Christos Dimitrakakis

Research interests
- Artificial intelligence and society
- Differential privacy
- Reinforcement learning
Teaching
Autumn semester: IN-STK5000, Adaptive methods for data-based decision making, which is a course on:
- Graphical models and Bayesian inference
- Decision theory
- Reproducibility in data-driven science
- Privacy
- Fairness
- Causality
- Adaptive experiment design
- Markov decision processes (introductory)
Spring semester: IN-STK5100, Reinforcement learning and decision making under uncertainty, which is a course on
- Decision theory
- Concentration inequalities and PAC theory
- Bandit theory
- Markov decision process theory
- Reinforcement learning
- Stochastic approximation
- Regret bounds
Publications
- Bayesian fairness, AAAI 2019.
- Randomised Bayesian Least-Squares Policy Iteration, EWRL 2018.
- Multi-View Decision Processes, [poster] [video] [slides] NIPS 2017.
- Calibrated fairness In bandits, FATML-17.
- Differential privacy for Bayesian Inference through posterior sampling, JMLR, 2017.
- Achieving privacy in the adversarial multi-armed bandit, AAAI 2017.
- Cover tree Bayesian reinforcement learning. J. Mach. Learn. Res. 15(1): 2313-2335 (2014)
- ABC Reinforcement Learning. ICML (3) 2013: 684-692
- Probabilistic inverse reinforcement learning in unknown environments. UAI 2013
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- Robust Bayesian Reinforcement Learning through Tight Lower Bounds. EWRL 2011: 177-188
- Bayesian Multitask Inverse Reinforcement Learning. EWRL 2011: 273-284
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Complexity of stochastic branch and bound methods for belief tree search in Bayesian reinforcement learning. CoRR abs/0912.5029 (2009)
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Rollout sampling approximate policy iteration. Machine Learning 72(3): 157-171 (2008)
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Nearly Optimal Exploration-Exploitation Decision Thresholds. ICANN (1) 2006: 850-859
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- Dimitrakakis, Christos; Liu, Yang; Parkes, David C. & Radanovic, Goran (2019). Bayesian fairness, In Proceedings of the AAAI Conference on Artificial Intelligence. AAAI Press. ISBN 978-1-57735-809-1. KAPITTEL.
- Ekström, Andreas; Forssen, Christian; Dimitrakakis, Christos; Dubhashi, Devdatt; Johansson, H. T.; Salomonsson, Hans & Schliep, Alexander (2019). Bayesian optimization in ab initio nuclear physics. Journal of Physics G: Nuclear and Particle Physics. ISSN 0954-3899. 46(9) . doi: 10.1088/1361-6471/ab2b14
- Dimitrakakis, Christos; Nelson, Blaine; Zhang, Zuhe; Mitrokotsa, Aikateirni & Rubinstein, Benjamin I.P. (2017). Differential privacy for Bayesian inference through posterior sampling. Journal of machine learning research. ISSN 1532-4435. 18(1)
- Dimitrakakis, Christos (2020). Differential privacy in energy systems.
- Eriksson, Hannes & Dimitrakakis, Christos (2020). Epistemic Risk-Sensitive Reinforcement Learning.
- Grover, Divya; Basu, Debabrota & Dimitrakakis, Christos (2020). Bayesian Reinforcement Learning via Deep, Sparse Sampling.
- Jorge, Emilio; Eriksson, Hannes; Dimitrakakis, Christos; Basu, Debabrota & Grover, Divya (2020). Inferential Induction: A Novel Framework for Bayesian Reinforcement Learning.
- Tossou, Aristide; Dimitrakakis, Christos; Rzepecki, Jaroslaw & Hofmann, Katja (2020). A Novel Individually Rational Objective In Multi-Agent Multi-Armed Bandits: Algorithms and Regret Bounds.
- Boroujeni, Mahrokh Ghoddousi; Fay, Dominik; Dimitrakakis, Christos & Kamgarpour, Maryam (2019). Privacy of Real-Time Pricing in Smart Grid.
- Dimitrakakis, Christos; Liu, Yang; Parkes, David C. & Radanovic, Goran (2019). Bayesian fairness.
- Dimitrakakis, Christos; Parkes, David C.; Radanovic, Goran & Tylkin, Paul (2017). Multi-View Decision Processes: The Helper-AI Problem.