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Found 5 papers, 5 papers with code
Investigating the Corruption Robustness of Image Classifiers with Random Lp-norm Corruptions
In the field of adversarial robustness of image classifiers, robustness is commonly defined as the stability of a model to all input changes within a p-norm distance.
Adaptive Stochastic Optimisation of Nonconvex Composite Objectives
In this paper, we propose and analyse a family of generalised stochastic composite mirror descent algorithms.
Adaptive Zeroth-Order Optimisation of Nonconvex Composite Objectives
In this paper, we propose and analyze algorithms for zeroth-order optimization of non-convex composite objectives, focusing on reducing the complexity dependence on dimensionality.
Optimistic Optimisation of Composite Objective with Exponentiated Update
Furthermore, the algorithms have efficient implementations for popular composite objectives and constraints and can be converted to stochastic optimisation algorithms with the optimal accelerated rate for smooth objectives.
Graduated Optimization of Black-Box Functions
Motivated by the problem of tuning hyperparameters in machine learning, we present a new approach for gradually and adaptively optimizing an unknown function using estimated gradients.
