2021 - IEEE Claude E. Shannon Award
His Linguistics research is linked to Zero (linguistics) and Alphabet. His study brings together the fields of Linguistics and Zero (linguistics). His work blends Statistics and Coding (social sciences) studies together. Coding (social sciences) is frequently linked to Variable-length code in his study. Alon Orlitsky conducted interdisciplinary study in his works that combined Variable-length code and Shannon–Fano coding. His work on Statistics expands to the thematically related Shannon–Fano coding. Many of his studies on Algorithm involve topics that are commonly interrelated, such as Probability of error. His work in Probability of error is not limited to one particular discipline; it also encompasses Algorithm. Alon Orlitsky combines Discrete mathematics and Applied mathematics in his research.
Alon Orlitsky connects relevant research areas such as Random variable, Estimator and Principle of maximum entropy in the realm of Statistics. With his scientific publications, his incorporates both Estimator and Statistics. Alon Orlitsky is involved in relevant fields of research such as Upper and lower bounds and Distribution (mathematics) in the domain of Mathematical analysis. In his study, he carries out multidisciplinary Distribution (mathematics) and Mathematical analysis research. Borrowing concepts from Applied mathematics, he weaves in ideas under Discrete mathematics. In his research, Alon Orlitsky undertakes multidisciplinary study on Applied mathematics and Discrete mathematics. His research ties Binary logarithm and Combinatorics together. As part of his studies on Binary logarithm, Alon Orlitsky often connects relevant subjects like Combinatorics. He merges many fields, such as Algorithm and Programming language, in his writings.
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Coding for computing
A. Orlitsky;J.R. Roche.
international symposium on information theory (1995)
Stopping set distribution of LDPC code ensembles
A. Orlitsky;Krishnamurthy Viswanathan;J. Zhang.
international symposium on information theory (2003)
Always Good Turing: asymptotically optimal probability estimation
A. Orlitsky;N.P. Santhanam;J. Zhang.
foundations of computer science (2003)
Zero-error information theory
J. Korner;A. Orlitsky.
IEEE Transactions on Information Theory (1998)
Universal compression of memoryless sources over unknown alphabets
A. Orlitsky;N.P. Santhanam;Junan Zhang.
IEEE Transactions on Information Theory (2004)
Source coding and graph entropies
N. Alon;A. Orlitsky.
IEEE Transactions on Information Theory (1996)
Worst-case interactive communication. I. Two messages are almost optimal
IEEE Transactions on Information Theory (1990)
Optimal prediction of the number of unseen species
Alon Orlitsky;Ananda Theertha Suresh;Yihong Wu.
Proceedings of the National Academy of Sciences of the United States of America (2016)
Monte Carlo generation of self-avoiding walks with fixed endpoints and fixed length
N. Madras;A. Orlitsky;L. A. Shepp.
Journal of Statistical Physics (1990)
Stopping sets and the girth of Tanner graphs
A. Orlitsky;R. Urbanke;K. Viswanathan;J. Zhang.
international symposium on information theory (2002)
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