Does Learning Require Memorization? A Short Tale about a Long Tail

12 June 2019

Papers citing "Does Learning Require Memorization? A Short Tale about a Long Tail"

50 / 336 papers shown

Title
What Does it Mean for a Language Model to Preserve Privacy? Hannah Brown Katherine Lee Fatemehsadat Mireshghallah Reza Shokri Florian Tramèr PILM 50 232 0 11 Feb 2022
Deletion Inference, Reconstruction, and Compliance in Machine (Un)Learning Ji Gao Sanjam Garg Mohammad Mahmoody Prashant Nalini Vasudevan MIACV AAML 19 22 0 07 Feb 2022
Evaluating natural language processing models with generalization metrics that do not need access to any training or testing data Yaoqing Yang Ryan Theisen Liam Hodgkinson Joseph E. Gonzalez Kannan Ramchandran Charles H. Martin Michael W. Mahoney 94 17 0 06 Feb 2022
Identifiability of Label Noise Transition Matrix Yang Liu Hao Cheng Kun Zhang NoLa 38 44 0 04 Feb 2022
Datamodels: Predicting Predictions from Training Data Andrew Ilyas Sung Min Park Logan Engstrom Guillaume Leclerc A. Madry TDI 47 131 0 01 Feb 2022
Bounding Training Data Reconstruction in Private (Deep) Learning Chuan Guo Brian Karrer Kamalika Chaudhuri L. V. D. van der Maaten 115 53 0 28 Jan 2022
Fooling MOSS Detection with Pretrained Language Models Stella Biderman Edward Raff DeLMO 19 35 0 19 Jan 2022
Zero-Shot Machine Unlearning Vikram S Chundawat Ayush K Tarun Murari Mandal Mohan S. Kankanhalli MU 19 120 0 14 Jan 2022
Reconstructing Training Data with Informed Adversaries Borja Balle Giovanni Cherubin Jamie Hayes MIACV AAML 43 158 0 13 Jan 2022
AutoBalance: Optimized Loss Functions for Imbalanced Data Mingchen Li Xuechen Zhang Christos Thrampoulidis Jiasi Chen Samet Oymak 19 67 0 04 Jan 2022
Counterfactual Memorization in Neural Language Models Chiyuan Zhang Daphne Ippolito Katherine Lee Matthew Jagielski Florian Tramèr Nicholas Carlini 32 129 0 24 Dec 2021
Understanding Memorization from the Perspective of Optimization via Efficient Influence Estimation Futong Liu Tao R. Lin Martin Jaggi TDI 20 8 0 16 Dec 2021
Probably approximately correct quantum source coding Armando Angrisani Brian Coyle E. Kashefi 42 0 0 13 Dec 2021
Learning Theory Can (Sometimes) Explain Generalisation in Graph Neural Networks P. Esser L. C. Vankadara D. Ghoshdastidar 28 53 0 07 Dec 2021
Membership Inference Attacks From First Principles Nicholas Carlini Steve Chien Milad Nasr Shuang Song Andreas Terzis Florian Tramèr MIACV MIALM 29 642 0 07 Dec 2021
Scaling Up Influence Functions Andrea Schioppa Polina Zablotskaia David Vilar Artem Sokolov TDI 33 90 0 06 Dec 2021
On the Convergence of Shallow Neural Network Training with Randomly Masked Neurons Fangshuo Liao Anastasios Kyrillidis 46 16 0 05 Dec 2021
SHAPr: An Efficient and Versatile Membership Privacy Risk Metric for Machine Learning Vasisht Duddu S. Szyller Nadarajah Asokan 32 12 0 04 Dec 2021
Machine unlearning via GAN Kongyang Chen Yao Huang Yiwen Wang MU 24 7 0 22 Nov 2021
Enhanced Membership Inference Attacks against Machine Learning Models Jiayuan Ye Aadyaa Maddi S. K. Murakonda Vincent Bindschaedler Reza Shokri MIALM MIACV 27 233 0 18 Nov 2021
Selective Ensembles for Consistent Predictions Emily Black Klas Leino Matt Fredrikson 20 21 0 16 Nov 2021
On the Necessity of Auditable Algorithmic Definitions for Machine Unlearning Anvith Thudi Hengrui Jia Ilia Shumailov Nicolas Papernot MU 8 141 0 22 Oct 2021
Differentially Private Fine-tuning of Language Models Da Yu Saurabh Naik A. Backurs Sivakanth Gopi Huseyin A. Inan ... Y. Lee Andre Manoel Lukas Wutschitz Sergey Yekhanin Huishuai Zhang 134 350 0 13 Oct 2021
Not all noise is accounted equally: How differentially private learning benefits from large sampling rates Friedrich Dörmann Osvald Frisk L. Andersen Christian Fischer Pedersen FedML 59 25 0 12 Oct 2021
