Optimization
Learning the Expected Core of Strictly Convex Stochastic Cooperative Games
Reward allocation, also known as the credit assignment problem, has been an important topic in economics, engineering, and machine learning.
due to a limited understanding of the mechanisms of the objective function. To
This problem configuration encompasses a broad range of applications in ML scenarios, e.g.
Approximation-Aware Bayesian Optimization
Our approach can be used with any decision-theoretic acquisition function and is readily compatible with trust region methods like TuRBO.
Boosting the Transferability of Adversarial Attack on Vision Transformer with Adaptive Token Tuning
Extensive experiments conducted on ViTs, undefended CNNs, and defended CNNs validate the superiority of our proposed A TT attack method. On average, our approach improves the attack performance by 10.1%
Globally Q-linear Gauss-Newton Method for Overparameterized Non-convex Matrix Sensing
Q-linear convergence of AGN represents a substantial enhancement over the convergence of the existing methods for the overparameterized non-convex LRMS.
