Learning Optimal Representations with the Decodable Information
Bottleneck

Learning Optimal Representations with the Decodable Information Bottleneck

27 September 2020

Douwe Kiela

Ramakrishna Vedantam

Papers citing "Learning Optimal Representations with the Decodable Information Bottleneck"

14 / 14 papers shown

Title
Generalization Guarantees for Multi-View Representation Learning and Application to Regularization via Gaussian Product Mixture Prior Milad Sefidgaran Abdellatif Zaidi Piotr Krasnowski 44 0 0 25 Apr 2025
Generalization Guarantees for Representation Learning via Data-Dependent Gaussian Mixture Priors Milad Sefidgaran A. Zaidi Piotr Krasnowski 88 1 0 21 Feb 2025
MLEM: Generative and Contrastive Learning as Distinct Modalities for Event Sequences Viktor Moskvoretskii Dmitry Osin Egor Shvetsov Igor Udovichenko Maxim Zhelnin Andrey Dukhovny Anna Zhimerikina E. Burnaev AI4TS 25 2 0 29 Jan 2024
Elastic Information Bottleneck Yuyan Ni Yanyan Lan Ao Liu Zhiming Ma 22 2 0 07 Nov 2023
Data-Efficient Protein 3D Geometric Pretraining via Refinement of Diffused Protein Structure Decoy Yufei Huang Lirong Wu Haitao Lin Jiangbin Zheng Ge Wang Stan Z. Li DiffM 24 14 0 05 Feb 2023
SynBench: Task-Agnostic Benchmarking of Pretrained Representations using Synthetic Data Ching-Yun Ko Pin-Yu Chen Jeet Mohapatra Payel Das Lucani E. Daniel 19 3 0 06 Oct 2022
Gacs-Korner Common Information Variational Autoencoder Michael Kleinman Alessandro Achille Stefano Soatto J. Kao CML DRL 24 12 0 24 May 2022
Empirical Evaluation and Theoretical Analysis for Representation Learning: A Survey Kento Nozawa Issei Sato AI4TS 19 4 0 18 Apr 2022
Optimal Representations for Covariate Shift Yangjun Ruan Yann Dubois Chris J. Maddison OOD 22 68 0 31 Dec 2021
Graph Structure Learning with Variational Information Bottleneck Qingyun Sun Jianxin Li Hao Peng Jia Wu Xingcheng Fu Cheng Ji Philip S. Yu 39 153 0 16 Dec 2021
Reducing Information Bottleneck for Weakly Supervised Semantic Segmentation Jungbeom Lee Jooyoung Choi J. Mok Sungroh Yoon SSeg 218 134 0 13 Oct 2021
Usable Information and Evolution of Optimal Representations During Training Michael Kleinman Alessandro Achille Daksh Idnani J. Kao 21 13 0 06 Oct 2020
On Large-Batch Training for Deep Learning: Generalization Gap and Sharp Minima N. Keskar Dheevatsa Mudigere J. Nocedal M. Smelyanskiy P. T. P. Tang ODL 281 2,888 0 15 Sep 2016
Norm-Based Capacity Control in Neural Networks Behnam Neyshabur Ryota Tomioka Nathan Srebro 119 577 0 27 Feb 2015