Summary of Generalization Error Of Spectral Algorithms, by Maksim Velikanov et al.
Generalization error of spectral algorithmsby Maksim Velikanov, Maxim Panov, Dmitry YarotskyFirst submitted to arxiv on:…
Summary of Low-cost Privacy-preserving Decentralized Learning, by Sayan Biswas et al.
Low-Cost Privacy-Preserving Decentralized Learningby Sayan Biswas, Davide Frey, Romaric Gaudel, Anne-Marie Kermarrec, Dimitri Lerévérend, Rafael…
Summary of Cgi-dm: Digital Copyright Authentication For Diffusion Models Via Contrasting Gradient Inversion, by Xiaoyu Wu et al.
CGI-DM: Digital Copyright Authentication for Diffusion Models via Contrasting Gradient Inversionby Xiaoyu Wu, Yang Hua,…
Summary of A Resource-constrained Stochastic Scheduling Algorithm For Homeless Street Outreach and Gleaning Edible Food, by Conor M. Artman et al.
A resource-constrained stochastic scheduling algorithm for homeless street outreach and gleaning edible foodby Conor M.…
Summary of Adedgedrop: Adversarial Edge Dropping For Robust Graph Neural Networks, by Zhaoliang Chen et al.
ADEdgeDrop: Adversarial Edge Dropping for Robust Graph Neural Networksby Zhaoliang Chen, Zhihao Wu, Ylli Sadikaj,…
Summary of Mechanics Of Next Token Prediction with Self-attention, by Yingcong Li et al.
Mechanics of Next Token Prediction with Self-Attentionby Yingcong Li, Yixiao Huang, M. Emrullah Ildiz, Ankit…
Summary of Learning-driven Physically-aware Large-scale Circuit Gate Sizing, by Yuyang Ye et al.
Learning-driven Physically-aware Large-scale Circuit Gate Sizingby Yuyang Ye, Peng Xu, Lizheng Ren, Tinghuan Chen, Hao…
Summary of Benign Overfitting in Leaky Relu Networks with Moderate Input Dimension, by Kedar Karhadkar et al.
Benign overfitting in leaky ReLU networks with moderate input dimensionby Kedar Karhadkar, Erin George, Michael…
Summary of Leveraging Continuous Time to Understand Momentum When Training Diagonal Linear Networks, by Hristo Papazov et al.
Leveraging Continuous Time to Understand Momentum When Training Diagonal Linear Networksby Hristo Papazov, Scott Pesme,…
Summary of Recovery Guarantees Of Unsupervised Neural Networks For Inverse Problems Trained with Gradient Descent, by Nathan Buskulic et al.
Recovery Guarantees of Unsupervised Neural Networks for Inverse Problems trained with Gradient Descentby Nathan Buskulic,…