most citedEstimation under Model Misspecification with Fake Features

11 citations · 17 across the 5 of their papers we have counts for

collaborators

5 papers

cs.LG2023

Distributed Continual Learning with CoCoA in High-dimensional Linear Regression

Martin Hellkvist, Ayça Özçelikkale, Anders Ahlén

We consider estimation under scenarios where the signals of interest exhibit change of characteristics over time. In particular, we consider the continual learning problem where di…

cs.LG2022

Regularization Trade-offs with Fake Features

Martin Hellkvist, Ayça Özçelikkale, Anders Ahlén

Recent successes of massively overparameterized models have inspired a new line of work investigating the underlying conditions that enable overparameterized models to generalize w…

stat.ML2022★ 1 cited

Continual Learning with Distributed Optimization: Does CoCoA Forget?

Martin Hellkvist, Ayça Özçelikkale, Anders Ahlén

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 previ…

eess.SY2022★ 5 cited

Risk assessment and optimal allocation of security measures under stealthy false data injection attacks

Sribalaji C. Anand, André M. H. Teixeira, Anders Ahlén

This paper firstly addresses the problem of risk assessment under false data injection attacks on uncertain control systems. We consider an adversary with complete system knowledge…

eess.SP2022★ 11 cited

Estimation under Model Misspecification with Fake Features

Martin Hellkvist, Ayça Özçelikkale, Anders Ahlén

We consider estimation under model misspecification where there is a model mismatch between the underlying system, which generates the data, and the model used during estimation. W…