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cs.LG2025
Learning Regularizers: Learning Optimizers that can Regularize
Suraj Kumar Sahoo, Narayanan C Krishnan
Learned Optimizers (LOs), a type of Meta-learning, have gained traction due to their ability to be parameterized and trained for efficient optimization. Traditional gradient-based…
cs.LG2025
Tractable Sharpness-Aware Learning of Probabilistic Circuits
Hrithik Suresh, Sahil Sidheekh, Vishnu Shreeram M. P +2
Probabilistic Circuits (PCs) are a class of generative models that allow exact and tractable inference for a wide range of queries. While recent developments have enabled the learn…