2005 - Fellow of Alfred P. Sloan Foundation
His primary areas of investigation include Discrete mathematics, Combinatorics, Boolean function, Upper and lower bounds and Computational learning theory. His research integrates issues of Approximation theory, Generalization, Monotone polygon and Unit sphere in his study of Discrete mathematics. The various areas that Rocco A. Servedio examines in his Combinatorics study include Function, Distribution, Polynomial and Constant.
His biological study spans a wide range of topics, including Time complexity and Quantum algorithm. His work deals with themes such as BrownBoost and Gradient boosting, which intersect with Computational learning theory. His study focuses on the intersection of Algorithm and fields such as Boosting with connections in the field of Noise tolerance.
His primary areas of study are Combinatorics, Discrete mathematics, Boolean function, Upper and lower bounds and Polynomial. His Combinatorics research integrates issues from Function, Distribution, Exponential function and Constant. The study incorporates disciplines such as Computational learning theory and Monotone polygon in addition to Discrete mathematics.
His research in Boolean function intersects with topics in Computational complexity theory and Conjecture. His study looks at the relationship between Upper and lower bounds and fields such as Algorithm, as well as how they intersect with chemical problems. His Polynomial research incorporates themes from Randomized algorithm, Deterministic algorithm and Degree.
Rocco A. Servedio mainly investigates Combinatorics, Discrete mathematics, Upper and lower bounds, Distribution and Boolean function. His Binary logarithm study, which is part of a larger body of work in Combinatorics, is frequently linked to Deletion channel, bridging the gap between disciplines. The Discrete mathematics study combines topics in areas such as Standard basis, Polynomial, Pseudorandom number generator and Monotone polygon.
His Upper and lower bounds study combines topics from a wide range of disciplines, such as Matching, Algorithm, Omega and Regular polygon. The study incorporates disciplines such as Total variation, Type, Polynomial, Unsupervised learning and Independent and identically distributed random variables in addition to Distribution. His research integrates issues of Property testing, Exponential function, Range, Function and Circuit complexity in his study of Boolean function.
His primary scientific interests are in Discrete mathematics, Combinatorics, Boolean function, Upper and lower bounds and Constant. While working in this field, Rocco A. Servedio studies both Discrete mathematics and Randomness. In general Combinatorics, his work in Conjecture, Karp–Lipton theorem and Boolean circuit is often linked to Random oracle linking many areas of study.
His studies deal with areas such as Property testing, Standard basis, Polynomial hierarchy, Range and Polynomial as well as Boolean function. The Upper and lower bounds study which covers Matching that intersects with Regular polygon. His work is dedicated to discovering how Constant, Binary logarithm are connected with Time complexity and other disciplines.
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Random classification noise defeats all convex potential boosters
Philip M. Long;Rocco A. Servedio.
Machine Learning (2010)
Agnostically Learning Halfspaces
Adam Tauman Kalai;Adam R. Klivans;Yishay Mansour;Rocco A. Servedio.
SIAM Journal on Computing (2008)
Learning intersections and thresholds of halfspaces
A. R. Klivans;R. O'Donnell;Rocco A. Servedio.
foundations of computer science (2002)
Learning DNF in time 2 õ ( n 1/3 )
Adam R. Klivans;Rocco A. Servedio.
symposium on the theory of computing (2004)
Smooth boosting and learning with malicious noise
Rocco A. Servedio.
Journal of Machine Learning Research (2003)
On the Capacity of Secure Network Coding
Jon Feldman;Tal Malkin;Rocco A. Servedio;Cliff Stein.
Learning functions of k relevant variables
Elchanan Mossel;Ryan O'Donnell;Rocco A. Servedio.
symposium on the theory of computing (2004)
Agnostically learning halfspaces
A.T. Kalai;A.R. Klivans;Yishay Mansour;R.A. Servedio.
foundations of computer science (2005)
Learning Monotone Decision Trees in Polynomial Time
Ryan O'Donnell;Rocco A. Servedio.
SIAM Journal on Computing (2007)
Learning DNF in time
Adam R. Klivans;Rocco Servedio.
symposium on the theory of computing (2001)
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