What is he best known for?
The fields of study he is best known for:
- Combinatorics
- Algebra
- Discrete mathematics
The scientist’s investigation covers issues in Discrete mathematics, Combinatorics, Block code, Concatenated error correction code and Linear code.
His Discrete mathematics research is multidisciplinary, relying on both Expander code, Decoding methods, Low-density parity-check code and Function.
His Decoding methods research includes elements of Theoretical computer science, Distributed data store, Binary code, Data center and Channel capacity.
His Combinatorics study incorporates themes from Upper and lower bounds, Error detection and correction and Binary symmetric channel.
His Concatenated error correction code study combines topics from a wide range of disciplines, such as Sequential decoding and Hamming code.
His work in the fields of Linear code, such as Tornado code and Raptor code, intersects with other areas such as Multinomial distribution, Binomial distribution and Negative binomial distribution.
His most cited work include:
- A Family of Optimal Locally Recoverable Codes (427 citations)
- Bounds on packings of spheres in the Grassmann manifold (210 citations)
- Minimal vectors in linear codes (198 citations)
What are the main themes of his work throughout his whole career to date?
His main research concerns Discrete mathematics, Combinatorics, Linear code, Decoding methods and Upper and lower bounds.
His work deals with themes such as Expander code, Block code, Hamming code, Concatenated error correction code and Binary code, which intersect with Discrete mathematics.
The various areas that Alexander Barg examines in his Concatenated error correction code study include Sequential decoding and Turbo code.
In the subject of general Combinatorics, his work in Finite collection is often linked to Maximum size, thereby combining diverse domains of study.
His research in Decoding methods intersects with topics in Theoretical computer science and Communication channel, Channel capacity.
His Upper and lower bounds study integrates concerns from other disciplines, such as Code word, Distributed data store, Reed–Solomon error correction, Field and Separable space.
He most often published in these fields:
- Discrete mathematics (65.35%)
- Combinatorics (40.16%)
- Linear code (22.44%)
What were the highlights of his more recent work (between 2017-2021)?
- Discrete mathematics (65.35%)
- Upper and lower bounds (20.47%)
- Bandwidth (4.72%)
In recent papers he was focusing on the following fields of study:
Alexander Barg spends much of his time researching Discrete mathematics, Upper and lower bounds, Bandwidth, Construct and Node.
His Discrete mathematics research integrates issues from Hamming space and Ball.
His work carried out in the field of Upper and lower bounds brings together such families of science as Order, Code word, Minimax, Differential privacy and Asymptotically optimal algorithm.
His Bandwidth study also includes fields such as
- Distributed data store that connect with fields like Finite field,
- Link and Simple most often made with reference to Topology.
The Construct study combines topics in areas such as Range and Theoretical computer science.
Alexander Barg studied Field and Separable space that intersect with Combinatorics.
Between 2017 and 2021, his most popular works were:
- Optimal Schemes for Discrete Distribution Estimation Under Locally Differential Privacy (70 citations)
- Clay codes: moulding MDS codes to yield an MSR code (38 citations)
- Combinatorial Alphabet-Dependent Bounds for Locally Recoverable Codes (30 citations)
In his most recent research, the most cited papers focused on:
- Algebra
- Combinatorics
- Algorithm
His scientific interests lie mostly in Discrete mathematics, Upper and lower bounds, Code word, Distributed data store and Erasure code.
Borrowing concepts from Approximation error, he weaves in ideas under Discrete mathematics.
His Upper and lower bounds research incorporates themes from Separable space and Field.
The study incorporates disciplines such as Linear programming, Algebraic curve, Binary number and Coding theory in addition to Code word.
His Distributed data store research incorporates themes from Codebase and Data center.
His work carried out in the field of Erasure code brings together such families of science as Support vector machine and Parallel computing.
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