Prof. Dr. Tobias Friedrich


Three papers accepted, one paper each at ACDA, SAT and FGVC@CVPR

The new SIAM Conference on Applied and Computational Discrete Algorithms (ACDA) brings together researchers who design and study combinatorial and graph algorithms motivated by applications. It subsumes the long-running series of SIAM Workshops on Combinatorial Scientific Computing, and expands its scope to applications of discrete models and algorithms across various sciences. The Algorithm Engineering group is proud to contribute one paper to this novel conference, held on July 19-21, 2021. In the paper, the authors present a new combinatorial model for identifying regulatory modules in gene co-expression data using a decomposition into weighted cliques. They present two parameterized algorithms for solving this combinatorial problem using matrix decomposition techniques and test them on a biologically inspired synthetic corpus.

The Algorithm Engineering group announces that another paper got accepted at this years edition of the International Conference on Theory and Applications of Satisfiability Testing (SAT) (held in Barcelona, Spain, July 5-9, 2021) which is the premier annual meeting for researchers focusing on the theory and applications of the propositional satisfiability problem, including Boolean optimization, Quantified Boolean Formulas, Satisfiability Modulo Theories, Model Counting, and many more. While it is known that satisfiable (uniform) random k-SAT instances are easy to solve with simple greedy heuristics if the clause-variable ratio is at least logarithmic, the authors show that the same holds if the distribution of variables is non-uniform as long it is not too heavy-tailed. Prominent examples of such distributions apart from the uniform one are power law distributions and geometric distributions.

Lastly, the Algorithm Engineering group contributes one paper to the Eighth Workshop on Fine-Grained Visual Categorization (FGVC) which is organized in conjunction with the IEEE Conference on Computer Vision and Pattern Recognition (CVPR). This venue brings together researchers working on the fine-grained categorization of many similar classes. In the paper, stemming from the project seminar Competitive Programming with Deep Learning, the authors use binary classification methods and weighted box fusions to detect and classify various lung diseases.

  • Cooley, Madison; Greene, Casey; Issac, Davis; Pividori, Milton; Sullivan, BlairParameterized Algorithms for Identifying Gene Co-Expression Modules via Weighted Clique Decomposition. Applied and Computational Discrete Algorithms (ACDA) 2021
  • Friedrich, Tobias; Neumann, Frank; Rothenberger, Ralf; Sutton, Andrew M.Solving Non-Uniform Planted and Filtered Random SAT Formulas Greedily. Theory and Applications of Satisfiability Testing (SAT) 2021
  • Fine-Grained Localization... - Download
    Berger, Julian; Bleidt, Tibor; Büßemeyer, Martin; Ding, Marcus; Feldmann, Moritz; Feuerpfeil, Moritz; Jacoby, Janusch; Schröter, Valentin; Sievers, Bjarne; Spranger, Moritz; Stadlinger, Simon; Wullenweber, Paul; Cohen, Sarel; Doskoč, Vanja; Friedrich, TobiasFine-Grained Localization, Classification and Segmentation of Lungs with Various Diseases. CVPR Workshop on Fine-Grained Visual Categorization (FGVC@CVPR) 2021