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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.

168,742 papers · 148 categories

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2 results for “g-Layers”
Post-hoc Calibration of Neural Networks by g-Layerscs.LG

Post-hoc calibration of neural networks using g-Layers proves theoretical justification.

problem Ensuring the confidence of neural network decisions in real-world applications.
method Proves theoretical justification for post-hoc calibration methods by adding g-Layers and minimizing NLL.
result Proves that adding g-Layers and minimizing NLL can lead to a calibrated network.
Neural NetworksCalibrationPost-Hoc Calibrationg-LayersNegative Log-Likelihood
2020-06-23abs ↗pdf ↗
Impact of classification difficulty on the weight matrices spectra in Deep Learning and application to early-stoppingcs.LG

The difficulty of classification affects the weight matrices' heavy tail appearance in deep learning networks.

problem Understanding the spectral properties of weight matrices in deep learning networks.
method Spectral analysis of weight matrices in different modules of DNNs, classification difficulty as a driving factor for heavy tail appearance.
result Higher classification difficulty leads to more frequent appearance of heavy tails in weight matrices spectra.
Deep LearningRandom Matrix TheoryWeight MatricesClassification DifficultyHeavy Tails
2021-11-26abs ↗pdf ↗