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Multinomial Distribution Learning for Effective Neural Architecture Search., , , , , and . ICCV, page 1304-1313. IEEE, (2019)Dynamic Distribution Pruning for Efficient Network Architecture Search., , , , , , , and . CoRR, (2019)Meta Architecture for Point Cloud Analysis., , , , , , , and . CVPR, page 17682-17691. IEEE, (2023)EBFT: Effective and Block-Wise Fine-Tuning for Sparse LLMs., , , , , , , and . CoRR, (2024)MIGO-NAS: Towards Fast and Generalizable Neural Architecture Search., , , , , , , , and . IEEE Trans. Pattern Anal. Mach. Intell., 43 (9): 2936-2952 (2021)Depth-Guided Semi-Supervised Instance Segmentation., , , , , and . CoRR, (2024)Uncovering the Over-Smoothing Challenge in Image Super-Resolution: Entropy-Based Quantification and Contrastive Optimization., , , , , , , and . IEEE Trans. Pattern Anal. Mach. Intell., 46 (9): 6199-6215 (September 2024)Event-Diffusion: Event-Based Image Reconstruction and Restoration with Diffusion Models., , , , , and . ACM Multimedia, page 3837-3846. ACM, (2023)Centralized Ranking Loss with Weakly Supervised Localization for Fine-Grained Object Retrieval., , , , , and . IJCAI, page 1226-1233. ijcai.org, (2018)Solving Oscillation Problem in Post-Training Quantization Through a Theoretical Perspective., , , , , , , , and . CVPR, page 7950-7959. IEEE, (2023)