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Deep Meta-Learning: Learning to Learn in the Concept Space., , and . CoRR, (2018)AABO: Adaptive Anchor Box Optimization for Object Detection via Bayesian Sub-sampling., , , , and . ECCV (5), volume 12350 of Lecture Notes in Computer Science, page 560-575. Springer, (2020)DHA: End-to-End Joint Optimization of Data Augmentation Policy, Hyper-parameter and Architecture., , , , , , and . Trans. Mach. Learn. Res., (2022)DetCLIPv2: Scalable Open-Vocabulary Object Detection Pre-training via Word-Region Alignment., , , , , , and . CVPR, page 23497-23506. IEEE, (2023)Transformation Invariant Few-Shot Object Detection., and . CVPR, page 3094-3102. Computer Vision Foundation / IEEE, (2021)ORDisCo: Effective and Efficient Usage of Incremental Unlabeled Data for Semi-Supervised Continual Learning., , , , , and . CVPR, page 5383-5392. Computer Vision Foundation / IEEE, (2021)Bridging the Gap between Sample-based and One-shot Neural Architecture Search with BONAS., , , , , and . NeurIPS, (2020)SODA10M: A Large-Scale 2D Self/Semi-Supervised Object Detection Dataset for Autonomous Driving., , , , , , , , , and 1 other author(s). NeurIPS Datasets and Benchmarks, (2021)Locally Differentially Private (Contextual) Bandits Learning., , , , and . NeurIPS, (2020)DetCLIP: Dictionary-Enriched Visual-Concept Paralleled Pre-training for Open-world Detection., , , , , , , , and . NeurIPS, (2022)