Understanding Pre-training and Fine-tuning from Loss Landscape Perspectives

23 May 2025

Papers citing "Understanding Pre-training and Fine-tuning from Loss Landscape Perspectives"

10 / 60 papers shown

Title
Loss Surfaces, Mode Connectivity, and Fast Ensembling of DNNs T. Garipov Pavel Izmailov Dmitrii Podoprikhin Dmitry Vetrov A. Wilson UQCV 47 746 0 27 Feb 2018
Visualizing the Loss Landscape of Neural Nets Hao Li Zheng Xu Gavin Taylor Christoph Studer Tom Goldstein 216 1,873 0 28 Dec 2017
Towards Deep Learning Models Resistant to Adversarial Attacks Aleksander Madry Aleksandar Makelov Ludwig Schmidt Dimitris Tsipras Adrian Vladu SILM OOD 181 11,962 0 19 Jun 2017
Nearly-tight VC-dimension and pseudodimension bounds for piecewise linear neural networks Peter L. Bartlett Nick Harvey Christopher Liaw Abbas Mehrabian 103 427 0 08 Mar 2017
Exploring loss function topology with cyclical learning rates L. Smith Nicholay Topin 26 23 0 14 Feb 2017
Neural Machine Translation of Rare Words with Subword Units Rico Sennrich Barry Haddow Alexandra Birch 131 7,683 0 31 Aug 2015
Norm-Based Capacity Control in Neural Networks Behnam Neyshabur Ryota Tomioka Nathan Srebro 199 583 0 27 Feb 2015
Explaining and Harnessing Adversarial Examples Ian Goodfellow Jonathon Shlens Christian Szegedy AAML GAN 122 18,922 0 20 Dec 2014
Qualitatively characterizing neural network optimization problems Ian Goodfellow Oriol Vinyals Andrew M. Saxe ODL 73 519 0 19 Dec 2014
Intriguing properties of neural networks Christian Szegedy Wojciech Zaremba Ilya Sutskever Joan Bruna D. Erhan Ian Goodfellow Rob Fergus AAML 101 14,831 1 21 Dec 2013