Adversarial Weighting for Domain Adaptation in Regression
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Updated
Jun 1, 2022 - Jupyter Notebook
Adversarial Weighting for Domain Adaptation in Regression
(t, m, s)-nets generator / Генератор (t, m, s)-сетей
Wrapper for sampling methods in R and approximate star discrepancy calculation
KH-SGD iteratively reorders datapoints during stochastic gradient descent training to provably accelerate convergence.
Code and data for an empirical square-root law of the degree discrepancy of binary m-sequences. Joonas Pääkkönen. Dr. Sci. Senior lecturer, Department of Information and Data Management, Dalarna University, Borlänge, Sweden.
Generalized Golden Spiral methods for quasi-random low-discrepancy points generation.
Domain Adaptation with Dynamic Open-Set Targets
Issues reported in the official Trello REST API documentation
Service for calculation of discrepancy between of two datasets marketing oriented
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