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Topics in statistical physics of high-dimensional machine learning

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Topics in statistical physics of high-dimensional machine learning

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Neural Set Function Extensions: Learning with Discrete Functions in High Dimensions

Efficient Transformer-Based Speech Recognition

Trace norm regularization for multi-task learning with scarce data

Phase diagram of Stochastic Gradient Descent in high-dimensional two-layer neural networks

Using Machine Learning to Predict Mortality for COVID-19 Patients on Day 0 in the ICU

Kernel Methods and Similarity Learning Applied in Computational Chemistry

Metric learning for kernel ridge regression: assessment of molecular similarity

Motion Style Transfer: Modular Low-Rank Adaptation for Deep Motion Forecasting

System Support for Robust Distributed Learning

HDTorch: Accelerating Hyperdimensional Computing with GP-GPUs for Design Space Exploration