Abstract
An important result in discrepancy due to Banaszczyk States that for any set of n vectors in Rm of ℓ2 norm at most 1 and any convex body K in Rm of Gaussian measure at least half, there exists a ±1 combination of these vectors which lies in 5K. This result implies the best known bounds for several problems in discrepancy. Banaszczyk’s proof of this result is non-constructive and a major open problem has been to give an efficient algorithm to find such a ±1 combination of the vectors. In this paper, we resolve this question and give an efficient randomized algorithm to find a ±1 combination of the vectors which lies in cK for c > 0 an absolute constant. This leads to new efficient algorithms for several problems in discrepancy theory.
Original language | English |
---|---|
Title of host publication | STOC 2018 - Proceedings of the 50th Annual ACM SIGACT Symposium on Theory of Computing |
Publisher | Association for Computing Machinery, Inc |
Pages | 1269-1282 |
Number of pages | 14 |
ISBN (Electronic) | 9781450355599 |
DOIs | |
Publication status | Published - 20 Jun 2018 |
Event | 50th Annual ACM Symposium on Theory of Computing, STOC 2018 - Los Angeles, United States Duration: 25 Jun 2018 → 29 Jun 2018 |
Conference
Conference | 50th Annual ACM Symposium on Theory of Computing, STOC 2018 |
---|---|
Country/Territory | United States |
City | Los Angeles |
Period | 25/06/18 → 29/06/18 |
Keywords
- Discrepancy
- Random walks
- Rounding techniques
- rounding techniques
- random walks