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.

  • Efficient Character-level Document Classification by Combining Convolution and Recurrent Layers


    year of publication: 2016 arXiv

    • Computation and Language
  • Nonlinearities and Adaptation of Color Vision from Sequential Principal Curves Analysis


    year of publication: 2016 arXiv

    • Machine Learning
    • Neurons and Cognition
  • Impurity entropy of junctions of multiple quantum wires


    year of publication: 2016 arXiv

    • Strongly Correlated Electrons
  • Active Particles in Complex and Crowded Environments


    year of publication: 2016 arXiv

    • Soft Condensed Matter
  • Hyperbolicity and genuine nonlinearity conditions for certain p-systems of conservation laws, weak solutions and the entropy condition


    year of publication: 2016 arXiv

    • Analysis of PDEs
  • CoCos under short-term uncertainty


    year of publication: 2016 arXiv

    • Mathematical Finance
  • Fast In-Memory SQL Analytics on Graphs


    year of publication: 2016 arXiv

    • Databases
  • Roots of Sparse Polynomials over a Finite Field


    year of publication: 2016 arXiv

    • Number Theory
  • On Time Correlations for KPZ Growth in One Dimension


    year of publication: 2016 arXiv

    • Mathematical Physics
    • Probability
    • Statistical Mechanics
  • Reachability in Two-Dimensional Unary Vector Addition Systems with States is NL-Complete


    year of publication: 2016 arXiv

    • Logic in Computer Science
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