Award Abstract # 1514339
AF: Medium: Collaborative Research: Hardness in Polynomial Time

NSF Org: CCF
Division of Computing and Communication Foundations
Recipient: THE LELAND STANFORD JUNIOR UNIVERSITY
Initial Amendment Date: June 9, 2015
Latest Amendment Date: June 9, 2015
Award Number: 1514339
Award Instrument: Continuing Grant
Program Manager: Tracy Kimbrel
CCF
 Division of Computing and Communication Foundations
CSE
 Directorate for Computer and Information Science and Engineering
Start Date: September 1, 2015
End Date: May 31, 2017 (Estimated)
Total Intended Award Amount: $600,000.00
Total Awarded Amount to Date: $291,908.00
Funds Obligated to Date: FY 2015 = $146,950.00
History of Investigator:
  • Virginia Williams (Principal Investigator)
    virgito@gmail.com
Recipient Sponsored Research Office: Stanford University
450 JANE STANFORD WAY
STANFORD
CA  US  94305-2004
(650)723-2300
Sponsor Congressional District: 16
Primary Place of Performance: Stanford University
Stanford
CA  US  94305-2004
Primary Place of Performance
Congressional District:
16
Unique Entity Identifier (UEI): HJD6G4D6TJY5
Parent UEI:
NSF Program(s): Algorithmic Foundations
Primary Program Source: 01001516DB NSF RESEARCH & RELATED ACTIVIT
01001718DB NSF RESEARCH & RELATED ACTIVIT

01001819DB NSF RESEARCH & RELATED ACTIVIT
Program Reference Code(s): 7924, 7926
Program Element Code(s): 779600
Award Agency Code: 4900
Fund Agency Code: 4900
Assistance Listing Number(s): 47.070

ABSTRACT

A central endeavor of theoretical computer science is to classify computational problems according to the resources (such as running time and storage space) needed to solve them.  Although the field of algorithm design has been highly successful in discovering efficient, polynomial-time algorithms for problems of practical interest, little evidence has been shown for the optimality of most algorithms.  The goal of this project is to build a useful complexity theory for the class of polynomial-time solvable problems (called P), by proving equivalences between problems and proving conditional lower bounds on specific problems, assuming the validity of certain plausible mathematical conjectures.

Known lower bounds for specific problems in P are conditioned on some complexity-theoretic assumption such as the (Strong) Exponential Time Hypothesis (concerning the complexity of k-CNF-SAT), the conjecture that dense all-pairs shortest paths (APSP) requires cubic time, or that 3SUM requires quadratic time.  The goals of this project are threefold.  The first goal is to establish conditional lower bounds on problems in diverse areas (such as graph optimization, string matching, geometry, and dynamic data structures) using standard hardness conjectures. The second goal is to search for better hardness conjectures that are both plausible and versatile, and to discover relationships (implications or equivalences) between nominally unrelated conjectures.  The last goal is to investigate the plausibility of these conjectures by attempting to disprove them.

The curricular portion of this project involves developing lecture material suitable for introductory algorithms and complexity courses at both the undergraduate and graduate level.

PUBLICATIONS PRODUCED AS A RESULT OF THIS RESEARCH

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Amir Abboud, Arturs Backurs, Thomas Dueholm Hansen, Virginia Vassilevska Williams, Or Zamir "Subtree Isomorphism Revisited" SODA 2016 , 2016 , p.1256
Amir Abboud, Thomas Dueholm Hansen, Virginia Vassilevska Williams, Ryan Williams "Simulating branching programs with edit distance and friends: or: a polylog shaved is a lower bound made" STOC 2016 , 2016 , p.375
Amir Abboud, Virginia Vassilevska Williams, Joshua R. Wang "Approximation and Fixed Parameter Subquadratic Algorithms for Radius and Diameter in Sparse Graphs" SODA 2016 , 2016 , p.377
Andrea Lincoln, Virginia Vassilevska Williams, Joshua R. Wang, R. Ryan Williams "Deterministic Time-Space Trade-Offs for k-SUM" ICALP 2016 , 2016 , p.1

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