What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Machine learning
- Programming language
Artificial intelligence, Data mining, Machine learning, Gene expression profiling and Mathematical optimization are his primary areas of study.
His work on Global optimization expands to the thematically related Artificial intelligence.
His Data mining study integrates concerns from other disciplines, such as Gene chip analysis, Microarray databases and Recommender system, Collaborative filtering.
Hugues Bersini interconnects Classifier and Pattern recognition in the investigation of issues within Machine learning.
His Mathematical optimization research includes themes of Simplex and Design methods.
The study incorporates disciplines such as Fuzzy set operations, Defuzzification and Fuzzy classification in addition to Neuro-fuzzy.
His most cited work include:
- A Survey on Filter Techniques for Feature Selection in Gene Expression Microarray Analysis (313 citations)
- Lazy learning for local modelling and control design (207 citations)
- Batch effect removal methods for microarray gene expression data integration: a survey (197 citations)
What are the main themes of his work throughout his whole career to date?
The scientist’s investigation covers issues in Artificial intelligence, Mathematical optimization, Machine learning, Artificial neural network and Theoretical computer science.
Artificial intelligence is closely attributed to Pattern recognition in his work.
His works in Optimal control and Multi-objective optimization are all subjects of inquiry into Mathematical optimization.
His Artificial neural network study frequently links to related topics such as Algorithm.
Hugues Bersini interconnects Fuzzy set operations, Fuzzy classification and Defuzzification in the investigation of issues within Neuro-fuzzy.
His research brings together the fields of Model selection and Lazy learning.
He most often published in these fields:
- Artificial intelligence (33.79%)
- Mathematical optimization (11.42%)
- Machine learning (10.96%)
What were the highlights of his more recent work (between 2012-2020)?
- Artificial intelligence (33.79%)
- Machine learning (10.96%)
- Atrial fibrillation (1.83%)
In recent papers he was focusing on the following fields of study:
His main research concerns Artificial intelligence, Machine learning, Atrial fibrillation, Collaborative filtering and Microeconomics.
His work on Artificial neural network is typically connected to Hyperlink as part of general Artificial intelligence study, connecting several disciplines of science.
He has researched Artificial neural network in several fields, including Algorithm, Clinical variables, Retrospective cohort study and Data set.
Hugues Bersini focuses mostly in the field of Collaborative filtering, narrowing it down to matters related to Recurrent neural network and, in some cases, Recommender system.
His work on Perfect competition as part of general Microeconomics research is frequently linked to Free market, bridging the gap between disciplines.
His work investigates the relationship between Convolutional neural network and topics such as Network topology that intersect with problems in State, Benchmark, Complex network and Topology.
Between 2012 and 2020, his most popular works were:
- Batch effect removal methods for microarray gene expression data integration: a survey (197 citations)
- Default Cascades in Complex Networks: Topology and Systemic Risk (122 citations)
- Long and Short-Term Recommendations with Recurrent Neural Networks (67 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Machine learning
- Programming language
Hugues Bersini focuses on Artificial intelligence, Topology, Complex network, Term and Recommender system.
His study looks at the relationship between Artificial intelligence and topics such as Graph, which overlap with Natural language processing and Information retrieval.
His biological study spans a wide range of topics, including Syntax and Scale-free network.
His research integrates issues of Stability, Network topology, Topology and Benchmark in his study of Complex network.
His Term study spans across into fields like Collaborative filtering, Recurrent neural network, Machine learning, Interpretation and Matrix decomposition.
Hugues Bersini performs multidisciplinary study on Sequence prediction and Data mining in his works.
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