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cs.LG2025
Training Instabilities Induce Flatness Bias in Gradient Descent
Lawrence Wang, Stephen J. Roberts
Classical analyses of gradient descent (GD) define a stability threshold based on the largest eigenvalue of the loss Hessian, often termed sharpness. When the learning rate lies be…
cs.LG2025
Pruning Cannot Hurt Robustness: Certified Trade-offs in Reinforcement Learning
James Pedley, Benjamin Etheridge, Stephen J. Roberts +1
Reinforcement learning (RL) policies deployed in real-world environments must remain reliable under adversarial perturbations. At the same time, modern deep RL agents are heavily o…
cs.LG2025
Beyond Accuracy: EcoL2 Metric for Sustainable Neural PDE Solvers
Taniya Kapoor, Abhishek Chandra, Anastasios Stamou +1
Real-world systems, from aerospace to railway engineering, are modeled with partial differential equations (PDEs) describing the physics of the system. Estimating robust solutions…