Faster Update Time for Turnstile Streaming Algorithms
Speaker: JoshTitle: Faster Update Time for Turnstile Streaming Algorithms
Date: 02 Mar 2020 5:30pm-7:00pm
Location: Maxwell-Dworkin 221
Food: Indian
Abstract: In this talk, I’ll present a new algorithm for maintaining linear sketches in turnstile streams with faster update time. In the turnstile streaming model, the data structure wants to maintain a vector v of n integers, under updates which increment or decrement entries of the vector. Algorithms in this model try to quickly maintain a sketch of v, of size much smaller than n, which can still be used to recover interesting properties of v. Many of the most successful algorithms work by maintaining log n different linear sketches, where each sketch partitions the coordinates into $k<log^{o(1)}$ n buckets using a c-wise independent hash function for constant c, and maintains the sum of coordinates for each bucket. Our new approach improves the update time for maintaining any sketch of this form in the RAM model. All your favorite algorithmic techniques will come into play, including hashing, bit tricks, and matrix multiplication.
Based on joint work with Huacheng Yu.