Peng Zhao
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The paper proposes a novel online learning algorithm that achieves an interval regret bound scaling with gradient variation, providing strong theoretical guarantees for non-stationary environments.
This paper proposes a method for handling overparameterized linear regression using early-stopped negative-shifted gradient descent, which allows for smooth filters and mixed-sign capabilities.
Papers
Beyond Negative-Ridge Endpoints: Mixed-Sign Spectral Regularization via Negative-Shifted Gradient Descent
This paper proposes a method for handling overparameterized linear regression using early-stopped negative-shifted gradient descent, which allows for smooth filters and mixed-sign capabilities.