What is he best known for?
The fields of study he is best known for:
- Quantum mechanics
- Mathematical analysis
- Algebra
Arnold Neumaier focuses on Mathematical optimization, Interval arithmetic, Applied mathematics, Discrete mathematics and Global optimization.
In his study, Branch and bound, Linear model and Finite difference is strongly linked to Function, which falls under the umbrella field of Mathematical optimization.
His Interval arithmetic research is multidisciplinary, incorporating elements of Rounding, Dynamical system and Integer programming.
The various areas that Arnold Neumaier examines in his Applied mathematics study include Linear system and Calculus.
His work investigates the relationship between Discrete mathematics and topics such as Combinatorics that intersect with problems in Eigenvalues and eigenvectors.
The study incorporates disciplines such as Optimization problem, Automatic differentiation and Directed acyclic graph in addition to Global optimization.
His most cited work include:
- Distance-Regular Graphs (2068 citations)
- Interval methods for systems of equations (1790 citations)
- Solving Ill-Conditioned and Singular Linear Systems: A Tutorial on Regularization (535 citations)
What are the main themes of his work throughout his whole career to date?
His primary scientific interests are in Mathematical optimization, Combinatorics, Discrete mathematics, Global optimization and Algorithm.
His work in the fields of Mathematical optimization, such as Optimization problem and Constrained optimization, overlaps with other areas such as Constraint satisfaction, Constraint satisfaction problem and Local consistency.
His studies link Eigenvalues and eigenvectors with Combinatorics.
Many of his studies involve connections with topics such as Applied mathematics and Discrete mathematics.
His work carried out in the field of Global optimization brings together such families of science as Interval arithmetic and Branch and bound.
His studies in Algorithm integrate themes in fields like Subgradient method and Convex optimization.
He most often published in these fields:
- Mathematical optimization (24.72%)
- Combinatorics (19.85%)
- Discrete mathematics (16.10%)
What were the highlights of his more recent work (between 2011-2021)?
- Mathematical optimization (24.72%)
- Algorithm (12.73%)
- Convex optimization (4.49%)
In recent papers he was focusing on the following fields of study:
His primary areas of study are Mathematical optimization, Algorithm, Convex optimization, Subgradient method and Constraint satisfaction problem.
In general Mathematical optimization, his work in Global optimization, Optimization problem and Branch and bound is often linked to Constraint satisfaction linking many areas of study.
Arnold Neumaier has researched Algorithm in several fields, including Scheme, Scale and Nonlinear system.
His work in the fields of Constraint satisfaction problem, such as Local consistency and Constraint satisfaction dual problem, intersects with other areas such as Interval arithmetic, Distance-regular graph and Graph.
His study looks at the intersection of Interval arithmetic and topics like Applied mathematics with Inverse, Square, Circle packing and Matrix.
His study focuses on the intersection of Simple and fields such as Lipschitz continuity with connections in the field of Discrete mathematics.
Between 2011 and 2021, his most popular works were:
- Global Attractivity of the Zero Solution for Wright's Equation (29 citations)
- OSGA: a fast subgradient algorithm with optimal complexity (24 citations)
- Black box optimization benchmarking of the global method (16 citations)
In his most recent research, the most cited papers focused on:
- Quantum mechanics
- Mathematical analysis
- Algebra
Arnold Neumaier mainly investigates Mathematical optimization, Algorithm, Global optimization, Subgradient method and Convex optimization.
His Mathematical optimization research incorporates elements of Process and Second-order cone programming.
His research in Second-order cone programming intersects with topics in Quadratic equation, Definite quadratic form, Quadratic residuosity problem, Applied mathematics and Sequential quadratic programming.
His Algorithm research is multidisciplinary, relying on both Scheme and Bounding overwatch.
His Global optimization study integrates concerns from other disciplines, such as Black box, Solver and Branch and bound.
His study ties his expertise on Discrete mathematics together with the subject of Convex optimization.
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