data. The ...
    • Human-centered AI through scalable visual data analytics 

      Kahng, Minsuk Brian (Georgia Institute of Technology, 2019-11-01)
      While artificial intelligence (AI) has led to major breakthroughs in many domains, understanding machine learning models remains a fundamental challenge. How can we make AI more accessible and interpretable, or more broadly, ...
    • AI-infused security: Robust defense by bridging theory and practice 

      Chen, Shang-Tse (Georgia Institute of Technology, 2019-09-20)
      While Artificial Intelligence (AI) has tremendous potential as a defense against real-world cybersecurity threats, understanding the capabilities and robustness of AI remains a fundamental challenge. This dissertation ...
    • Energy efficient parallel and distributed simulation 

      Biswas, Aradhya (Georgia Institute of Technology, 2019-07-26)
      New challenges and opportunities emerge as computing interacts with our surroundings in unprecedented ways. One of these challenges is the energy consumed by computations and communications. In large cloud-based computing ...
    • Cost benefit analysis of adding technologies to commercial aircraft to increase the survivability against surface to air threats 

      Patterson, Anthony (Georgia Institute of Technology, 2018-07-27)
      Flying internationally is an integral part of people's everyday lives. Most United States airlines fly internationally on a daily basis. The world continues to become a more dangerous place, due to improvements to technology ...
    • Techniques to improve genome assembly quality 

      Nihalani, Rahul (Georgia Institute of Technology, 2019-03-28)
      De-novo genome assembly is an important problem in the field of genomics. Discovering and analysing genomes of different species has numerous applications. For humans, it can lead to early detection of disease traits and ...
    • Diagnosing performance bottlenecks in HPC applications 

      Czechowski, Kenneth (Georgia Institute of Technology, 2019-03-29)
      The software performance optimizations process is one of the most challenging aspects of developing highly performant code because underlying performance limitations are hard to diagnose. In many cases, identifying performance ...
    • Long read mapping at scale: Algorithms and applications 

      Jain, Chirag (Georgia Institute of Technology, 2019-04-01)
      Capability to sequence DNA has been around for four decades now, providing ample time to explore its myriad applications and the concomitant development of bioinformatics methods to support them. Nevertheless, disruptive ...
    • Parallel and scalable combinatorial string algorithms on distributed memory systems 

      Flick, Patrick (Georgia Institute of Technology, 2019-03-29)
      Methods for processing and analyzing DNA and genomic data are built upon combinatorial graph and string algorithms. The advent of high-throughput DNA sequencing is enabling the generation of billions of reads per experiment. ...
    • Automated surface finish inspection using convolutional neural networks 

      Louhichi, Wafa (Georgia Institute of Technology, 2019-03-25)
      The surface finish of a machined part has an important effect on friction, wear, and aesthetics. The surface finish became a critical quality measure since 1980s mainly due to demands from automotive industry. Visual ...