Functional Regularization for Representation Learning: A Unified Theoretical Perspective

6 August 2020

Papers citing "Functional Regularization for Representation Learning: A Unified Theoretical Perspective"

8 / 8 papers shown

Title
Learning with Explanation Constraints Rattana Pukdee Dylan Sam J. Zico Kolter Maria-Florina Balcan Pradeep Ravikumar FAtt 34 6 0 25 Mar 2023
Provable Pathways: Learning Multiple Tasks over Multiple Paths Yingcong Li Samet Oymak MoE 29 4 0 08 Mar 2023
Adaptation of Autoencoder for Sparsity Reduction From Clinical Notes Representation Learning Thanh-Dung Le R. Noumeir J. Rambaud Guillaume Sans P. Jouvet 32 7 0 26 Sep 2022
Empirical Evaluation and Theoretical Analysis for Representation Learning: A Survey Kento Nozawa Issei Sato AI4TS 26 4 0 18 Apr 2022
Sample Efficiency of Data Augmentation Consistency Regularization Shuo Yang Yijun Dong Rachel A. Ward Inderjit S. Dhillon Sujay Sanghavi Qi Lei AAML 31 17 0 24 Feb 2022
Pre-training Molecular Graph Representation with 3D Geometry Shengchao Liu Hanchen Wang Weiyang Liu Joan Lasenby Hongyu Guo Jian Tang 126 304 0 07 Oct 2021
On the Surrogate Gap between Contrastive and Supervised Losses Han Bao Yoshihiro Nagano Kento Nozawa SSL UQCV 41 19 0 06 Oct 2021
Understanding Negative Samples in Instance Discriminative Self-supervised Representation Learning Kento Nozawa Issei Sato SSL 22 43 0 13 Feb 2021