What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Machine learning
- Statistics
Tobias Scheffer mainly focuses on Artificial intelligence, Machine learning, Support vector machine, Optimization problem and Pattern recognition.
A large part of his Artificial intelligence studies is devoted to Classifier.
His work carried out in the field of Classifier brings together such families of science as Semi-supervised learning, Information extraction and Knowledge representation and reasoning.
His Machine learning research integrates issues from Algorithm and Reduction.
His research integrates issues of Discriminative learning, Discriminative model and Covariate shift in his study of Optimization problem.
The concepts of his Structured support vector machine study are interwoven with issues in Least squares support vector machine, Web page, Naive Bayes classifier, Linear classifier and Class.
His most cited work include:
- Multi-view clustering (535 citations)
- Active Hidden Markov Models for Information Extraction (322 citations)
- Discriminative learning for differing training and test distributions (280 citations)
What are the main themes of his work throughout his whole career to date?
His scientific interests lie mostly in Artificial intelligence, Machine learning, Data mining, Support vector machine and Pattern recognition.
Artificial intelligence is closely attributed to Computer vision in his study.
His studies examine the connections between Machine learning and genetics, as well as such issues in Optimization problem, with regards to Email spam.
In his research, Web page is intimately related to Cluster analysis, which falls under the overarching field of Data mining.
Support vector machine is a component of his Structured support vector machine and Relevance vector machine studies.
His work focuses on many connections between Association rule learning and other disciplines, such as Knowledge extraction, that overlap with his field of interest in World Wide Web.
He most often published in these fields:
- Artificial intelligence (50.76%)
- Machine learning (34.09%)
- Data mining (19.70%)
What were the highlights of his more recent work (between 2015-2021)?
- Artificial intelligence (50.76%)
- Eye movement (5.30%)
- Encryption (3.79%)
In recent papers he was focusing on the following fields of study:
Tobias Scheffer spends much of his time researching Artificial intelligence, Eye movement, Encryption, Malware and Eye tracking.
His Artificial intelligence research incorporates elements of Machine learning and Computer vision.
His Eye movement research is multidisciplinary, relying on both Discriminative model, Generative model, Support vector machine and Convolutional neural network.
His Encryption research is multidisciplinary, incorporating elements of Timestamp, Data mining and Joint.
His study in Data mining is interdisciplinary in nature, drawing from both Optimization problem and Flooding.
Tobias Scheffer focuses mostly in the field of Eye tracking, narrowing it down to topics relating to Pattern recognition and, in certain cases, Generative grammar.
Between 2015 and 2021, his most popular works were:
- A Nonergodic Ground-Motion Model for California with Spatially Varying Coefficients (36 citations)
- Huber-Norm Regularization for Linear Prediction Models (14 citations)
- Malware Detection by Analysing Network Traffic with Neural Networks (12 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Machine learning
- Statistics
Tobias Scheffer mostly deals with Timestamp, Client, Computer network, Host and Malware.
Tobias Scheffer combines subjects such as Scalability, Traffic analysis, Network packet, Artificial neural network and Encryption with his study of Timestamp.
His study on Client is covered under Server.
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.