Distinguishing rule- and exemplar-based generalization in learning systems Ishita Dasgupta Erin Grant Thomas Griffiths 18 13 0 08 Oct 2021
Robin Hood and Matthew Effects: Differential Privacy Has Disparate Impact on Synthetic Data Georgi Ganev Bristena Oprisanu Emiliano De Cristofaro 37 57 0 23 Sep 2021
Partial sensitivity analysis in differential privacy Tamara T. Mueller Alexander Ziller Dmitrii Usynin Moritz Knolle F. Jungmann Daniel Rueckert Georgios Kaissis 45 1 0 22 Sep 2021
SoK: Machine Learning Governance Varun Chandrasekaran Hengrui Jia Anvith Thudi Adelin Travers Mohammad Yaghini Nicolas Papernot 38 16 0 20 Sep 2021
ComSum: Commit Messages Summarization and Meaning Preservation Leshem Choshen Idan Amit 17 4 0 23 Aug 2021
Federated Asymptotics: a model to compare federated learning algorithms Gary Cheng Karan N. Chadha John C. Duchi FedML 13 14 0 16 Aug 2021
Unified Regularity Measures for Sample-wise Learning and Generalization Chi Zhang Xiaoning Ma Yu Liu Le Wang Yuanqi Su Yuehu Liu 39 1 0 09 Aug 2021
Multi-Label Gold Asymmetric Loss Correction with Single-Label Regulators Cosmin Octavian Pene Amirmasoud Ghiassi Taraneh Younesian Robert Birke Lydia Y. Chen 34 3 0 04 Aug 2021
Large-Scale Differentially Private BERT Rohan Anil Badih Ghazi Vineet Gupta Ravi Kumar Pasin Manurangsi 36 132 0 03 Aug 2021
A Tale Of Two Long Tails Daniel D'souza Zach Nussbaum Chirag Agarwal Sara Hooker 29 22 0 27 Jul 2021
Memorization in Deep Neural Networks: Does the Loss Function matter? Deep Patel P. Sastry TDI 27 8 0 21 Jul 2021
A Theory of PAC Learnability of Partial Concept Classes N. Alon Steve Hanneke R. Holzman Shay Moran 28 50 0 18 Jul 2021
Deep Learning on a Data Diet: Finding Important Examples Early in Training Mansheej Paul Surya Ganguli Gintare Karolina Dziugaite 19 435 0 15 Jul 2021
Trustworthy AI: A Computational Perspective Haochen Liu Yiqi Wang Wenqi Fan Xiaorui Liu Yaxin Li Shaili Jain Yunhao Liu Anil K. Jain Jiliang Tang FaML 104 196 0 12 Jul 2021
RoFL: Robustness of Secure Federated Learning Hidde Lycklama Lukas Burkhalter Alexander Viand Nicolas Küchler Anwar Hithnawi FedML 37 55 0 07 Jul 2021
Covariance-Aware Private Mean Estimation Without Private Covariance Estimation Gavin Brown Marco Gaboardi Adam D. Smith Jonathan R. Ullman Lydia Zakynthinou FedML 28 48 0 24 Jun 2021
Membership Inference on Word Embedding and Beyond Saeed Mahloujifar Huseyin A. Inan Melissa Chase Esha Ghosh Marcello Hasegawa MIACV SILM 25 46 0 21 Jun 2021
Towards the Memorization Effect of Neural Networks in Adversarial Training Han Xu Xiaorui Liu Wentao Wang Wenbiao Ding Zhongqin Wu Zitao Liu Anil K. Jain Jiliang Tang TDI AAML 29 6 0 09 Jun 2021
Antipodes of Label Differential Privacy: PATE and ALIBI Mani Malek Ilya Mironov Karthik Prasad I. Shilov Florian Tramèr 16 62 0 07 Jun 2021
On Memorization in Probabilistic Deep Generative Models G. V. D. Burg Christopher K. I. Williams TDI 25 59 0 06 Jun 2021
Self-Damaging Contrastive Learning Ziyu Jiang Tianlong Chen Bobak J. Mortazavi Zhangyang Wang CLL 22 69 0 06 Jun 2021
Exploring Memorization in Adversarial Training Yinpeng Dong Ke Xu Xiao Yang Tianyu Pang Zhijie Deng Hang Su Jun Zhu TDI 33 69 0 03 Jun 2021
Accuracy-Privacy Trade-off in Deep Ensemble: A Membership Inference Perspective Shahbaz Rezaei Zubair Shafiq Xin Liu FedML MIACV 40 13 0 12 May 2021
Dataset Inference: Ownership Resolution in Machine Learning Pratyush Maini Mohammad Yaghini Nicolas Papernot FedML 72 105 0 21 Apr 2021
The Curious Case of Hallucinations in Neural Machine Translation Vikas Raunak Arul Menezes Marcin Junczys-Dowmunt 44 190 0 14 Apr 2021
Leverage Score Sampling for Complete Mode Coverage in Generative Adversarial Networks J. Schreurs Hannes De Meulemeester Michaël Fanuel B. De Moor Johan A. K. Suykens GAN 31 0 0 06 Apr 2021