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Found 4 papers, 2 papers with code
Multivariate Quantile Function Forecaster
We propose Multivariate Quantile Function Forecaster (MQF$^2$), a global probabilistic forecasting method constructed using a multivariate quantile function and investigate its application to multi-horizon forecasting.
Learning Quantile Functions without Quantile Crossing for Distribution-free Time Series Forecasting
Quantile regression is an effective technique to quantify uncertainty, fit challenging underlying distributions, and often provide full probabilistic predictions through joint learnings over multiple quantile levels.
Avoiding The Double Descent Phenomenon of Random Feature Models Using Hybrid Regularization
To close this gap, the hybrid method considered in our paper combines the respective strengths of the two most common forms of regularization: early stopping and weight decay.
PNKH-B: A Projected Newton-Krylov Method for Large-Scale Bound-Constrained Optimization
We present an interior point method to solve the quadratic projection problem efficiently.
Numerical Analysis Numerical Analysis
