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University of California
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Provable system identification for partially observed linear dynamics is now possible even with up to 50% adversarial data poisoning.
Automating LiDAR annotation can cut down the labor-intensive process of data labeling while achieving near-human accuracy in segmentation tasks.
DO-ALL achieves long-term robustness in continual adaptation by distilling source information into compact anchors, sidestepping privacy issues without sacrificing performance.