Statistical Learning
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DINTR: Tracking via Diffusion-based Interpolation Pha Nguyen
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Object tracking is a fundamental task in computer vision, requiring the localization of objects of interest across video frames.
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Changing the Training Data Distribution to Reduce Simplicity Bias Improves In-distribution Generalization
Neural Information Processing Systems
By studying a two-layer CNN, we rigorously prove that SAM learns different features more uniformly, particularly in early epochs.
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