What is he best known for?
The fields of study he is best known for:
- Computer network
- Algorithm
- Combinatorics
Baruch Schieber spends much of his time researching Combinatorics, Approximation algorithm, Time complexity, Mathematical optimization and Path.
His research in Combinatorics intersects with topics in Discrete mathematics, Parallel algorithm and Function problem.
As part of his studies on Approximation algorithm, Baruch Schieber frequently links adjacent subjects like Multicast.
Baruch Schieber interconnects Enhanced Data Rates for GSM Evolution, Unit and Topology in the investigation of issues within Time complexity.
His work investigates the relationship between Mathematical optimization and topics such as Fair-share scheduling that intersect with problems in Dynamic bandwidth allocation, Dynamic priority scheduling and Bandwidth allocation.
His study in Path is interdisciplinary in nature, drawing from both Robot and Artificial intelligence.
His most cited work include:
- On Finding Lowest Common Ancestors: Simplification and Parallelization (472 citations)
- A unified approach to approximating resource allocation and scheduling (351 citations)
- Approximating Minimum Feedback Sets and Multicuts in Directed Graphs (275 citations)
What are the main themes of his work throughout his whole career to date?
Baruch Schieber mainly focuses on Combinatorics, Discrete mathematics, Time complexity, Approximation algorithm and Mathematical optimization.
His Combinatorics research integrates issues from Computational complexity theory, Parallel algorithm, Upper and lower bounds and Computation tree.
His Discrete mathematics research is multidisciplinary, incorporating elements of Path, Computation and Directed acyclic graph.
His work deals with themes such as Function, Dynamic programming, Online algorithm and Lowest common ancestor, which intersect with Time complexity.
His biological study spans a wide range of topics, including Euclidean space and Fair-share scheduling.
His work on Greedy algorithm as part of general Mathematical optimization research is often related to Schedule, thus linking different fields of science.
He most often published in these fields:
- Combinatorics (46.20%)
- Discrete mathematics (28.07%)
- Time complexity (23.98%)
What were the highlights of his more recent work (between 2016-2020)?
- Combinatorics (46.20%)
- Sublinear function (4.68%)
- Maximal independent set (3.51%)
In recent papers he was focusing on the following fields of study:
Baruch Schieber mostly deals with Combinatorics, Sublinear function, Maximal independent set, Approximation algorithm and Graph.
His Submodular set function study in the realm of Combinatorics interacts with subjects such as Suffix tree.
As a member of one scientific family, Baruch Schieber mostly works in the field of Sublinear function, focusing on e and, on occasion, Enhanced Data Rates for GSM Evolution, Dynamic problem and Randomized algorithm.
His Approximation algorithm study necessitates a more in-depth grasp of Mathematical optimization.
His Graph study also includes
- Range that connect with fields like Constant,
- Deterministic algorithm which connect with Channel, Computer network and Point-to-point.
His Complement research is multidisciplinary, relying on both Time complexity and Algorithm.
Between 2016 and 2020, his most popular works were:
- On Finding Lowest Common Ancestors: Simplification and Parallelization (472 citations)
- Scalable Fair Clustering (41 citations)
- Fully dynamic maximal independent set with sublinear update time (39 citations)
In his most recent research, the most cited papers focused on:
- Computer network
- Algorithm
- Combinatorics
Combinatorics, Time complexity, Sublinear function, Maximal independent set and Algorithm are his primary areas of study.
Baruch Schieber has included themes like Metric, Measure, Class, Theory of computation and Optimization problem in his Combinatorics study.
His studies deal with areas such as Scalability, Algorithmics, Lowest common ancestor, Parallel algorithm and Search algorithm as well as Time complexity.
His research on Sublinear function concerns the broader Discrete mathematics.
His studies in Maximal independent set integrate themes in fields like Range and Randomized algorithm.
The concepts of his Algorithm study are interwoven with issues in Point, Center, Complement and Cluster analysis.
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.
