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arXiv research

A locally-built, LLM-digested index of recent arXiv papers in quant finance, geometry/topology, and statistical ML — keyword search served straight from SQLite on this machine.

168,695 papers · 148 categories

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2 results for “CIFAR-5m”

Kernel Regression with Infinite-Width Neural Networks on Millions of Examplesstat.ML

Researchers parallelize neural kernels for large-scale data, achieving state-of-the-art accuracy.

problem Limited scalability of neural kernels on large datasets.

method Massively parallel computation across many GPUs, combined with a distributed, preconditioned conjugate gradients algorithm.

result Achieved state-of-the-art accuracy of 91.2% on CIFAR-5m dataset using neural kernels.

neural kernels large-scale data parallel computing CIFAR-5m protein prediction

2023-03-09abs ↗pdf ↗

Theory of Optimal Learning Rate Schedules and Scaling Laws for a Random Feature Modelcond-mat.dis-nn

We find optimal learning rate schedules for a random feature model.

problem Choosing optimal learning rates for deep learning models.

method We analyze a powerlaw random feature model trained with SGD, considering optimal schedules as numerical and analytical problems.

result We discover two regimes: easy and hard phases, with different optimal learning rate schedules.

learning rate random feature model optimal schedule powerlaw stochastic gradient descent

2026-02-04abs ↗pdf ↗