Research interests- Decision theory
- Reinforcement learning and Control
- Machine learning and Statistics
- Security, Privacy and Fairness
Open Projects- Postdoc in multi-agent AI, mechanism design and differential privacy, in collaboration with Harvard.- Contact me for possible collaborations or projects.Current group members and collaborators- Aristide Tossou (Chalmers), PhD student on Secure and Private Machine Learning and Decision Making.
- Hannes Eriksson (Chalmers), PhD student on Autonomous Vehicles.
- Divya Grover (Chalmers), PhD student on Reinforcement Learning under Information and Computation Constraints.
- Raphael Duroselle (Ecole Polytechnique), Intern at Harvard.
- David Parkes (Harvard), Professor.
- Paul Tylkin (Harvard), PhD student (David Parkes).
- Goran Radanovic (Harvard), Postdoc.
- Yang Liu (Harvard), Postdoc
- Maryam Kamgarpour (ETHZ), Assistant Professor
- Nikolaos Tziortziotis (Ecole Polytechnique), Postdoc.
| News - Easing into a new position at Oslo from 2017. - On 50% parental leave for 2017/18 Teaching- Reinforcement Learning for Autonomous Vehicles (Chalmers)
- Database design (Lille)
- Data mining (Lille)
- Web fundamentals (Lille)
- Decision making under uncertainty
(Chalmers, University of Tokyo) - Algorithms, data structures and logic (Chalmers, 2014/2015 3)
- Artificial Intelligence (Chalmers, period 4, 2013/2014)
| Selected recent papers- Fair experimentation, CODE 2017.
- Multi-View Decision Processes, NIPS 2017.
- A differentially private encryption scheme, ISC 2017.
- Learning to Match, Value-aware and multi-stakeholder recommendation workshop at RecSys-17,
- Calibrated fairness In bandits, FATML-17.
- Subjective fairness: Fairness is in the eye of the beholder (working paper), 2017.
- Bayesian inference for Least Squares Temporal Difference regularization, ECML-17.
- Differential privacy for Bayesian Inference through posterior sampling, JMLR, 2017.
- Achieving privacy in the adversarial multi-armed bandit, AAAI 2017.
- Thompson sampling for stochastic bandits with graph feedback, AAAI 2017.
- Expected loss bounds for authentication in constrained channels. Journal of Computer Security, 2015.
- Cover tree Bayesian reinforcement learning. Journal of machine learning research, 2014.
- Personalized news recommendation with context trees, RecSys 2013.
- Probabilistic inverse reinforcement learning in unknown environments, UAI 2013.
- ABC reinforcement learning, ICML 2013.
|
