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cs.LG2026
Differentiable Efficient Operator Search
Xiaohuan Pei, Jiyuan Zhang, Yuanfan Guo +4
Efficient multimodal foundation models often rely on manually designed token-reduction operators, such as pruning, merging, pooling, and adaptive reweighting. Although these operat…
cs.LG2026
Scalable Hyperparameter-Divergent Ensemble Training with Automatic Learning Rate Exploration for Large Models
Hailing Cheng, Tao Huang, Chen Zhu +1
Training large neural networks with data-parallel stochastic gradient descent allocates N GPU replicas to compute effectively identical updates -- a practice that leaves the rich s…
cs.LG2023
Adaptive Training Meets Progressive Scaling: Elevating Efficiency in Diffusion Models
Wenhao Li, Xiu Su, Yu Han +3
Diffusion models have demonstrated remarkable efficacy in various generative tasks with the predictive prowess of denoising model. Currently, diffusion models employ a uniform deno…