EDBT 2026 Demo / reviewers in the wild / expert
Todd Ebert
dblp:06/850
· DBLP profile ↗
3ranked-venue papers
3as first author
0since 2021 · last 2003
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Theory of computation · 3 · 3 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
1 paper |
Computational complexity · 100% |
Topics — the 3 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Computational complexity
algorithmic randomness |
0.0 | 1 | 2003 | On the Autoreducibility of Random Sequences · SIAM J. Comput. 2003 |
Computational complexity › reduction
autoreducibility |
0.0 | 1 | 2003 | On the Autoreducibility of Random Sequences · SIAM J. Comput. 2003 |
Computational complexity › algorithmic randomness
martin-löf randomness |
0.0 | 1 | 2003 | On the Autoreducibility of Random Sequences · SIAM J. Comput. 2003 |
Methods — techniques the papers use, named apart from their topics
truth-table reducibility · 0.0oracle turing machine · 0.0
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2003 | On the Autoreducibility of Random SequencesabstractA binary sequence $A=A(0)A(1)\ldots$ is called infinitely often (i.o.)~Turing-au\-to\-re\-duc\-ible if A~is reducible to itself via an oracle Turing machine that never queries its oracle at the current input, outputs either $A(x)$ or a don't-know symbol on any given input~x, and outputs $A(x)$ for infinitely many~x. If in addition the oracle Turing machine terminates on all inputs and oracles, A~is called i.o.~truth-table-autoreducible. We obtain the somewhat counterintuitive result that every Martin-L\"of random sequence, in fact even every rec-random or p-random sequence, is i.o.~truth-table-autoreducible. Furthermore, we investigate the question of how dense the set of guessed bits can be when i.o.~autoreducing a random sequence. We show that rec-random sequences are never i.o.~truth-table-autoreducible such that the set of guessed bits has positive constant density in the limit and that a similar assertion holds for Martin-L\"of random sequences and i.o.~Turing autoreducibility. On the other hand, we show that for any rational-valued computable function~r that goes nonascendingly to zero, any rec-random sequence is i.o.~truth-table-autoreducible such that on any prefix of length~m at least a fraction of~$r(m)$ of the m~bits in the prefix are guessed. We include a self-contained account of the hat problem, a puzzle that has received some attention outside of theoretical computer science. The hat problem asks for guessing bits of a finite sequence, thus illustrating the notion of i.o.~autoreducibility in a finite setting. The solution to the hat problem is then used as a module in the proofs of the positive results on i.o.~autoreducibility. Todd Ebert, Wolfgang Merkle, Heribert Vollmer |
SIAM J. Comput. | 1 |
| 2002 | Autoreducibility of Random Sets: A Sharp Bound on the Density of Guessed Bits
Todd Ebert, Wolfgang Merkle |
MFCS | 1 |
| 2000 | On the Autoreducibility of Random Sequences
Todd Ebert, Heribert Vollmer |
MFCS | 1 |