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- Eric Allender

Discipline name
D-index
D-index (Discipline H-index) only includes papers and citation values for an examined
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Citations
Publications
World Ranking
National Ranking

Computer Science
D-index
31
Citations
3,848
104
World Ranking
7819
National Ranking
3682

2006 - ACM Distinguished Member

2006 - ACM Fellow For contributions to computational complexity theory.

- Algorithm
- Discrete mathematics
- Computational complexity theory

Eric Allender focuses on Discrete mathematics, Combinatorics, Complexity class, Circuit complexity and Computational complexity theory. His Discrete mathematics research integrates issues from Electronic circuit and ACC0. His Combinatorics research is multidisciplinary, relying on both Class, Function, Upper and lower bounds, Polynomial and Multiplication.

His work deals with themes such as PSPACE, Bounded function and Hierarchy, which intersect with Complexity class. Eric Allender interconnects Lebesgue measure, Measure and Generalization in the investigation of issues within Computational complexity theory. Eric Allender combines subjects such as Kolmogorov complexity and Kolmogorov structure function with his study of Time complexity.

- Uniform constant-depth threshold circuits for division and iterated multiplication (169 citations)
- On the Complexity of Numerical Analysis (135 citations)
- A note on the power of threshold circuits (116 citations)

Eric Allender mostly deals with Discrete mathematics, Combinatorics, Complexity class, Kolmogorov complexity and Computational complexity theory. His Discrete mathematics study integrates concerns from other disciplines, such as Upper and lower bounds and Bounded function. His Combinatorics study combines topics from a wide range of disciplines, such as Class and Circuit complexity.

His Circuit complexity research is multidisciplinary, incorporating elements of Planarity testing and Planar graph. His Complexity class research incorporates themes from Function, PSPACE, Theoretical computer science and Turing machine. The various areas that Eric Allender examines in his Kolmogorov complexity study include Decidability, NEXPTIME, Reduction and Universal Turing machine.

- Discrete mathematics (67.10%)
- Combinatorics (45.45%)
- Complexity class (38.10%)

- Discrete mathematics (67.10%)
- Complexity class (38.10%)
- Kolmogorov complexity (22.51%)

His main research concerns Discrete mathematics, Complexity class, Kolmogorov complexity, Combinatorics and Graph isomorphism. Eric Allender has included themes like PSPACE, Bounded function and Algebraic number in his Discrete mathematics study. His study in Complexity class is interdisciplinary in nature, drawing from both Theoretical computer science, Circuit minimization for Boolean functions, Class, Variety and Circuit complexity.

His Kolmogorov complexity research is multidisciplinary, incorporating perspectives in Function, Reduction and Universal Turing machine. His research ties Computational complexity theory and Combinatorics together. His Time complexity study incorporates themes from Nondeterministic algorithm and Pushdown automaton.

- The Minimum Oracle Circuit Size Problem (19 citations)
- Width-Parameterized SAT: Time-Space Tradeoffs (18 citations)
- Zero knowledge and circuit minimization (14 citations)

- Algorithm
- Computational complexity theory
- Discrete mathematics

Eric Allender mainly focuses on Discrete mathematics, Complexity class, Kolmogorov complexity, Combinatorics and Circuit minimization for Boolean functions. His Discrete mathematics research focuses on Graph isomorphism in particular. His Complexity class study contributes to a more complete understanding of Computational complexity theory.

In his research on the topic of Kolmogorov complexity, Conjecture, Time complexity, Reduction and Worst-case complexity is strongly related with Universal Turing machine. His work on Combinatorics deals in particular with Graph automorphism and Automorphism. Circuit complexity, Graph and Class is closely connected to Clique in his research, which is encompassed under the umbrella topic of Circuit minimization for Boolean functions.

This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.

Uniform constant-depth threshold circuits for division and iterated multiplication

William Hesse;Eric Allender;David A. Mix Barrington.

Journal of Computer and System Sciences **(2002)**

222 Citations

On the Complexity of Numerical Analysis

Eric Allender;Peter Bürgisser;Johan Kjeldgaard-Pedersen;Peter Bro Miltersen.

SIAM Journal on Computing **(2008)**

193 Citations

Complexity of finite-horizon Markov decision process problems

Martin Mundhenk;Judy Goldsmith;Christopher Lusena;Eric Allender.

Journal of the ACM **(2000)**

176 Citations

P-printable sets

Eric W. Allender;Roy S. Rubinstein.

SIAM Journal on Computing **(1988)**

167 Citations

Relationships among PL, #L, and the determinant

Eric Allender;Mitsunori Ogihara.

structure in complexity theory annual conference **(1994)**

165 Citations

A note on the power of threshold circuits

E. Allender.

foundations of computer science **(1989)**

158 Citations

Making Nondeterminism Unambiguous

Klaus Reinhardt;Eric Allender.

SIAM Journal on Computing **(2000)**

135 Citations

The complexity of sparse sets in P

Eric Allender.

structure in complexity theory annual conference **(1986)**

125 Citations

The complexity of matrix rank and feasible systems of linear equations

Eric Allender;Robert Beals;Mitsunori Ogihara.

Computational Complexity **(1999)**

116 Citations

Non-commutative arithmetic circuits: depth reduction and size lower bounds

Eric Allender;Jia Jiao;Meena Mahajan;V. Vinay.

Theoretical Computer Science **(1998)**

112 Citations

University of Amsterdam

Santa Fe Institute

University of Toronto

University of Miami

University of Massachusetts Amherst

Rutgers, The State University of New Jersey

University of Tokyo

University of Michigan–Ann Arbor

Aarhus University

UNSW Sydney

Profile was last updated on December 6th, 2021.

Research.com Ranking is based on data retrieved from the Microsoft Academic Graph (MAG).

The ranking d-index is inferred from publications deemed to belong to the considered discipline.

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