Roy Schwartz

Computational Theory and Mathematics · with Feldman · 2011–2015

A researcher in the Science corpus: 5 papers; trusts 25 researchers and is trusted by 16 researchers here, as inferred from the citation graph.

Subfields

• Computational Theory and Mathematics — 32 citations into it; #2,241 of 12,182 by trust here, #3,117 by citations
• Computer Graphics and Computer-Aided Design — 16 citations into it
• Artificial Intelligence — 13 citations into it; #8,692 of 35,345 by trust here, #15,542 by citations
• Computer Networks and Communications — 13 citations into it; #2,691 of 9,886 by trust here, #5,340 by citations
• Optimization & Training — 12 citations into it; #2,520 of 2,601 by trust here, #2,112 by citations
• Algorithms & Complexity — 11 citations into it; #501 of 516 by trust here, #343 by citations

Whom Roy Schwartz trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. Andreas Krause
2. Jan Vondr'ak
3. Uriel Feige
4. Hui-Ching Lin
5. George L. Nemhauser
6. Carlos Guestrin
7. L. Lov'asz
8. Shayan Oveis Gharan
9. J. Bilmes
10. Maxim Sviridenko

Who trusts Roy Schwartz overall

1. Alex Kulesza
2. Jennifer Gillenwater
3. B. Taskar
4. Francis R. Bach
5. Niv Buchbinder
6. Ashwinkumar Badanidiyuru
7. Jan Vondr'ak
8. Moran Feldman

Papers from Roy Schwartz's perspective

Ordered by how strongly the researchers Roy Schwartz trusts endorse each paper. Same corpus, a different order for every researcher.

1. A threshold of ln n for approximating set cover (preliminary version)
2. An analysis of approximations for maximizing submodular set functions—I
3. Maximizing a Submodular Set Function Subject to a Matroid Constraint (Extended Abstract) (Conference on Integer Programming and Combinatorial Optimization)
4. Submodular functions and convexity
5. Maximizing the spread of influence through a social network
6. A note on maximizing a submodular set function subject to a knapsack constraint (Operations Research Letters)
7. Near-optimal Nonmyopic Value of Information in Graphical Models
8. Best Algorithms for Approximating the Maximum of a Submodular Set Function
9. Pipage Rounding: A New Method of Constructing Algorithms with Proven Performance Guarantee (Journal of combinatorial optimization)
10. Maximizing Non-Monotone Submodular Functions

Their papers

• Nonmonotone Submodular Maximization via a Structural Continuous Greedy Algorithm - (Extended Abstract) (2011) — 51 citations
• A Unified Continuous Greedy Algorithm for Submodular Maximization (2011) — 294 citations
• Submodular Maximization with Cardinality Constraints (2014) — 341 citations
• Online Submodular Maximization with Preemption (2015) — 128 citations
• Annual Conference Computational Learning Theory: Preface (2012) — 439 citations