Parnian Kassraie
Ph.D. Student, ETH Zurich
pkassraie [AT] ethz.ch
Bio
I am a 2nd year Ph.D. student at the department of Computer Science at ETH Zurich, fortunate to be advised by Andreas Krause and Peter Bühlmann. I am a member of ETH Institute for Machine Learning and associated with the ETH AI Center. I work on Theory of Machine Learning, often in the context of Sequential Decision-making and Meta-learning.
I completed my M.Sc. at ETH, under the supervision of Andreas Krause and Fanny Yang, with a thesis on Contextual Neural Bandits. Before coming to ETH, I did a dual B.Sc. in Electrical Engineering and Computer Science at Sharif University of Technology. My thesis was on Visualizing Adversarial Attacks on Convolutional Neural Networks, which I wrote with Nassir Navab and Federico Tombari at TU Munich.
Publications
My work focuses on improving sequential decision-making algorithms in high-dimensional domains via
- Meta-learning sparse priors with oracle guarantees [META]
- Feature learning using NNs with provably valid confidence sets [NN]
Hallucinated Adversarial Control for Conservative Offline Policy Evaluation
Jonas Rothfuss*, Bhavya Sukhija*, Tobias Birchler*, Parnian Kassraie, Andreas Krause
arxiv Preprint, 2023
Lifelong Bandit Optimization: No prior and No Regret
Felix Schur*, Parnian Kassraie*, Jonas Rothfuss, Andreas Krause
arxiv Preprint, 2023
Instance-Dependent Generalization Bounds via Optimal Transport
Songyan Hou*, Parnian Kassraie*, Anastasis Kratsios*, Jonas Rothfuss*, Andreas Krause
arXiv Preprint, 2022
Graph Neural Network Bandits
Parnian Kassraie, Andreas Krause, Ilija Bogunovic
In Conference on Neural Information Processing Systems (NeurIPS), 2022
Meta-Learning Hypothesis Spaces for Sequential Decision-making
Parnian Kassraie, Jonas Rothfuss, Andreas Krause
In International Conference on Machine Learning (ICML), 2022
Also in Safe, Anytime-Valid Inference workshop (SAVI), 2022
Also in Adaptive Experimental Design and Active Learning Workshop (ReALML), 2022
Neural Contextual Bandits without Regret
Parnian Kassraie, Andreas Krause
In International Conference on Artificial Intelligence and Statistics (AISTATS), 2022
Lifelong Bandit Optimization: No prior and No Regret
Felix Schur*, Parnian Kassraie*, Jonas Rothfuss, Andreas Krause
arxiv Preprint, 2023
Meta-Learning Hypothesis Spaces for Sequential Decision-making
Parnian Kassraie, Jonas Rothfuss, Andreas Krause
In International Conference on Machine Learning (ICML), 2022
Also in Safe, Anytime-Valid Inference workshop (SAVI), 2022
Also in Adaptive Experimental Design and Active Learning Workshop (ReALML), 2022
Hallucinated Adversarial Control for Conservative Offline Policy Evaluation
Jonas Rothfuss*, Bhavya Sukhija*, Tobias Birchler*, Parnian Kassraie, Andreas Krause
arxiv Preprint, 2023
Instance-Dependent Generalization Bounds via Optimal Transport
Songyan Hou*, Parnian Kassraie*, Anastasis Kratsios*, Jonas Rothfuss*, Andreas Krause
arXiv Preprint, 2022
Graph Neural Network Bandits
Parnian Kassraie, Andreas Krause, Ilija Bogunovic
In Conference on Neural Information Processing Systems (NeurIPS), 2022
Neural Contextual Bandits without Regret
Parnian Kassraie, Andreas Krause
In International Conference on Artificial Intelligence and Statistics (AISTATS), 2022
News
- [06.02.23] Among AISTATS 2023 top 10% reviewers.
- [22.11.22] Attending NeurIPS@Paris. Presenting GNN Bandits.
- [03.11.22] New Preprints: Lifelong Bandit Optimization: No Prior and No Regret, and Instance-Dependent Generalization Bounds via Optimal Transport
- [12-16.09.22] Attending Quantifying Uncertainty Workshop @ Simons Institute. Presenting a poster on Meta-KeL and some new results.
- [17-23.07.22]
Attending ICML 2022, serving as a Session Chair. Presenting Meta-KeL at the main conference, and at ReALML.(visa arrived too late) - [15.07.22] New Preprint: Graph Neural Network Bandits
- [13.07.22] Among ICML 2022 top 10% reviewers.
- [21.06.22]
Invited to Deep Learning Theory Workshop @ Simons Institute.(visa arrived too late) - [07.06.22] Reviewing for NeurIPS and ReALML @ ICML.
- [01.06.22] Made it 1 year into the PhD.
- [30.05-03.06.22] Attending SAVI 2022. Presenting Meta-KeL.
- [28-30.03.22] 'Attending' AISTATS 2022. Presenting 'Neural Contextual Bandits without Regret'.
- [11.02.2022] Among AISTATS 2022 top 10% reviewers.
- [01.02.2022] New Preprint: Meta-KeL
- [29.01.22] Reviewing for ICML.
- [22.12.21] Giving a talk at ReACT 2021 on 'No-regret Bayesian Optimization with limited knowledge of the function space'.
- [15.10.21] Reviewing for AISTATS.
- [07.07.21] New Preprint: Neural Contextual Bandits without Regret
- [01.06.21] Started a PhD.