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Javier Porras-Valenzuela

2 accepted papers

2026

A Constrained Optimization Perspective of Unrolled Transformers

ICML 2026spotlight

We introduce a constrained optimization framework for training transformers that behave like optimization descent algorithms. Specifically, we enforce layerwise descent constraints on the objective function and replace standard empirical risk minimization (ERM) with a primal-dual training scheme. Th…

Cited by 0SourceScholar
2024

Loss Shaping Constraints for Long-Term Time Series Forecasting

ICML 2024poster

Several applications in time series forecasting require predicting multiple steps ahead. Despite the vast amount of literature in the topic, both classical and recent deep learning based approaches have mostly focused on minimising performance averaged over the predicted window. We observe that this…

Cited by 4SourcePDFScholar