Summary of Adaptive Data Optimization: Dynamic Sample Selection with Scaling Laws, by Yiding Jiang et al.
Adaptive Data Optimization: Dynamic Sample Selection with Scaling Lawsby Yiding Jiang, Allan Zhou, Zhili Feng,…
Summary of Analyzing Neural Scaling Laws in Two-layer Networks with Power-law Data Spectra, by Roman Worschech and Bernd Rosenow
Analyzing Neural Scaling Laws in Two-Layer Networks with Power-Law Data Spectraby Roman Worschech, Bernd RosenowFirst…
Summary of Scaling Laws Across Model Architectures: a Comparative Analysis Of Dense and Moe Models in Large Language Models, by Siqi Wang et al.
Scaling Laws Across Model Architectures: A Comparative Analysis of Dense and MoE Models in Large…
Summary of Searching For Efficient Linear Layers Over a Continuous Space Of Structured Matrices, by Andres Potapczynski et al.
Searching for Efficient Linear Layers over a Continuous Space of Structured Matricesby Andres Potapczynski, Shikai…
Summary of Neural Scaling Laws Of Deep Relu and Deep Operator Network: a Theoretical Study, by Hao Liu et al.
Neural Scaling Laws of Deep ReLU and Deep Operator Network: A Theoretical Studyby Hao Liu,…
Summary of How Feature Learning Can Improve Neural Scaling Laws, by Blake Bordelon et al.
How Feature Learning Can Improve Neural Scaling Lawsby Blake Bordelon, Alexander Atanasov, Cengiz PehlevanFirst submitted…
Summary of Rethinking Conventional Wisdom in Machine Learning: From Generalization to Scaling, by Lechao Xiao
Rethinking Conventional Wisdom in Machine Learning: From Generalization to Scalingby Lechao XiaoFirst submitted to arxiv…
Summary of Exploring Scaling Laws For Local Sgd in Large Language Model Training, by Qiaozhi He et al.
Exploring Scaling Laws for Local SGD in Large Language Model Trainingby Qiaozhi He, Xiaomin Zhuang,…
Summary of Provable In-context Learning Of Linear Systems and Linear Elliptic Pdes with Transformers, by Frank Cole et al.
Provable In-Context Learning of Linear Systems and Linear Elliptic PDEs with Transformersby Frank Cole, Yulong…
Summary of Scaling Law Hypothesis For Multimodal Model, by Qingyun Sun et al.
Scaling Law Hypothesis for Multimodal Modelby Qingyun Sun, Zhen Guo, PIN AI TeamFirst submitted to…