Where is the Information in a Deep Neural Network?

29 May 2019

Papers citing "Where is the Information in a Deep Neural Network?"

27 / 27 papers shown

Title
Quantifying Privacy Leakage in Split Inference via Fisher-Approximated Shannon Information Analysis Ruijun Deng Zhihui Lu Qiang Duan FedML 46 0 0 14 Apr 2025
FisherTune: Fisher-Guided Robust Tuning of Vision Foundation Models for Domain Generalized Segmentation Dong Zhao Jinlong Li Shuang Wang Mengyao Wu Qi Zang N. Sebe Zhun Zhong 170 0 0 23 Mar 2025
Taming AI Bots: Controllability of Neural States in Large Language Models Stefano Soatto Paulo Tabuada Pratik Chaudhari Tianwei Liu LLMAG LM&Ro 18 13 0 29 May 2023
AI Model Disgorgement: Methods and Choices Alessandro Achille Michael Kearns Carson Klingenberg Stefano Soatto MU 31 11 0 07 Apr 2023
Two Facets of SDE Under an Information-Theoretic Lens: Generalization of SGD via Training Trajectories and via Terminal States Ziqiao Wang Yongyi Mao 30 10 0 19 Nov 2022
Towards Semantic Communication Protocols: A Probabilistic Logic Perspective Sejin Seo Jihong Park Seung-Woo Ko Jinho Choi M. Bennis Seong-Lyun Kim 30 22 0 08 Jul 2022
On Leave-One-Out Conditional Mutual Information For Generalization Mohamad Rida Rammal Alessandro Achille Aditya Golatkar Suhas Diggavi Stefano Soatto VLM 28 5 0 01 Jul 2022
HEAM: High-Efficiency Approximate Multiplier Optimization for Deep Neural Networks Su Zheng Zhen Li Yao Lu Jingbo Gao Jide Zhang Lingli Wang 17 5 0 20 Jan 2022
Training Neural Networks with Fixed Sparse Masks Yi-Lin Sung Varun Nair Colin Raffel FedML 32 196 0 18 Nov 2021
Merging Models with Fisher-Weighted Averaging Michael Matena Colin Raffel FedML MoMe 50 352 0 18 Nov 2021
Fast Yet Effective Machine Unlearning Ayush K Tarun Vikram S Chundawat Murari Mandal Mohan S. Kankanhalli MU 31 171 0 17 Nov 2021
Does the Data Induce Capacity Control in Deep Learning? Rubing Yang Jialin Mao Pratik Chaudhari 33 15 0 27 Oct 2021
Deep Neural Networks and Tabular Data: A Survey V. Borisov Tobias Leemann Kathrin Seßler Johannes Haug Martin Pawelczyk Gjergji Kasneci LMTD 45 647 0 05 Oct 2021
Estimating informativeness of samples with Smooth Unique Information Hrayr Harutyunyan Alessandro Achille Giovanni Paolini Orchid Majumder Avinash Ravichandran Rahul Bhotika Stefano Soatto 27 24 0 17 Jan 2021
Mixed-Privacy Forgetting in Deep Networks Aditya Golatkar Alessandro Achille Avinash Ravichandran M. Polito Stefano Soatto CLL MU 130 159 0 24 Dec 2020
Generalized Variational Continual Learning Noel Loo S. Swaroop Richard Turner BDL CLL 33 58 0 24 Nov 2020
Artificial Neural Variability for Deep Learning: On Overfitting, Noise Memorization, and Catastrophic Forgetting Zeke Xie Fengxiang He Shaopeng Fu Issei Sato Dacheng Tao Masashi Sugiyama 21 60 0 12 Nov 2020
Whitening and second order optimization both make information in the dataset unusable during training, and can reduce or prevent generalization Neha S. Wadia Daniel Duckworth S. Schoenholz Ethan Dyer Jascha Narain Sohl-Dickstein 27 13 0 17 Aug 2020
Optimizing Information Loss Towards Robust Neural Networks Philip Sperl Konstantin Böttinger AAML 18 3 0 07 Aug 2020
Adversarial Training Reduces Information and Improves Transferability M. Terzi Alessandro Achille Marco Maggipinto Gian Antonio Susto AAML 24 23 0 22 Jul 2020
Backpropagated Gradient Representations for Anomaly Detection Gukyeong Kwon Mohit Prabhushankar Dogancan Temel Ghassan AlRegib 22 71 0 18 Jul 2020
A Diffusion Theory For Deep Learning Dynamics: Stochastic Gradient Descent Exponentially Favors Flat Minima Zeke Xie Issei Sato Masashi Sugiyama ODL 28 17 0 10 Feb 2020
Machine Unlearning: Linear Filtration for Logit-based Classifiers Thomas Baumhauer Pascal Schöttle Matthias Zeppelzauer MU 109 130 0 07 Feb 2020
Information in Infinite Ensembles of Infinitely-Wide Neural Networks Ravid Shwartz-Ziv Alexander A. Alemi 19 21 0 20 Nov 2019
Information-Theoretic Generalization Bounds for SGLD via Data-Dependent Estimates Jeffrey Negrea Mahdi Haghifam Gintare Karolina Dziugaite Ashish Khisti Daniel M. Roy FedML 113 147 0 06 Nov 2019
A General Framework for Uncertainty Estimation in Deep Learning Antonio Loquercio Mattia Segu Davide Scaramuzza UQCV BDL OOD 31 289 0 16 Jul 2019
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 308 2,890 0 15 Sep 2016