Papers

• LF. Toso, Y. LeCun, J. Anderson, O. Bounou "Preserving Unstable Modes Through Inverse Dynamics in JEPA World Models". Under review.
• LF. Toso, J. Anderson, R. Pinot, N. Gupta "Byzantine-Robust Federated Representation Learning". Under review.
• LF. Toso, J. Anderson, N. Gupta, R. Pinot, "On the Gradient Heterogeneity Dynamics of Adversarially Robust Federated Regression". Under review.
• LF. Toso^*, C. Stamouli^*, K. Fallah^*, G. Pappas, J. Anderson, "Multitask LQG Control: Performance and Generalization Bounds". Accepted at the 65th Conference on Decision and Control (CDC).
• LF. Toso^*, D. Shadunts^*, Y. Lu^*, G. Geng^*, Nihal Sharma, D. Zhan, NH. Nguyen, J. Anderson, "JEPA-Bisim: Learning Robust Visual Representations for Planning with Joint-Embedding Predictive World Models". Presented at L4DC and WM@Booth, 2026.
• K. Fallah^*, LF. Toso^*, J. Anderson, "Adversarially Robust Multitask Adaptive Control". L4DC 2026.
• A. Scampicchio^*, LF. Toso^*, R. Rickenbach, J. Anderson, M. Zeilinger, "Physics-informed learning under mixing: How physical knowledge speeds up learning". ICLR 2026.
• C. Stamouli^*, LF. Toso^*, A. Tsiamis, G. Pappas, J. Anderson, "Policy Gradient Bounds in Multitask LQR". IEEE L-CSS, 2025. ACC 2026.
• K. Fallah, LF. Toso, J. Anderson, "On the Gradient Domination of the LQG Problem". Under review.
• LF. Toso, L. Ye, J. Anderson, "Learning Stabilizing Policies via an Unstable Subspace Representation". CDC 2025 (Outstanding Paper Award).
• D. Zhan, LF. Toso, J. Anderson, "Coreset-Based Task Selection for Sample-Efficient Meta-Reinforcement Learning". CDC 2025.
• B. Lee^*, LF. Toso^*, T. Zhang^*, J. Anderson, N. Matni, "Regret Analysis of Multi-task Representation Learning for Linear-Quadratic Adaptive Control". AAAI, 2025.
• LF. Toso^*, H. Wang^*, J. Anderson, "Asynchronous Heterogeneous Linear Quadratic Regulator Design". CDC, 2024.
• Best Paper Award - LF. Toso, D. Zhang, J. Anderson, H. Wang, "Meta-Learning Linear Quadratic Regulators: A Policy Gradient MAML Approach for Model-free LQR". L4DC, 2024 (oral - top 7.5%).
• T. Zhang, LF. Toso, J. Anderson, N. Matni, "Sample-Efficient Linear Representation Learning from Non-IID Non-Isotropic Data". ICLR, 2024 (spotlight - top 5%).
• LF. Toso, H. Wang, J. Anderson, "Oracle Complexity Reduction for Model-free LQR: A Stochastic Variance-Reduced Policy Gradient Approach". ACC, 2024.
• H. Wang, LF. Toso, J. Anderson, "Model-free Learning with Heterogeneous Dynamical Systems: A Federated LQR Approach". To appear at Transactions on Machine Learning Research (TMLR), 2026.
• LF. Toso, H. Wang, J. Anderson, "Learning Personalized Models with Clustered System Identification". CDC, 2023.
• H. Wang, LF. Toso, J. Anderson, "Fedsysid: A federated approach to sample-efficient system identification". L4DC, 2023.
• LF. Toso, R. Drummond, S. Duncan, "Regional stability analysis of transitional fluid flows". IEEE Control Systems Letters, 2022.
• LF. Toso, G. Valmorbida, "Lyapunov Function computation for Periodic Linear Hybrid Systems via Handelman, Polya and SoS approaches: A comparative study". IFAC CAO, 2022.

^* denotes equal contribution.