A Theory of PAC Learnability under Transformation Invariances

15 February 2022

Papers citing "A Theory of PAC Learnability under Transformation Invariances"

9 / 9 papers shown

Title
Approximate Nullspace Augmented Finetuning for Robust Vision Transformers Haoyang Liu Aditya Singh Yijiang Li Haohan Wang AAML ViT 36 1 0 15 Mar 2024
Sample, estimate, aggregate: A recipe for causal discovery foundation models Menghua Wu Yujia Bao Regina Barzilay Tommi Jaakkola CML 49 7 0 02 Feb 2024
Approximation-Generalization Trade-offs under (Approximate) Group Equivariance Mircea Petrache Shubhendu Trivedi 35 22 0 27 May 2023
Learning with Explanation Constraints Rattana Pukdee Dylan Sam J. Zico Kolter Maria-Florina Balcan Pradeep Ravikumar FAtt 32 6 0 25 Mar 2023
VC dimensions of group convolutional neural networks P. Petersen A. Sepliarskaia VLM 19 7 0 19 Dec 2022
Automatic Data Augmentation via Invariance-Constrained Learning Ignacio Hounie Luiz F. O. Chamon Alejandro Ribeiro 23 10 0 29 Sep 2022
Sample Efficiency of Data Augmentation Consistency Regularization Shuo Yang Yijun Dong Rachel A. Ward Inderjit S. Dhillon Sujay Sanghavi Qi Lei AAML 23 17 0 24 Feb 2022
Realizable Learning is All You Need Max Hopkins D. Kane Shachar Lovett G. Mahajan 109 22 0 08 Nov 2021
Learning with invariances in random features and kernel models Song Mei Theodor Misiakiewicz Andrea Montanari OOD 46 89 0 25 Feb 2021