Bernd Schmeltz

dblp:52/892 · DBLP profile ↗
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3ranked-venue papers
1as first author
0since 2021 · last 1991
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Theory of computation · 3 · 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
1 paper
Computational complexity · 100%

Topics — the 5 heaviest of 5, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Computational complexity
circuit complexity
0.011991
Reliable Computation with Noisy Circuits and Decision Trees-A General n log n Lower Bound · FOCS 1991
Computational complexity › query complexity
decision tree complexity
0.011991
Reliable Computation with Noisy Circuits and Decision Trees-A General n log n Lower Bound · FOCS 1991
Computational complexity › query complexity › decision tree complexity
noisy decision tree
0.011991
Reliable Computation with Noisy Circuits and Decision Trees-A General n log n Lower Bound · FOCS 1991
Computational complexity
reliable computation
0.011991
Reliable Computation with Noisy Circuits and Decision Trees-A General n log n Lower Bound · FOCS 1991
Computational complexity
lower bounds
0.011991
Reliable Computation with Noisy Circuits and Decision Trees-A General n log n Lower Bound · FOCS 1991

Methods — techniques the papers use, named apart from their topics

static decision tree analysis · 0.0probabilistic error model · 0.0
YearPublicationVenuePosition
1991 Reliable Computation with Noisy Circuits and Decision Trees-A General n log n Lower Bound
abstract
Boolean circuits in which gates independently make errors with probability (at most) epsilon are considered. It is shown that the critical number crit(f) of a function f yields lower bound Omega (crit(f) log crit (f)) for the noisy circuit size. The lower bound is proved for an even stronger computational model, static Boolean decision trees with erroneous answers. A decision tree is static if the questions it asks do not depend on previous answers. The depth of such a tree provides a lower bound on the number of gates that depend directly on some input and hence on the size of a noisy circuit. Furthermore, it is shown that an Omega (n log n) lower bound holds for almost all Boolean n-input functions with respect to the depth of noisy dynamic decision trees. This bound is the best possible and implies that almost all n-input Boolean functions have noisy decision tree complexity Theta (n log n) in the static as well as in the dynamic case.>
Rüdiger Reischuk, Bernd Schmeltz
FOCS2
1991 Optimal Tradeoffs Between Time And Bit Complexity In Distributed Synchronous Rings
Bernd Schmeltz
STACS1
1989 Area Efficient Methods to Increase the Reliability of Combinatorial Circuits
Rüdiger Reischuk, Bernd Schmeltz
STACS2