Machine Learning Techniques for Predicting Molecular Properties
Event details
| Date | 06.07.2015 |
| Hour | 15:30 › 17:30 |
| Speaker | Viviana Petrescu |
| Location | |
| Category | Conferences - Seminars |
EDIC Candidacy Exam:
Exam president: Prof. Jean Philippe Thiran
Thesis director: Prof. Volkan Cevher
Thesis codirector: Prof. Christoph Koch
Co-examiner: Dr Pearl Pu
Research Proposal
Information-Theoretic Regret Bounds for Gaussian Process Optimization in the Bandit Setting by Niranjan Srinivas, Andreas Krause, Sham M. Kakade, and Matthias W. Seeger.
Self-taught Learning: Transfer Learning from Unlabeled Data by Rajat Raina, Alexis Battle, Honglak Lee, Benjamin Packer and Andrew Y. Ng.
Learning Invariant Representations of Molecules for Atomization Energy Prediction by Grégoire Montavon, et al.
Exam president: Prof. Jean Philippe Thiran
Thesis director: Prof. Volkan Cevher
Thesis codirector: Prof. Christoph Koch
Co-examiner: Dr Pearl Pu
Research Proposal
Information-Theoretic Regret Bounds for Gaussian Process Optimization in the Bandit Setting by Niranjan Srinivas, Andreas Krause, Sham M. Kakade, and Matthias W. Seeger.
Self-taught Learning: Transfer Learning from Unlabeled Data by Rajat Raina, Alexis Battle, Honglak Lee, Benjamin Packer and Andrew Y. Ng.
Learning Invariant Representations of Molecules for Atomization Energy Prediction by Grégoire Montavon, et al.
Practical information
- General public
- Free
Contact
- Evelyn Duperrex