. Unmasking the Lottery Ticket Hypothesis: What's Encoded in a Winning Ticket's Mask?. ICLR, 2023.

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. Limitations of Information-Theoretic Generalization Bounds for Gradient Descent Methods in Stochastic Convex Optimization. ALT, 2023.

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. The Effect of Data Dimensionality on Neural Network Prunability. NeurIPS ‘I Can’t Believe It’s Not Better’ Workshop: Understanding Deep Learning Through Empirical Falsification, 2022.

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. Understanding Generalization via Leave-One-Out Conditional Mutual Information. ISIT, 2022.

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. Pruning's Effect on Generalization Through the Lens of Training and Regularization. NeurIPS, 2022.

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. Lottery Tickets on a Data Diet: Finding Initializations with Sparse Trainable Networks. NeurIPS, 2022.

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. Towards a Unified Information-Theoretic Framework for Generalization. NeurIPS, 2021.

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. Deep Learning on a Data Diet: Finding Important Examples Early in Training. NeurIPS, 2021.

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. Information-Theoretic Generalization Bounds for Stochastic Gradient Descent. COLT, 2021.

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. On the role of data in PAC-Bayes bounds. AISTATS, 2021.

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. Pruning Neural Networks at Initialization: Why are We Missing the Mark?. ICLR, 2021.

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