Vector quantization induces a structured partition of the representation space for composing heterogeneous multiclass calibration maps via shared codeword-dependent Dirichlet factors.
The elements of statistical learning
3 Pith papers cite this work. Polarity classification is still indexing.
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Negative-capable ridge regression uses controlled negative regularization as anti-shrinkage to increase effective complexity along weak eigendirections and mitigate underfitting in small-data regression.
Multi-pipeline machine learning with conformal prediction up-ranks subthreshold LIGO/Virgo candidates, including GW200311_103121, as signal-like.
citing papers explorer
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Divide et Calibra: Multiclass Local Calibration via Vector Quantization
Vector quantization induces a structured partition of the representation space for composing heterogeneous multiclass calibration maps via shared codeword-dependent Dirichlet factors.
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A Ridge Too Far: Correcting Over-Shrinkage via Negative Regularization
Negative-capable ridge regression uses controlled negative regularization as anti-shrinkage to increase effective complexity along weak eigendirections and mitigate underfitting in small-data regression.
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Combining gravitational wave search pipelines to find subthreshold signals in GWTC-5.0
Multi-pipeline machine learning with conformal prediction up-ranks subthreshold LIGO/Virgo candidates, including GW200311_103121, as signal-like.