Rutger Verbeek

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12ranked-venue papers
3as first author
0since 2021 · last 2001
—ORCID · none

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

Theory of computation · 12 · 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
7 papers
Computational complexity · 73% Automata and formal languages · 19% Algorithms and data structures · 5%

Topics — the 15 heaviest of 16, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Computational complexity
randomized computation
0.031993
On Randomized Versus Deterministic Computation · ICALP 1993
On the Power of Two-Way Random Generators and the Impossibility of Deterministic Poly-Space Simulation · Inf. Control. 1986
There Is No Polynomial Deterministic Space Simulation of Probabilistic Space with a Two-Way Random-Tape Generator · Inf. Control. 1985
Computational complexity
space complexity
0.021986
On the Power of Two-Way Random Generators and the Impossibility of Deterministic Poly-Space Simulation · Inf. Control. 1986
There Is No Polynomial Deterministic Space Simulation of Probabilistic Space with a Two-Way Random-Tape Generator · Inf. Control. 1985
Computational complexity
time-space tradeoffs
0.031983
The Recognition of Deterministic CFL's in Small Time and Space · Inf. Control. 1983
Time-Space Trade-Offs for General Recursion · FOCS 1981
A Recognition Algorithm for Deterministic CFLS optimal in Time and Space · FOCS 1980
Computational complexity › complexity classes
probabilistic complexity classes
0.011987
On the Monte Carlo Space Constructible Functions and Seperation Results for Probabilistic Complexity Classes · Inf. Comput. 1987
Computational complexity › structural complexity › complexity class separation
separation results
0.011987
On the Monte Carlo Space Constructible Functions and Seperation Results for Probabilistic Complexity Classes · Inf. Comput. 1987
Computational complexity › space complexity
space constructibility
0.011987
On the Monte Carlo Space Constructible Functions and Seperation Results for Probabilistic Complexity Classes · Inf. Comput. 1987
Automata and formal languages
context-free languages
0.021983
The Recognition of Deterministic CFL's in Small Time and Space · Inf. Control. 1983
A Recognition Algorithm for Deterministic CFLS optimal in Time and Space · FOCS 1980
Computational complexity › space complexity
randomized space simulation
0.011985
There Is No Polynomial Deterministic Space Simulation of Probabilistic Space with a Two-Way Random-Tape Generator · Inf. Control. 1985
Algorithms and data structures
deterministic algorithms
0.011993
On Randomized Versus Deterministic Computation · ICALP 1993
Automata and formal languages › context-free languages
deterministic context-free languages
0.011983
The Recognition of Deterministic CFL's in Small Time and Space · Inf. Control. 1983
Automata and formal languages › context-free languages
recognition complexity
0.011983
The Recognition of Deterministic CFL's in Small Time and Space · Inf. Control. 1983
Computational complexity › space complexity
pebble game
0.011981
Time-Space Trade-Offs for General Recursion · FOCS 1981
Automata and formal languages
pushdown automata
0.011981
Time-Space Trade-Offs for General Recursion · FOCS 1981
Logic in computer science
recursion
0.011981
Time-Space Trade-Offs for General Recursion · FOCS 1981
Automata and formal languages › context-free languages › context-free language recognition
deterministic context-free language recognition
0.011980
A Recognition Algorithm for Deterministic CFLS optimal in Time and Space · FOCS 1980

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

complexity theory · 0.0separation results · 0.0impossibility proof · 0.0space simulation · 0.0random access input · 0.0multitape turing machine simulation · 0.0space-time tradeoff · 0.0multitape turing machine · 0.0lower bound proof · 0.0
YearPublicationVenuePosition
2001 Monte-Carlo Polynomial Versus Linear Time - The Truth-Table Case
Robert Rettinger, Rutger Verbeek
FCT2
1996 On Randomized versus Deterministic Computation
Marek Karpinski, Rutger Verbeek
Theor. Comput. Sci.2
1993 On Randomized Versus Deterministic Computation
Marek Karpinski, Rutger Verbeek
ICALP2
1987 On the Monte Carlo Space Constructible Functions and Seperation Results for Probabilistic Complexity Classes
Marek Karpinski, Rutger Verbeek
Inf. Comput.2
1986 On the Power of Two-Way Random Generators and the Impossibility of Deterministic Poly-Space Simulation
Marek Karpinski, Rutger Verbeek
Inf. Control.2
1985 There Is No Polynomial Deterministic Space Simulation of Probabilistic Space with a Two-Way Random-Tape Generator
Marek Karpinski, Rutger Verbeek
Inf. Control.2
1983 Input-Driven Languages are Recognized in log n Space
Burchard von Braunmühl, Rutger Verbeek
FCT2
1983 The Recognition of Deterministic CFL's in Small Time and Space
abstract
Let S(n) be a nice space bound such that log2 n S(n) n. Then every DCFL is recognized by a multitape Turing machine simultaneously in time O(n2/S(n)) and space O(S(n)), and this time bound is optimal. If the machine is allowed a random access input, then the time bound can be improved so that the time-space product is O(n1 + ).
Burchard von Braunmühl, Stephen A. Cook, Kurt Mehlhorn, Rutger Verbeek
Inf. Control.4
1981 Time-Space Trade-Offs for General Recursion
abstract
A lower bound for the time-space trade-off of pebble games on PD-Graphs (which represent computations of push-down automata or recursion schemes) is proved, that is only a bit lower than the best known upper bound (the lower and upper time bound is about n · 2 logn/log(s/log n)). The best lower bound known up to now is the bound for linear recursion (about n · log n/log(s/log n) for s ≫ log n.
Rutger Verbeek
FOCS1
1980 A Recognition Algorithm for Deterministic CFLS optimal in Time and Space
abstract
An algorithm is presented which recognizes arbitrary deterministic CFLs in space O(log2n) and time O(n2/log2n) simultaneously on a deterministic multitape Turing machine. Furthermore, the algorithm provides a general space-time trade-off for deterministic CFLs: the lower bound of the space time product is n2 and our algorithm uses time O(n2/s(n)) for any "acceptable" space functions s(n) between log2n and n. The same methods also give very small upper bounds for DCFL recognition using a fast read-only memory for the input (e.g. space (log n)2 and time n1+ε simultaneously for any ε ≫ o).
Burchard von Braunmühl, Rutger Verbeek
FOCS2
1978 Data Representation and Computational Complexity
Rutger Verbeek, Klaus Weihrauch
Theor. Comput. Sci.1
1976 The Influence of the Data Presentation on the Computational POwer of Machines
Rutger Verbeek, Klaus Weihrauch
MFCS1