What is Problem Mining? This is a tool based on data of arXiv.org which periodically scans packets of full texts of papers hosted on arXiv and available through arXiv's bulk data access policy, with the aim to automatically detect papers containing discussions on open problems or conjectures. It then creates a list from the detected papers putting together papers' descriptive data and some short snippets extracted from the full texts displaying an information on open problems or conjectures presented in the paper. The papers appearing on this list are only references to the arXiv's versions and we do NOT store the actual papers (TeX sources or PDFs) on our servers. To read any of the papers in this list one needs to follow the arXiv link displayed on the papers' blocks.

You can search within the list using keywords, author names, and subject area. By a simple click of the Interesting button, you may anonymously indicate your interest in the problem. If you think the automatic extraction resulted in incorrect data, you may click on the False positive button instead. The Stats section shows the worldwide interest by our users on a specific problem.

  • Stochastic Localization + Stieltjes Barrier = Tight Bound for Log-Sobolev


    year of publication: 2017 arXiv

    • Functional Analysis
    • Probability
  • Arithmetic Progression Hypergraphs: Examining the Second Moment Method


    year of publication: 2017 arXiv

    • Data Structures and Algorithms
  • Effect of the cosmological constant on the deflection angle by a rotating cosmic string


    year of publication: 2017 arXiv

  • Open problems in geometry of continued fractions


    year of publication: 2017 arXiv

    • Combinatorics
    • Number Theory

    MSC 2010: 52B20

  • Specialization Models of Network Growth


    year of publication: 2017 arXiv

    • Dynamical Systems
    • Physics and Society
    • Social and Information Networks

    MSC 2010: 05C82 37H99

  • Simulation of Quantum Walks and Fast Mixing with Classical Processes


    year of publication: 2017 arXiv

    MSC 2010: 05C85 60G50 60J10 68R10

  • Eigendecompositions of Transfer Operators in Reproducing Kernel Hilbert Spaces


    year of publication: 2017 arXiv

    • Dynamical Systems
    • Machine Learning
  • A New Strategy for Riemann Hypothesis


    year of publication: 2017 arXiv

    • Number Theory
  • An Efficient Quantum Compiler that reduces $T$ count


    year of publication: 2017 arXiv

  • Chains of Semiprime and Prime Ideals in Leavitt Path Algebras


    year of publication: 2017 arXiv

    • Rings and Algebras

    MSC 2010: 16D25 16W10

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