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Jan Vondrák is a Czech applied mathematician and theoretical computer scientist. He has been a professor of mathematics at Stanford University since 2015. He was a research staff member in the theory group at the IBM Almaden Research Center from 2009 to 2015.
Professor of Mathematics. Dept. of Mathematics Stanford University 450 Jane Lanthrop Way, building 380 Stanford, CA 94305 E-mail: jvondrak-at-stanford-dot-edu. Research interests. Discrete optimization. Matroids and submodular functions. Approximation algorithms. Algorithmic game theory. Probabilistic combinatorics. My papers. Some presentations.
Department of Mathematics Building 380, Stanford, California 94305 Phone: (650) 725-6284 mathwebsite [at] lists.stanford.edu (Email)
18. Aug. 2022 · Jan Vondrak. curriculum vitae. updated August 18, 2022. Current position. Stanford University, Stanford, CA. Professor, Department of Mathematics. Director of Graduate Studies in Mathematics. Previous employment. IBM Almaden Research Center, San Jose, CA. Research sta member, theory group, 2009-15. Princeton University, Princeton, NJ.
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Shahar Dobzinski, Shiri Ron, Jan Vondrak: On the hardness of dominant strategy mechanism design in STOC 2022, 690-703.Zi Yang Kang, Francisco Pernice, Jan Vondrak: Fixed-Price Approximations in Bilateral Trade in SODA 2022, 2964-2985.Wenzheng Li, Jan Vondrak: A constant-factor approximation algorithm for Nash Social Welfare with submodular valuations in FOCS 2021, 25-36.Wenzheng Li, Jan Vondrak: Estimating the Nash Social Welfare for coverage and other submodular valuations in SODA 2021, 1119-1130.Paul Liu, Aviad Rubinstein, Jan Vondrak, Junyao Zhao: Cardinality constrained submodular maximization for random streams in NeurIPS 2021, 6491-6502.Wenzheng Li, Paul Liu, Jan Vondrak: A polynomial lower bound on adaptive complexity of submodular maximization in STOC 2020.Ashwinkumar Badanidiyuru, Amin Karbasi, Ehsan Kazemi, Jan Vondrak: Submodular Maximization Through Barrier Functions in NeurIPS 2020.Vitaly Feldman, Jan Vondrak: High probability generalization bounds for uniformly stable algorithms with nearly optimal rate in COLT 2019.Paul Liu, Jan Vondrak: Submodular Optimization in the MapReduce Model in SOSA 2019.Zi Yang Kang, Jan Vondrak: Fixed-price approximations to optimal efficiency in bilateral trade manuscript, 2019.Vitaly Feldman, Jan Vondrak: Generalization bounds for uniformly stable algorithms in NeurIPS 2018.Nick Harvey, Piyush Srivastava, Jan Vondrak: Computing the independence polynomial: from the tree threshold down to the roots in SODA 2018. full version on arxiv.org:1608.02282Kevin Garbe, Jan Vondrak: Concentration of Lipschitz functions of negatively dependent variables manuscript, 2018.Nick Harvey, Jan Vondrak: Short proofs for generalizations of the Lovasz Local Lemma: Shearer's condition and cluster expansion manuscript, 2017.Vitaly Feldman, Pravesh Kothari, Jan Vondrak: Tight bounds on l1 approximation and learning of self-bounding functions in ALT 2017.Tim Roughgarden, Inbal Talgam-Cohen, Jan Vondrak: When are welfare guarantees robust? in APPROX-RANDOM 2017, 22:1-22:23.Vaggos Chatziafratis, Tim Roughgarden, Jan Vondrak: Stability and recovery for independence systems in ESA 2017, 26:1-26:15.Shahar Dobzinski, Jan Vondrak: Impossibility results for truthful combinatorial auctions with submodular valuations. J. ACM 63(1): 5:1-5:19, 2016.
Maryam Mirzakhani, Jan Vondrak: Sperner's colorings and optimal partitiongs of the simplex in A Journey Through Discrete Mathematics, a tribute to Jiri Matousek, Springer 2017. A conference version...Nick Harvey, Jan Vondrak: An algorithmic proof of the Lovasz Local Lemma via resampling oracles SIAM J. Comput. 49:2, 394-428, 2020 conference version in FOCS 2015.Vitaly Feldman, Jan Vondrak: Tight bounds on low-degree spectral concentration of submodular and XOS functions in FOCS 2015. full version on arxiv.org:1504.03391.Maxim Sviridenko, Jan Vondrak, Justin Ward: Optimal approximation for submodular and supermodular optimization with bounded curvature Math. Oper. Res. 42(4), 1197-1218, 2017; earlier version in SOD...Ankit Sharma, Jan Vondrak: Multiway Cut, pairwise realizable distributions, and descending thresholds in STOC 2014. full version on arxiv.org:1309.2729.T.S. Jayram, Jan Vondrak: Exchangeability and realizability: De Finetti theorems on graphs in RANDOM 2014.Alina Ene, Jan Vondrak: Hardness of Submodular Cost Allocation: Lattice Matching and a simplex coloring conjecture in APPROX 2014.Ashwinkumar B.V., Jan Vondrak: Fast algorithms for maximizing submodular functions in SODA 2014, 1497-1514.Vitaly Feldman, Jan Vondrak: Optimal bounds on approximation of submodular and XOS functions by juntas. SIAM J. Comput. 45(3): 1129-1170, 2016. conference version in FOCS 2013,Vitaly Feldman, Pravesh Kothari, Jan Vondrak: Representation, approximation and learning of submodular functions using low-rank decision trees in COLT 2013, full version on arxiv.org:1304.0730.Michael Kapralov, Ian Post, Jan Vondrak: Online submodular welfare maximization: Greedy is optimal in SODA 2013, 1216-1225. full version on arxiv.org:1204.1025.Shahar Dobzinski, Jan Vondrak: Communication complexity of combinatorial auctions with submodular bidders in SODA 2013, 1205-1215.Wenzheng Li, Paul Liu, Jan Vondrák: A polynomial lower bound on adaptive complexity of submodular maximization. CoRR abs/2002.09130 ( 2020) 2010 – 2019. 2019. [c50] Vitaly Feldman, Jan Vondrák: High probability generalization bounds for uniformly stable algorithms with nearly optimal rate.
Jan Vondrak. professor, Stanford University. Jan Vondrak got his PhD in Applied Mathematics from MIT in 2005. He did postdocs at Microsoft Research and Princeton University, and was a Research Staff Member in the IBM Almaden Research Lab between 2009-15.
