Summary of Review Of Interpretable Machine Learning Models For Disease Prognosis, by Jinzhi Shen and Ke Ma
Review of Interpretable Machine Learning Models for Disease Prognosisby Jinzhi Shen, Ke MaFirst submitted to…
Summary of Learning Regularities From Data Using Spiking Functions: a Theory, by Canlin Zhang and Xiuwen Liu
Learning Regularities from Data using Spiking Functions: A Theoryby Canlin Zhang, Xiuwen LiuFirst submitted to…
Summary of Netmamba: Efficient Network Traffic Classification Via Pre-training Unidirectional Mamba, by Tongze Wang et al.
NetMamba: Efficient Network Traffic Classification via Pre-training Unidirectional Mambaby Tongze Wang, Xiaohui Xie, Wenduo Wang,…
Summary of Comparisons Are All You Need For Optimizing Smooth Functions, by Chenyi Zhang and Tongyang Li
Comparisons Are All You Need for Optimizing Smooth Functionsby Chenyi Zhang, Tongyang LiFirst submitted to…
Summary of A Dual Power Grid Cascading Failure Model For the Vulnerability Analysis, by Tianxin Zhou et al.
A Dual Power Grid Cascading Failure Model for the Vulnerability Analysisby Tianxin Zhou, Xiang Li,…
Summary of Remodels: Quantile Regression Averaging Models, by Grzegorz Zakrzewski et al.
ReModels: Quantile Regression Averaging modelsby Grzegorz Zakrzewski, Kacper Skonieczka, Mikołaj Małkiński, Jacek MańdziukFirst submitted to…
Summary of Preparing For Black Swans: the Antifragility Imperative For Machine Learning, by Ming Jin
Preparing for Black Swans: The Antifragility Imperative for Machine Learningby Ming JinFirst submitted to arxiv…
Summary of How Big Is Big Data?, by Daniel T. Speckhard et al.
How big is Big Data?by Daniel T. Speckhard, Tim Bechtel, Luca M. Ghiringhelli, Martin Kuban,…
Summary of Flattened One-bit Stochastic Gradient Descent: Compressed Distributed Optimization with Controlled Variance, by Alexander Stollenwerk and Laurent Jacques
Flattened one-bit stochastic gradient descent: compressed distributed optimization with controlled varianceby Alexander Stollenwerk, Laurent JacquesFirst…
Summary of Dynamic Embeddings with Task-oriented Prompting, by Allmin Balloccu et al.
Dynamic Embeddings with Task-Oriented promptingby Allmin Balloccu, Jack ZhangFirst submitted to arxiv on: 17 May…