What is he best known for?
The fields of study he is best known for:
- Combinatorics
- Algorithm
- Discrete mathematics
His main research concerns Combinatorics, Discrete mathematics, Coreset, k-means clustering and Cluster analysis.
His Approximation algorithm, Spanning tree and Line graph study in the realm of Combinatorics connects with subjects such as Bounded function.
His Approximation algorithm research is multidisciplinary, incorporating elements of Kullback–Leibler divergence, Time complexity, Divergence, Mahalanobis distance and Metric space.
In the subject of general Discrete mathematics, his work in Euclidean minimum spanning tree and Universal graph is often linked to Constant and Dimension, thereby combining diverse domains of study.
His research integrates issues of CURE data clustering algorithm, Data stream clustering, Nonuniform sampling and Theoretical computer science in his study of k-means clustering.
His Cluster analysis research integrates issues from Algorithm, Point set, Euclidean space and Partition.
His most cited work include:
- Turning big data into tiny data: constant-size coresets for k-means, PCA and projective clustering (271 citations)
- Counting triangles in data streams (222 citations)
- StreamKM++: A clustering algorithm for data streams (205 citations)
What are the main themes of his work throughout his whole career to date?
His primary areas of investigation include Combinatorics, Discrete mathematics, Property testing, Cluster analysis and Bounded function.
In his study, Christian Sohler carries out multidisciplinary Combinatorics and Constant research.
His work on Line graph, Metric space and Graph property as part of general Discrete mathematics study is frequently connected to Streaming algorithm, therefore bridging the gap between diverse disciplines of science and establishing a new relationship between them.
His work deals with themes such as Adjacency matrix, Vertex, Graph and Graph, which intersect with Property testing.
Christian Sohler interconnects Coreset and Algorithm in the investigation of issues within Cluster analysis.
His Coreset research includes themes of Subspace topology and Euclidean space.
He most often published in these fields:
- Combinatorics (59.44%)
- Discrete mathematics (41.26%)
- Property testing (20.98%)
What were the highlights of his more recent work (between 2015-2021)?
- Combinatorics (59.44%)
- Bounded function (18.88%)
- Cluster analysis (20.28%)
In recent papers he was focusing on the following fields of study:
His scientific interests lie mostly in Combinatorics, Bounded function, Cluster analysis, Property testing and Discrete mathematics.
In his research, Christian Sohler undertakes multidisciplinary study on Combinatorics and Constant.
His Cluster analysis study combines topics from a wide range of disciplines, such as Time complexity and Algorithm.
The concepts of his Algorithm study are interwoven with issues in Coreset and Heuristics.
His Property testing study combines topics in areas such as Graph, Partition and Theoretical computer science.
In general Discrete mathematics study, his work on Adjacency matrix and Graph often relates to the realm of Streaming algorithm, thereby connecting several areas of interest.
Between 2015 and 2021, his most popular works were:
- Fair Coresets and Streaming Algorithms for Fair k-Means Clustering. (35 citations)
- Random projections for Bayesian regression (27 citations)
- Theoretical Analysis of the k -Means Algorithm – A Survey (27 citations)
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