26 citations · 91 across the 27 of their papers we have counts for
4 papers · 1 filter
On Optimization Complexity of Second-Order Certified Unlearning
Nikita Doikov, Anastasia Koloskova
We study machine unlearning: the removal of memorized training data from a trained model. Specifically, we investigate the algorithmic complexity of certified unlearning from an op…
PACER: Acyclic Causal Discovery from Large-Scale Interventional Data
Ramon Viñas Torné, Sílvia Fàbregas Salazar, Soyon Park +4
Inferring the structure of directed acyclic graphs (DAGs) from data is a central challenge in causal discovery, particularly in modern high-dimensional settings where large-scale i…
Cubic regularized subspace Newton for non-convex optimization
Jim Zhao, Aurelien Lucchi, Nikita Doikov
This paper addresses the optimization problem of minimizing non-convex continuous functions, which is relevant in the context of high-dimensional machine learning applications char…
On Convergence of Incremental Gradient for Non-Convex Smooth Functions
Anastasia Koloskova, Nikita Doikov, Sebastian U. Stich +1
In machine learning and neural network optimization, algorithms like incremental gradient, and shuffle SGD are popular due to minimizing the number of cache misses and good practic…