2000 - Fellow of Alfred P. Sloan Foundation
Combinatorics, Discrete mathematics, Approximation algorithm, Time complexity and Computational complexity theory are his primary areas of study. His study connects Optimization problem and Combinatorics. He studies Regular graph, a branch of Discrete mathematics.
His Approximation algorithm research is multidisciplinary, relying on both Linear programming, Semidefinite programming and Spanning tree. Luca Trevisan interconnects Independent set, Bounded function and Degree in the investigation of issues within Time complexity. His Binary logarithm study deals with Sequential decoding intersecting with Lemma and List decoding.
The scientist’s investigation covers issues in Combinatorics, Discrete mathematics, Approximation algorithm, Time complexity and Upper and lower bounds. His studies in Combinatorics integrate themes in fields like Bounded function and Constant. The Discrete mathematics study which covers Pseudorandom number generator that intersects with Lemma.
His Approximation algorithm study incorporates themes from Linear programming, Combinatorial optimization and Semidefinite programming. His research investigates the connection between Time complexity and topics such as Polynomial that intersect with issues in Function. His Upper and lower bounds research is multidisciplinary, incorporating perspectives in Permutation and Laplace operator.
Luca Trevisan mainly investigates Combinatorics, Graph, Upper and lower bounds, Discrete mathematics and Time complexity. His study on Approximation algorithm, Degree and Maximum cut is often connected to Omega as part of broader study in Combinatorics. His Approximation algorithm research focuses on Dominating set and how it connects with Clique, Parameterized complexity and Complete bipartite graph.
His research integrates issues of Binary logarithm, Complete graph, Ramanujan's sum and Laplace operator in his study of Upper and lower bounds. Luca Trevisan studies Discrete mathematics, namely Vertex. His research in Time complexity intersects with topics in Bounded function and Constant.
His scientific interests lie mostly in Combinatorics, Algorithm, Upper and lower bounds, Constant and Approximation algorithm. His study ties his expertise on Exponential function together with the subject of Combinatorics. He combines subjects such as Logarithm, Graph and Centrality with his study of Algorithm.
His Upper and lower bounds research focuses on Laplace operator and how it relates to Eigenvalues and eigenvectors and Complete graph. His studies deal with areas such as Structure, Multiplicative function, Rank, Degree and Matching as well as Constant. His work is dedicated to discovering how Polynomial, Discrete mathematics are connected with Bounded function and other disciplines.
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.
Pseudorandom generators without the XOR lemma
M. Sudan;L. Trevisan;S. Vadhan.
conference on computational complexity (1999)
Counting Distinct Elements in a Data Stream
Ziv Bar-Yossef;T. S. Jayram;Ravi Kumar;D. Sivakumar.
randomization and approximation techniques in computer science (2002)
Extractors and pseudorandom generators.
Journal of the ACM (2001)
Gadgets, Approximation, and Linear Programming
Luca Trevisan;Gregory B. Sorkin;Madhu Sudan;David P. Williamson.
SIAM Journal on Computing (2000)
On the efficiency of local decoding procedures for error-correcting codes
Jonathan Katz;Luca Trevisan.
symposium on the theory of computing (2000)
Notions of Reducibility between Cryptographic Primitives
Omer Reingold;Luca Trevisan;Salil P. Vadhan.
theory of cryptography conference (2004)
Multiway Spectral Partitioning and Higher-Order Cheeger Inequalities
James R. Lee;Shayan Oveis Gharan;Luca Trevisan.
Journal of the ACM (2014)
Non-approximability results for optimization problems on bounded degree instances
symposium on the theory of computing (2001)
Some Applications of Coding Theory in Computational Complexity
Electronic Colloquium on Computational Complexity (2004)
Extracting randomness from samplable distributions
L. Trevisan;S. Vadhan.
foundations of computer science (2000)
Profile was last updated on December 6th, 2021.
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