Publications

Faster Rates for No-Regret Learning in General Games via Cautious Optimism
Ashkan Soleymani, Georgios Piliouras, and Gabriele Farina
The Annual ACM Symposium on Theory of Computing (STOC), 2025
Learning with Exact Invariances in Polynomial Time
Ashkan Soleymani*, Behrooz Tahmasebi*, Stefanie Jegelka, and Patrick Jaillet
submitted to International Conference on Learning Representations (ICML), 2025
Conference on Parsimony and Learning (CPAL), Recent Spotlight Track, 2025
A Robust Kernel Statistical Test of Invariance: Detecting Subtle Asymmetries
Ashkan Soleymani*, Behrooz Tahmasebi*, Stefanie Jegelka, and Patrick Jaillet
International Conference on Artificial Intelligence and Statistics (AISTAT), 2025 (Oral Presentation - Top 2% of Submissions)
Conference on Parsimony and Learning (CPAL), Recent Spotlight Track, 2025
Learning Decision Policies with Instrumental Variables through Double Machine Learning
Daqian Shao, Ashkan Soleymani, Francesco Quinzan, Marta Kwiatkowska
International Conference on Machine Learning (ICML), 2024
A Universal Class of Sharpness-Aware Minimization Algorithms
Behrooz Tahmasebi, Ashkan Soleymani, Dara Bahri, Stefanie Jegelka, and Patrick Jaillet
International Conference on Machine Learning (ICML), 2024
High-dimensional Learning Dynamics: The Emergence of Structure and Reasoning (HiLD @ ICML workshop), 2024 (Best Paper Award)
On Scale-Invariant Sharpness Measures
Behrooz Tahmasebi, Ashkan Soleymani, Stefanie Jegelka, and Patrick Jaillet
Mathematics of Modern Machine Learning (M3L @ NeurIPS workshop), 2023
DRCFS: Doubly Robust Causal Feature Selection
Francesco Quinzan*, Ashkan Soleymani*, Patrick Jaillet, Cristian R. Rojas, and Stefan Bauer
International Conference on Machine Learning (ICML), 2023
Causal Feature Selection via Orthogonal Search
Ashkan Soleymani*, Anant Raj*, Michel Besserve, Stefan Bauer and Bernhard Schölkopf
Transactions on Machine Learning Research (TMLR), 2022
Pyfectious: A probabilistic hierarchical simulator of infectious diseases and fine-grained control measures
Arash Mehrjo*, Ashkan Soleymani*, Amin Abyaneh, Samir Bhatt, Stefan Bauer and Bernhard Schölkopf
PLOS Computational Biology 19(1): e1010799, 2023
GeneDisco: A Benchmark for Experimental Design in Drug Discovery
Arash Mehrjou, Ashkan Soleymani, Andrew Jesson, Pascal Notin, Yarin Gal, Stefan Bauer, and Patrick Schwab
International Conference on Learning Representations (ICLR), 2022
Adaptive Experimental Design and Active Learning in the Real World (ReALML @ ICML workshop), 2022 (Spotlight Presentation)

Preprints and submissions

Cautious Optimism: A Meta-Algorithm for Near-Constant Regret in General Games
Ashkan Soleymani, Georgios Piliouras, and Gabriele Farina
submitted to The Twenty-Sixth ACM Conference on Economics and Computation (EC), 2025
Doubly Robust Structure Identification from Temporal Data
Emmanouil Angelis, Francesco Quinzan, Ashkan Soleymani, Patrick Jaillet and Stefan Bauer
submitted to International Conference on Learning Representations (ICML), 2025
Physical Derivatives: Computing policy gradients by physical forward-propagation
Arash Mehrjou, Ashkan Soleymani, Stefan Bauer and Bernhard Schölkopf
arXiv:2201.05830, 2022
Federated Learning in Multi-Center Critical Care Research: A Systematic Case Study using the eICU Database
Arash Mehrjou*, Ashkan Soleymani*, Annika Buchholz, Jürgen Hetzel, Patrick Schwab and Stefan Bauer
arXiv:2204.09328, 2021
* denotes equal contributions.