What is he best known for?
The fields of study he is best known for:
- Statistics
- Artificial intelligence
- Algorithm
John N. Tsitsiklis mostly deals with Mathematical optimization, Dynamic programming, Computational complexity theory, Algorithm and Theoretical computer science.
The concepts of his Mathematical optimization study are interwoven with issues in Decision theory, Convergence, Upper and lower bounds and Markov decision process.
John N. Tsitsiklis combines subjects such as Computation, State space and Graph with his study of Dynamic programming.
His Computational complexity theory research includes elements of Time complexity, Computability, Stochastic control, Discretization and Integer.
His studies deal with areas such as Temporal difference learning, Markov process, Expected cost, Decentralised system and Nonlinear system as well as Algorithm.
His Theoretical computer science research incorporates elements of Parallel computing, Optimization problem, Decision problem and Decentralized decision-making.
His most cited work include:
- Parallel and Distributed Computation: Numerical Methods (4260 citations)
- Neuro-dynamic programming (3576 citations)
- Introduction to linear optimization (1933 citations)
What are the main themes of his work throughout his whole career to date?
His main research concerns Mathematical optimization, Discrete mathematics, Combinatorics, Algorithm and Theoretical computer science.
John N. Tsitsiklis works in the field of Mathematical optimization, namely Dynamic programming.
His work investigates the relationship between Discrete mathematics and topics such as Computational complexity theory that intersect with problems in Time complexity.
His Combinatorics study combines topics in areas such as Function and Upper and lower bounds.
John N. Tsitsiklis interconnects Distributed algorithm and Computation in the investigation of issues within Theoretical computer science.
He has included themes like Server and Traffic intensity in his Queue study.
He most often published in these fields:
- Mathematical optimization (34.12%)
- Discrete mathematics (11.29%)
- Combinatorics (10.35%)
What were the highlights of his more recent work (between 2009-2021)?
- Mathematical optimization (34.12%)
- Queue (9.18%)
- Bounded function (9.88%)
In recent papers he was focusing on the following fields of study:
John N. Tsitsiklis focuses on Mathematical optimization, Queue, Bounded function, Upper and lower bounds and Scheduling.
His work deals with themes such as Convergence, Network delay, Markov decision process and Topology, which intersect with Mathematical optimization.
His Queue research integrates issues from Discrete mathematics, Queueing theory, Server and Traffic intensity.
His Bounded function research incorporates themes from Mathematical economics, Computation, Quadratic growth and Graph.
He has researched Upper and lower bounds in several fields, including Markov process, Degree, Combinatorics, Exponential growth and Function.
His study in Function is interdisciplinary in nature, drawing from both Node and Algorithm.
Between 2009 and 2021, his most popular works were:
- Linearly Parameterized Bandits (285 citations)
- Weighted Gossip: Distributed Averaging using non-doubly stochastic matrices (192 citations)
- Convergence of Type-Symmetric and Cut-Balanced Consensus Seeking Systems (170 citations)
In his most recent research, the most cited papers focused on:
- Statistics
- Artificial intelligence
- Computer network
His primary scientific interests are in Mathematical optimization, Queue, Combinatorics, Convergence and Upper and lower bounds.
His Mathematical optimization research incorporates themes from Theoretical computer science, Markov decision process, Limit and Applied mathematics.
His studies in Queue integrate themes in fields like Scheduling, Distributed computing and Traffic intensity.
His Combinatorics research includes themes of Discrete mathematics, Multi-armed bandit, Degree of a polynomial and Symmetric polynomial.
The various areas that John N. Tsitsiklis examines in his Convergence study include Stochastic process, Multi-agent system and Topology.
His research in Algorithm intersects with topics in Distributed algorithm and Robustness.
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