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

  1. Meta-learning sparse priors with oracle guarantees [META]
  2. Feature learning using NNs with provably valid confidence sets [NN]

Instance-Dependent Generalization Bounds via Optimal Transport

Songyan Hou*, Parnian Kassraie*, Anastasis Kratsios*, Jonas Rothfuss*, Andreas Krause

arXiv Preprint, 2022

Lifelong Bandit Optimization: No prior and No Regret

Felix Schur, Parnian Kassraie, 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, 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

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

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