Publications with Michael Mitzenmacher
Wear minimization for cuckoo hashing: how not to throw a lot of eggs into one basket.
D. Eppstein, M. T. Goodrich, M .Mitzenmacher, and P. Pszona.
arXiv:1404.0286.
Proc. 13th International Symposium on Experimental Algorithms (SEA 2014), Copenhagen, Denmark, 2014.
Springer, Lecture Notes in Comp. Sci. 8504, pp. 162–173, 2014.We study cuckoo hashing data structures in a model of flash memory in which each memory cell has a limited number of times it can be changed, so the goal is to prevent hot spots that change many times.
Models and algorithms for graph watermarking.
D. Eppstein, M. T. Goodrich, J. Lam, N. Mamano, M. Mitzenmacher, and M. Torres.
arXiv:1605.09425.
Proc. 19th Information Security Conference (ISC 2016), Honolulu, Hawaii.
Springer, Lecture Notes in Comp. Sci. 9866 (2016), pp. 283–301.We show how to modify a small number of edges in a large social network in order to make the modified copy easy to identify, even if an adversary tries to hide the modification by permuting the vertices and flipping a much larger number of edges. The result depends on the random fluctuation of vertex degrees in such networks, and the ability to uniquely identify vertices by their adjacencies to a small number of high-degree landmark vertices. This paper won the best student paper award at ISC for its student co-authors Lam, Mamano, and Torres.
2-3 cuckoo filters for faster triangle listing and set intersection.
D. Eppstein, M. T. Goodrich, M. Mitzenmacher, and M. Torres.
Proc. 36th ACM SIGMOD-SIGACT-SIGAI Symposium on Principles of Database Systems (PODS 2017), Chicago, 2017, pp. 247–260.We show that bit-parallel algorithm design techniques, on a machine of word size w, can speed up the time for sparse set intersection by a factor of log w/w. The main data structure underlying our algorithms is the cuckoo filter, a variant of cuckoo hash tables that has operations similar to a Bloom filter but outperforms Bloom filters in several respects.