Csaba Szepesvári
Csaba Szepesvári publishes mostly in Artificial Intelligence, Management Science and Operations Research and Computer Networks and Communications, on topics such as Advanced Bandit Algorithms Research, Reinforcement Learning in Robotics and Machine Learning and Algorithms.
- World rank
- #182,656 of 7,710,434 ranked researchers
- Rank in Canada
- #6,139 of 183,316
- Works
- 457
- Citations
- 17k
- Citations per work
- 37.1
What does Csaba Szepesvári research?
Csaba Szepesvári's work is mostly in Computer Science (55%), Decision Sciences (23%), Mathematics (4%).
Their six largest subfields, inside their fields and domains; the grey slice is everything else they publish. The interactive view splits every one of their works down to single topics.
The fields and subfields, with their numbers
- Physical Sciences26658.3%
- Computer Science25054.8%
- Mathematics163.5%
- Social Sciences10422.7%
- Decision Sciences10422.7%
- Everything else8719.0%
- 1Artificial Intelligence42% of their works
- 2Management Science and Operations Research23% of their works
- 3Computer Networks and Communications6% of their works
- 4Computational Theory and Mathematics4% of their works
- 5Statistics and Probability4% of their works
- 6Computer Vision and Pattern Recognition3% of their works
Research topics
Which keywords describe Csaba Szepesvári's research?
The keywords of their largest research topics: Deep Learning, Convex Optimization, Bandit Optimization, Bayesian Optimization, Neural Networks, Reinforcement Learning, Robotics and Semi-Supervised Learning.
- Markov Chain
- Bayesian Monte Carlo
- Random Projections
- Auction Theory
- Online Algorithms
- Machine Learning
- Semi-Supervised Learning
- Reinforcement Learning
- Bayesian Optimization
- Convex Optimization
- Deep Learning
- Bandit Optimization
- Neural Networks
- Robotics
- Active Learning
- Mobile Robots
- Approximation Algorithms
- Mechanism Design
- Stochastic Gradient Descent
- Domain Adaptation
- Transfer Learning
Size is their works in the topics tagged with each word, from their 8 largest topics. Each links to the topic it comes from most. The words come from the keyword list OpenAlex gives each topic, not from the text of the papers, so a word can appear that none of the papers uses.
All 21 words, with their numbers
- Deep Learning3393 topics
- Convex Optimization2552 topics
- Bandit Optimization2231 topic
- Bayesian Optimization2231 topic
- Neural Networks1972 topics
- Reinforcement Learning1651 topic
- Robotics1651 topic
- Semi-Supervised Learning1652 topics
- Active Learning1421 topic
- Machine Learning1421 topic
- Mobile Robots561 topic
- Online Algorithms561 topic
- Approximation Algorithms552 topics
- Auction Theory331 topic
- Mechanism Design331 topic
- Random Projections321 topic
- Stochastic Gradient Descent321 topic
- Bayesian Monte Carlo231 topic
- Domain Adaptation231 topic
- Markov Chain231 topic
- Transfer Learning231 topic
Where does Csaba Szepesvári work?
Csaba Szepesvári's main affiliation in the publication record is University of Alberta, Canada.
How many publications and citations does Csaba Szepesvári have?
OpenAlex counts 457 works and 16,962 citations for Csaba Szepesvári, an h-index of 57, ranking #182,656 of 7,710,434 researchers worldwide on the quality score.
Ranked on field-normalised citation excellence (50%), output (30%) and citations (20%). Counts come from OpenAlex author records, which occasionally merge different people who share a name or split one person into several.
Papers, co-authors, who cited this work and researchers on the nearest topics have tabs of their own, above. Is this your page? Claim it with your ORCID iD, or request a correction or removal.
Discussion
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