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Pavel Kolev
Max Planck Institute for Informatics
Department 1: Algorithms and Complexity
Campus E1 4, Room 326
66123 Saarbrücken
Germany
Email:
pkolev
mpi-inf.mpg.de
Phone: +49 681 9325 1026
Links:
Homepage
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LinkedIn
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GitHub
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DBLP
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Google Scholar
I obtained my doctoral degree on 2018 in the Computer Science Department at Saarland University, where I was fortunate to be advised by Prof. Dr. Kurt Mehlhorn and Dr. Karl Bringmann.
During my doctoral studies, I was also affiliated with the Algorithms and Complexity Department at Max Planck Institute for Informatics and the Cluster of Excellence on "Multimodal Computing and Interaction".
Afterwards, I spent a year as a Postdoctoral researcher at the Algorithms and Complexity Department at Max Planck Institute for Informatics,
hosted by Prof. Dr. Kurt Mehlhorn.
- Machine Learning
- Low Rank Approximation
- Physarum Dynamics
- Randomized Linear Algebra
- Spectral Graph Theory
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Physarum Multi-Commodity Flow Dynamics
Vincenzo Bonifaci,
Enrico Facca,
Frederic Folz,
Andreas Karrenbauer,
Pavel Kolev,
Kurt Mehlhorn,
Giovanna Morigi,
Golnoosh Shahkarami,
Quentin Vermande
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Secretary and Online Matching Problems with Machine Learned Advice
Advances in Neural Information Processing Systems 33 (NeurIPS 2020)
Antonios Antoniadis,
Themis Gouleakis,
Pieter Kleer,
Pavel Kolev
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Convergence of the Non-Uniform Directed Physarum Model
Journal of Theoretical Computer Science (TCS), Section C (Theory of Natural Computing).
Enrico Facca,
Andreas Karrenbauer,
Pavel Kolev,
Kurt Mehlhorn
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Convergence of the Non-Uniform Physarum Dynamics
Journal of Theoretical Computer Science (TCS), Section C (Theory of Natural Computing).
Andreas Karrenbauer,
Pavel Kolev,
Kurt Mehlhorn
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A PTAS for $\ell_{0}$-Low Rank Approximation
30th Annual ACM-SIAM Symposium on Discrete Algorithms (SODA 2019)
Frank Ban,
Vijay Bhattiprolu,
Karl Bringmann,
Pavel Kolev,
Euiwoong Lee,
David P. Woodruff
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Approximation Algorithms for $\ell_{0}$-Low Rank Approximation
Advances in Neural Information Processing Systems 30 (NeurIPS 2017)
Karl Bringmann,
Pavel Kolev,
David P. Woodruff
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Two Results on Slime Mold Computations
Journal of Theoretical Computer Science (TCS), Section C (Theory of Natural Computing).
Ruben Becker,
Vincenzo Bonifaci,
Andreas Karrenbauer,
Pavel Kolev,
Kurt Mehlhorn
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Density Independent Algorithms for Sparsifying k-Step Random Walks
20th International Workshop on Approximation Algorithms for Combinatorial Optimization Problems (APPROX/RANDOM 2017)
Gorav Jindal, Pavel Kolev, Richard Peng,
Saurabh Sawlani
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Approximate Spectral Clustering: Efficiency and Guarantees
A preliminary version
of this paper was presented at the 24th Annual European Symposium on Algorithms (ESA 2016)
Pavel Kolev, Kurt Mehlhorn
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An Efficient Parallel Algorithm for Spectral Sparsification of Laplacian and SDDM Matrix Polynomials
Gorav Jindal, Pavel Kolev
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Dirichlet Eigenvalues, Local Random Walks, and Analyzing Clusters in Graphs
25th International Symposium on Algorithms and Computation (ISAAC 2014).
Pavel Kolev, He Sun
- Own Work
- Two Results on Slime Mold Computations:
OR'17
- Seminars
- Gradient Descent only Converges to Minimizers:
ATML-SS17
- Faster spectral sparsification and numerical algorithms for SDD matrices:
RGA-SS17
- Approximate Undirected Maximum Flows in O(m polylog(n)) Time:
RGA-WS16
- Faster Online Matrix-Vector Multiplication:
RGA-SS16
- Streaming Lower Bounds for Approximating MAX-CUT:
ALB-WS15
- Spectral Sparsification and Regret Minimization Beyond Matrix Multiplicative Updates:
RGA-WS15
- Spectral Sparsification of Random-Walk Matrix Polynomials:
RGA-SS15
- Multi-way spectral partitioning and higher-order Cheeger inequalities:
RGA-WS12
- Conflict Packing Yields Linear Vertex-Kernels for k-FAST, k-dense RTI and a Related Problem:
RGA-SS12
- 49th Annual ACM Symposium on the Theory of Computing: June 19 - 23, 2017, Montreal, Canada
- ACM-SIAM Symposium on Discrete Algorithms: January 10 – 29, 2016, Arlington, Virginia, USA
- MADALGO Summer School on Streaming Algorithms: August 10 – 13, 2015, Aarhus University, Denmark
- Conference on Learning Theory: July 3 - 6, 2015, University Pierre and Marie Curie, Paris, France
- Algorithmic Spectral Graph Theory Boot Camp: August 26 – 29, 2014, Simons Institute for the Theory of Computing, UC Berkeley, USA
- ADFOCS Current Trends in Network Optimization: August 11 - 15, 2014, Saarbrücken, Germany
- EADS Summer School on Hashing: Theory and Applications: July 14 – 17, 2014, University of Copenhagen, Denmark
- ADFOCS Current Trends in Theoretical Computer Science: August 13 - 17, 2012, Saarbrücken, Germany
- STOC 2019, JMIV 2018, ITCS 2018, ESA 2017, ICALP 2017, STACS 2017, MFCS 2016
