Computational complexity studies the amount of resources (such as time, space, randomness, or communication) that are necessary to solve computational problems in various models of computation. Finding efficient algorithms for solving computational tasks is crucial for practical applications. Despite a long line of research, for many problems that arise in practice it is not known if they can be solved efficiently – in particular in polynomial time. Beside questions about the existence of polynomial time algorithms for problems like Satisfiability or Factoring, where the best known algorithms run in exponential time, there is a huge class of practical problems where algorithms with polynomial running time (e.g. cubic or even quadratic time) are known, but it would be important to establish whether these running times are best possible, to what extent they can be improved, and whether parallel algorithms allow improvements of the runtime.

These fundamental questions motivate developments in various areas from algorithm design to circuit complexity, communication complexity and coding theory. During this Dagstuhl Seminar, we plan to discuss some of the most exciting recent developments in those areas related to computational complexity.

The bulk of the seminar will be taken up by talks and discussions. The topics will depend on and be driven by the participants, who will share their current research interests in talks, open problem sessions, and smaller group research. The list of topics will include – but not be limited to – subjects such as formula size – especially new results on lower bounds –, complexity measures of Boolean functions, lower bounds for algorithm runtimes arising from connections to Satisfiability problems, the relationship of circuit complexity and fixed parameter tractability, communication complexity, as well as deep learning and circuit complexity.

The seminar is a continuation of the series of Dagstuhl Seminars entitled “Computational Complexity of Discrete Problems” and formerly “Complexity of Boolean Functions.” It will build on the long experience and focus on what has made the series strong in the past: bringing together the leading experts and the exceptionally talented junior researchers to discuss the most exciting recent developments in different areas of computational complexity of discrete problems – both regarding recent results, but also regarding open problems.

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Anna Gál, Oded Regev, Rahul Santhanam, and Till Tantau

• Eric Allender (Rutgers University - Piscataway, US) [dblp]
• Paul Beame (University of Washington - Seattle, US) [dblp]
• Harry Buhrman (CWI - Amsterdam, NL) [dblp]
• Igor Carboni Oliveira (University of Oxford, GB) [dblp]
• Katrin Casel (Hasso-Plattner-Institut - Potsdam, DE) [dblp]
• Amit Chakrabarti (Dartmouth College - Hanover, US) [dblp]
• Sourav Chakraborty (Indian Statistical Institute - Kolkata, IN) [dblp]
• Arkadev Chattopadhyay (TIFR - Mumbai, IN) [dblp]
• Gil Cohen (Princeton University, US) [dblp]
• Anindya De (University of Pennsylvania - Philadelphia, US) [dblp]
• Lukáš Folwarczný (Charles University - Prague, CZ) [dblp]
• Lance Fortnow (Georgia Institute of Technology - Atlanta, US) [dblp]
• Anna Gál (University of Texas - Austin, US) [dblp]
• Alexander Golovnev (Harvard University - Cambridge, US) [dblp]
• Kristoffer Arnsfelt Hansen (Aarhus University, DK) [dblp]
• Prahladh Harsha (TIFR - Mumbai, IN) [dblp]
• Johan Hastad (KTH Royal Institute of Technology, SE) [dblp]
• Valentine Kabanets (Simon Fraser University - Burnaby, CA) [dblp]
• Michael Kapralov (EPFL - Lausanne, CH) [dblp]
• Mathew Katzman (University of Oxford, GB)
• Antonina Kolokolova (Memorial University of Newfoundland - St. John's, CA) [dblp]
• Swastik Kopparty (Rutgers University - Piscataway, US) [dblp]
• Michal Koucký (Charles University - Prague, CZ) [dblp]
• Matthias Krause (Universität Mannheim, DE) [dblp]
• Meena Mahajan (Institute of Mathematical Sciences - Chennai, IN) [dblp]
• Or Meir (University of Haifa, IL) [dblp]
• Jakob Nordström (KTH Royal Institute of Technology - Stockholm, SE) [dblp]
• Ramamohan Paturi (University of California - San Diego, US) [dblp]
• Pavel Pudlák (The Czech Academy of Sciences - Prague, CZ) [dblp]
• Rüdiger Reischuk (Universität zu Lübeck, DE) [dblp]
• Michael E. Saks (Rutgers University - Piscataway, US) [dblp]
• Rahul Santhanam (University of Oxford, GB) [dblp]
• Ronen Shaltiel (University of Haifa, IL) [dblp]
• Amnon Ta-Shma (Tel Aviv University, IL) [dblp]
• Avishay Tal (Stanford University, US) [dblp]
• Till Tantau (Universität zu Lübeck, DE) [dblp]
• Thomas Thierauf (Hochschule Aalen, DE) [dblp]
• Jacobo Torán (Universität Ulm, DE) [dblp]
• Ben Lee Volk (Caltech - Pasadena, US) [dblp]
• Omri Weinstein (Columbia University - New York, US) [dblp]