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ProteusTM: Abstraction Meets Performance in Transactional Memory

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ProteusTM: Abstraction Meets Performance in Transactional Memory

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Regularization of polynomial networks for image recognition

Improving Generalization of Pretrained Language Models

Leveraging Unlabeled Data to Track Memorization

Bayesian Inversion for Nonlinear Imaging Models Using Deep Generative Priors

TEE-based decentralized recommender systems: The raw data sharing redemption

In-Memory Hardware and Architectural Extensions for Workloads Acceleration

Generalization of an Encoder-Decoder LSTM model for flood prediction in ungauged catchments

Deep Learning Generalization with Limited and Noisy Labels

Regularization of polynomial networks for image recognition