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stat.ML2023
Provable benefits of annealing for estimating normalizing constants: Importance Sampling, Noise-Contrastive Estimation, and beyond
Omar Chehab, Aapo Hyvarinen, Andrej Risteski
Recent research has developed several Monte Carlo methods for estimating the normalization constant (partition function) based on the idea of annealing. This means sampling success…
stat.ML2023
Optimizing the Noise in Self-Supervised Learning: from Importance Sampling to Noise-Contrastive Estimation
Omar Chehab, Alexandre Gramfort, Aapo Hyvarinen
Self-supervised learning is an increasingly popular approach to unsupervised learning, achieving state-of-the-art results. A prevalent approach consists in contrasting data points…