Demo Data from SIGIR 2026 / reviewers in the wild / expert
Konstantin Myasnikov
dblp:424/6162
· DBLP profile ↗
2ranked-venue papers
0as first author
2since 2021 · last 2026
0009-0001-5849-8337ORCID · reported
Domains — the database's venue-derived domains; a paper can count in several
Theory of computation · 2 · 2 since 2021
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 |
Computational complexity · 67% Algorithms and data structures · 33% |
Topics — the 6 heaviest of 6, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Algorithms and data structures › data structure lower bounds
cell-probe lower bounds |
1.0 | 1 | 2026 | Sampling Permutations with Cell Probes Is Hard · STOC 2026 |
Computational complexity
circuit complexity |
1.0 | 1 | 2026 | Spiky Rank and Its Applications to Rigidity and Circuits · ICALP 2026 |
Computational complexity › circuit complexity
matrix rigidity |
1.0 | 1 | 2026 | Spiky Rank and Its Applications to Rigidity and Circuits · ICALP 2026 |
Computational complexity
query complexity |
1.0 | 1 | 2026 | Sampling Permutations with Cell Probes Is Hard · STOC 2026 |
Computational complexity › lower bounds
sampling lower bounds |
1.0 | 1 | 2026 | Sampling Permutations with Cell Probes Is Hard · STOC 2026 |
Algorithms and data structures › space-efficient algorithms
succinct data structures |
1.0 | 1 | 2026 | Sampling Permutations with Cell Probes Is Hard · STOC 2026 |
Methods — techniques the papers use, named apart from their topics
cell probe model · 1.0
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2026 | Spiky Rank and Its Applications to Rigidity and Circuits
Lianna Hambardzumyan, Konstantin Myasnikov, Artur Riazanov, Morgan Shirley, Adi Shraibman |
ICALP | 2 |
| 2026 | Sampling Permutations with Cell Probes Is HardabstractSuppose we are given an infinite sequence of input cells, each initialized with a uniform random symbol from [n]. How hard is it to output a sequence in [n]n that is close to a uniform random permutation? Viola (SICOMP 2020) conjectured that if each output cell is computed by making d probes to input cells, then d≥ω(1). Our main result shows that, in fact, d≥ (logn)Ω(1), which is tight up to the constant in the exponent. Our techniques also show that if the probes are nonadaptive, then d≥ nΩ(1), which is an exponential improvement over the previous nonadaptive lower bound due to Yu and Zhan (ITCS 2024). Our results also imply lower bounds against succinct data structures for storing permutations. Yaroslav Alekseev, Mika Göös, Konstantin Myasnikov, Artur Riazanov, Dmitry Sokolov 0001 |
STOC | 3 |