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Found 6 papers, 0 papers with code
Regularization with Fake Features
We present a non-asymptotic high-probability bound on the generalization error of the ridge regression problem under the model misspecification of having fake features.
Continual Learning with Distributed Optimization: Does CoCoA Forget?
We focus on the continual learning problem where the tasks arrive sequentially and the aim is to perform well on the newly arrived task without performance degradation on the previously seen tasks.
Risk assessment and optimal allocation of security measures under stealthy false data injection attacks
The numerical example also illustrates that the security allocation using the Value-at-risk, and the impact on the nominal system may have different outcomes: thereby depicting the benefit of using risk metrics.
Estimation under Model Misspecification with Fake Features
Our results show that fake features can significantly improve the estimation performance, even though they are not correlated with the features in the underlying system.
Linear Regression with Distributed Learning: A Generalization Error Perspective
We provide high-probability bounds on the generalization error for both isotropic and correlated Gaussian data as well as sub-gaussian data.
Generalization Error for Linear Regression under Distributed Learning
We consider the setting where the unknowns are distributed over a network of nodes.
