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GrOD: Deep Learning with Gradients Orthogonal Decomposition for Knowledge Transfer, Distillation, and Adversarial Training.

, , , , , , and . ACM Trans. Knowl. Discov. Data, 16 (6): 117:1-117:25 (2022)

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Large-scale Knowledge Distillation with Elastic Heterogeneous Computing Resources., , , , , , , and . CoRR, (2022)Towards Making Deep Transfer Learning Never Hurt., , , , and . ICDM, page 578-587. IEEE, (2019)Towards Inadequately Pre-trained Models in Transfer Learning., , , , , and . ICCV, page 19340-19351. IEEE, (2023)Adaptive Consistency Regularization for Semi-Supervised Transfer Learning., , , , and . CVPR, page 6923-6932. Computer Vision Foundation / IEEE, (2021)Quasi-optimal Data Placement for Secure Multi-tenant Data Federation on the Cloud., , , , , , , , and . IEEE BigData, page 1954-1963. IEEE, (2020)An optimized large-scale hybrid DGEMM design for CPUs and ATI GPUs., , , , and . ICS, page 377-386. ACM, (2012)Delta: Deep Learning Transfer using Feature Map with Attention for Convolutional Networks., , , , , and . ICLR (Poster), OpenReview.net, (2019)Classical vs Quantum Advice and Proofs Under Classically-Accessible Oracle., , , and . ITCS, volume 287 of LIPIcs, page 72:1-72:19. Schloss Dagstuhl - Leibniz-Zentrum für Informatik, (2024)Photorealistic Robotic Simulation using Unreal Engine 5 for Agricultural Applications., and . CoRR, (2024)How (not) to Build Quantum PKE in Minicrypt., , , and . CoRR, (2024)