Abstract
We study the power of Arthur-Merlin probabilistic proof systems in the data stream model. We show a canonical AM streaming algorithm for a class of data stream problems. The algorithm offers a tradeoff between the length of the proof and the space complexity that is needed to verify it. As an application, we give an AM streaming algorithm for the Distinct Elements problem. Given a data stream of length m over alphabet of size n, the algorithm uses Õ(s) space and a proof of size Õ(w), for every s,w such that s•w>n (where Õ hides a polylog(m,n) factor). We also prove a lower bound, showing that every MA streaming algorithm for the Distinct Elements problem that uses s bits of space and a proof of size w, satisfies s•w=Ω(n). Furthermore, the lower bound also holds for approximating the number of distinct elements within a multiplicative factor of 1±1/n. As a part of the proof of the lower bound for the Distinct Elements problem, we show a new lower bound of Ω(n) on the MA communication complexity of the Gap Hamming Distance problem, and prove its tightness.
Original language | English (US) |
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Pages (from-to) | 145-165 |
Number of pages | 21 |
Journal | Information and Computation |
Volume | 243 |
DOIs | |
State | Published - Jul 28 2015 |
Externally published | Yes |
All Science Journal Classification (ASJC) codes
- Theoretical Computer Science
- Information Systems
- Computer Science Applications
- Computational Theory and Mathematics
Keywords
- Communication complexity
- Data streams
- Probabilistic proof systems