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Nikhil Bansal

Full Name: Prof.dr. N. Bansal
Function(s): Researcher, Professor - Technische Universiteit Eindhoven

Email: N.Bansal@cwi.nl
Telephone: +31 20 592 4152
Room: M238
Department(s): Networks and Optimization

Publications

Bansal, N, & Spencer, J.H. (2020). On-line balancing of random inputs. Random Structures & Algorithms, 57(4), 879–891. doi:10.1002/rsa.20955
Bansal, N, & Meka, R. (2020). On the discrepancy of random low degree set systems. Random Structures & Algorithms, 57(3). doi:10.1002/rsa.20935
Bansal, N, Jiang, H, Singla, S, & Sinha, M. (2020). Online vector balancing and geometric discrepancy. In Proceedings of the Annual ACM Symposium on Theory of Computing (pp. 1139–1152). doi:10.1145/3357713.3384280
Bansal, N, & Meka, R. (2020). On the discrepancy of random low degree set systems. In Proceedings of the Annual ACM-SIAM Symposium on Discrete Algorithms. doi:10.1137/1.9781611975482.157
Abbasi-Zadeh, S, Bansal, N, Guruganesh, G, Nikolov, A, Schwartz, R, & Singh, M. (2020). Sticky Brownian rounding and its applications to constraint satisfaction problems. In Proceedings of the Annual ACM-SIAM Symposium on Discrete Algorithms (pp. 854–873).
Bansal, N, Dadush, D.N, Garg, S, & Lovett, S. (2019). The Gram-Schmidt Walk: A Cure for the Banaszczyk Blues. Theory of Computing, 15. doi:10.4086/toc.2019.v015a021
Bansal, N, Böhm, M, Eliáš, M, Koumoutsos, G, & Umboh, S.W. (2019). Nested convex bodies are chaseable. Algorithmica. doi:10.1007/s00453-019-00661-x
Bansal, N, Svensson, O, & Trevisan, L. (2019). New notions and constructions of sparsification for graphs and hypergraphs. In Proceedings of FOCS (pp. 910–928). doi:10.1109/FOCS.2019.00059
Bansal, N, Chalermsook, P, Laekhanukit, B, Nanongkai, D, & Nederlof, J. (2019). New Tools and Connections for Exponential-Time Approximation. Algorithmica, 81(10), 3993–4009.
Bansal, N, & Gupta, A. (2019). Potential-function proofs for gradient methods. Theory of Computing, 15. doi:10.4086/toc.2019.v015a004

Current projects with external funding

Continuous Methods in Discrete Optimization ()
Optimization for and with Machine Learning (OPTIMAL)

Grants

Vici (2018)