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Reconstructing Training Data From Trained Neural Networks., , , , and . NeurIPS, (2022)On the Power and Limitations of Random Features for Understanding Neural Networks., and . NeurIPS, page 6594-6604. (2019)On the Benefits of Rank in Attention Layers., , and . CoRR, (2024)Locally Optimal Descent for Dynamic Stepsize Scheduling., , , , , and . CoRR, (2023)Width is Less Important than Depth in ReLU Neural Networks., , and . COLT, volume 178 of Proceedings of Machine Learning Research, page 1249-1281. PMLR, (2022)Proving the Lottery Ticket Hypothesis: Pruning is All You Need., , , and . ICML, volume 119 of Proceedings of Machine Learning Research, page 6682-6691. PMLR, (2020)RedEx: Beyond Fixed Representation Methods via Convex Optimization., , and . ALT, volume 237 of Proceedings of Machine Learning Research, page 518-543. PMLR, (2024)Reconstructing Training Data From Real World Models Trained with Transfer Learning., , , , , and . CoRR, (2024)Gradient Methods Provably Converge to Non-Robust Networks., , and . NeurIPS, (2022)The Effects of Mild Over-parameterization on the Optimization Landscape of Shallow ReLU Neural Networks., , and . COLT, volume 134 of Proceedings of Machine Learning Research, page 3889-3934. PMLR, (2021)