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cs.LG2021
Simultaneous Perturbation Method for Multi-Task Weight Optimization in One-Shot Meta-Learning
Andrei Boiarov, Kostiantyn Khabarlak, Igor Yastrebov
Meta-learning methods aim to build learning algorithms capable of quickly adapting to new tasks in low-data regime. One of the most difficult benchmarks of such algorithms is a one…
cs.LG2020
Simultaneous Perturbation Stochastic Approximation for Few-Shot Learning
Andrei Boiarov, Oleg Granichin, Olga Granichina
Few-shot learning is an important research field of machine learning in which a classifier must be trained in such a way that it can adapt to new classes which are not included in…