Demo Data from EDBT 2026 / reviewers in the wild / expert
Asaf Nachmias
dblp:81/2538
· DBLP profile ↗
2ranked-venue papers
1as first author
0since 2021 · last 2010
0000-0002-4852-5645ORCID · corroborated
Domains — the database's venue-derived domains; a paper can count in several
Theory of computation · 2 · 1 first-author
Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.
| Theoretical computer science
2 papers |
Algorithms and data structures · 44% Computational complexity · 34% Graph algorithms and graph theory · 22% |
Topics — the 4 heaviest of 4, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Computational complexity › property testing › graph property testing
expansion testing |
0.1 | 1 | 2010 | Testing the expansion of a graph · Inf. Comput. 2010 |
Algorithms and data structures › randomized algorithms › sampling
markov chain monte carlo |
0.1 | 1 | 2007 | Mixing Time Power Laws at Criticality · FOCS 2007 |
Algorithms and data structures › markov chains
mixing time |
0.1 | 1 | 2007 | Mixing Time Power Laws at Criticality · FOCS 2007 |
Graph algorithms and graph theory
percolation |
0.1 | 1 | 2007 | Mixing Time Power Laws at Criticality · FOCS 2007 |
Methods — techniques the papers use, named apart from their topics
swendsen-wang dynamics · 0.1random walk analysis · 0.1
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2010 | Testing the expansion of a graph
Asaf Nachmias, Asaf Shapira |
Inf. Comput. | 1 |
| 2007 | Mixing Time Power Laws at CriticalityabstractWe study the mixing time of some Markov chains converging to critical physical models. These models are indexed by a parameter beta and there exists some critical value betacwhere the model undergoes a phase transition. According to physics lore, the mixing time of such Markov chains is often of logarithmic order outside the critical regime, when beta ne betac, and satisfies-some power law at criticality, when beta = betac. We prove this in the two following settings: 1. Lazy random walk on the critical percolation cluster of "mean-field" graphs, which include the complete graph and random d-regular graphs. The critical mixing time here is of order Theta(n). This answers a question of Benjamini, Kozma and Wormald. 2. Swendsen-Wang dynamics on the complete, graph. The critical mixing time, here is of order Theta(n1/4). This improves results of Cooper, Dyer, Frieze and Rue. In both settings, the main tool is understanding the Markov chain dynamics via properties of critical percolation on the underlying graph. Asaf Nachmias, Yuval Peres |
FOCS | 2 |