Matthew W. Hoffman
Matthew W. Hoffman publishes mostly in Artificial Intelligence, Computer Vision and Pattern Recognition and Computational Theory and Mathematics, on topics such as Machine Learning and Algorithms, Gaussian Processes and Bayesian Inference and Advanced Multi-Objective Optimization Algorithms.
- World rank
- #1,856,554 of 7,710,434 ranked researchers
- Rank in United States
- #568,652 of 1,627,098
- Works
- 30
- Citations
- 2.2k
- Citations per work
- 72.4
What does Matthew W. Hoffman research?
Matthew W. Hoffman's work is mostly in Computer Science (67%), Decision Sciences (9%), Engineering (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 Sciences2272.9%
- Computer Science2067.0%
- Engineering13.5%
- Physics and Astronomy12.4%
- Everything else517.7%
- Social Sciences39.4%
- Decision Sciences39.4%
- 1Artificial Intelligence44% of their works
- 2Computer Vision and Pattern Recognition13% of their works
- 3Computational Theory and Mathematics11% of their works
- 4Management Science and Operations Research9% of their works
- 5Biomedical Engineering4% of their works
- 6Statistical and Nonlinear Physics2% of their works
Research topics
Which keywords describe Matthew W. Hoffman's research?
The keywords of their largest research topics: Deep Learning, Gaussian Processes, Machine Learning, Bayesian Optimization, Semi-Supervised Learning, Image Classification, Neural Networks and Active Learning.
- Machine Translation
- Convolutional Neural Networks
- Domain Adaptation
- Reinforcement Learning
- Bandit Optimization
- Text Categorization
- Multiobjective Optimization
- Active Learning
- Image Classification
- Bayesian Optimization
- Gaussian Processes
- Deep Learning
- Machine Learning
- Semi-Supervised Learning
- Neural Networks
- Evolutionary Algorithms
- Sparse Regression
- Variational Inference
- Contextual Bandits
- Robotics
- Transfer Learning
- Image Recognition
- Word Representation
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.
All 23 words, with their numbers
- Deep Learning254 topics
- Gaussian Processes162 topics
- Machine Learning162 topics
- Bayesian Optimization152 topics
- Semi-Supervised Learning122 topics
- Image Classification112 topics
- Neural Networks92 topics
- Active Learning81 topic
- Evolutionary Algorithms81 topic
- Multiobjective Optimization81 topic
- Sparse Regression81 topic
- Text Categorization81 topic
- Variational Inference81 topic
- Bandit Optimization71 topic
- Contextual Bandits71 topic
- Reinforcement Learning61 topic
- Robotics61 topic
- Domain Adaptation41 topic
- Transfer Learning41 topic
- Convolutional Neural Networks31 topic
- Image Recognition31 topic
- Machine Translation31 topic
- Word Representation31 topic
Where does Matthew W. Hoffman work?
Matthew W. Hoffman's main affiliation in the publication record is Google (United States), United States.
How many publications and citations does Matthew W. Hoffman have?
OpenAlex counts 30 works and 2,172 citations for Matthew W. Hoffman, an h-index of 18, ranking #1,856,554 of 7,710,434 researchers worldwide on the quality score.
Ranked on field-normalised 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.
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