Introduces a regularized estimator achieving optimal MSE rates under a new relative balancedness condition while providing safety guarantees that match independent learning when tasks are unrelated.
International Conference on Machine Learning , pages=
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Multi-task Linear Regression without Eigenvalue Lower Bounds: Adaptivity, Robustness and Safety
Introduces a regularized estimator achieving optimal MSE rates under a new relative balancedness condition while providing safety guarantees that match independent learning when tasks are unrelated.