Suchergebnisse
Suchergebnisse:
Principal Scientist, Google DeepMind. Publications , Google Scholar. Talks. Courses: Fall 2016: Stat155 Game theory. Spring 2016: CS281B/Stat241B Statistical learning theory. Fall 2015: CS281A/Stat241A Statistical learning theory. Spring 2015: CS189/289A Introduction to Machine Learning.
- Neural Network Learning
Martin Anthony and Peter L. Bartlett. This book describes...
- Talks
Peter Bartlett's Talks. Optimization in high-dimensional...
- Publications
Peter L. Bartlett, David P. Helmbold, and Philip M. Long....
- Biography
Peter Bartlett is a professor in the Department of...
- Achievements
Ella at four days: Last update: Sun Jun 30 21:49:09 2002
- Cs189/289A Introduction to Machine Learning
How to Sign In as a SPA. To sign in to a Special Purpose...
- Neural Network Learning
Neural network learning: Theoretical foundations. M Anthony, PL Bartlett, PL Bartlett. cambridge university press 9, 8. , 1999. 2533. 1999. For valid generalization the size of the weights is more important than the size of the network. P Bartlett. Advances in neural information processing systems 9.
24. Juli 2022 · Peter L. Bartlett. Professor. Department of Electrical Engineering and Computer Sciences. Department of Statistics. Berkeley AI Research Lab. University of California at Berkeley. Director. Collaboration on the Theoretical Foundations of Deep Learning. Director.
Peter Bartlett is a professor in the Department of Electrical Engineering and Computer Sciences and the Department of Statistics and Head of Google Research Australia. Since 2020, he has been Director of the Foundations of Data Science Institute and Director of the Collaboration on the Theoretical Foundations of Deep Learning.
Peter Bartlett is a professor of computer science and statistics at UC Berkeley and the head of Google Research Australia. He is an expert in machine learning and statistical learning theory, and has co-authored a book on neural network learning.
