Optimization
AQuantitativeGeometricApproachto Neural-NetworkSmoothness
The techniques for theℓ2-perturbation do not easily transfer to theℓ -case (Leino et al., 2021). One critical step is to measure the Lipschitz constant more precisely and efficiently.
Scalable Hyperparameter Transfer Learning
Valerio Perrone, Rodolphe Jenatton, Matthias W. Seeger, Cedric Archambeau
In this work, we aim to warm-start BO in the context of hyperparameter optimization (HPO).
Provably Correct Automatic Sub-Differentiation for Qualified Programs
Neural Information Processing Systems http://nips.cc/
and
Successfully employing cutting planes can be challenging because there are infinitely many cuts to choose from and there are still many open questions about which cuts to employ when.
Greedy Hash: Towards Fast Optimization for Accurate Hash Coding in CNN
Shupeng Su, Chao Zhang, Kai Han, Yonghong Tian
Neural Information Processing Systems http://nips.cc/
Efficient Convex Completion of Coupled Tensors using Coupled Nuclear Norms
Kishan Wimalawarne, Hiroshi Mamitsuka
Neural Information Processing Systems http://nips.cc/