Metadata Archaeology: Unearthing Data Subsets by Leveraging Training Dynamics

20 September 2022

Shoaib Ahmed Siddiqui

Papers citing "Metadata Archaeology: Unearthing Data Subsets by Leveraging Training Dynamics"

28 / 28 papers shown

Title
Beyond neural scaling laws: beating power law scaling via data pruning Ben Sorscher Robert Geirhos Shashank Shekhar Surya Ganguli Ari S. Morcos 79 439 0 29 Jun 2022
Emergent Abilities of Large Language Models Jason W. Wei Yi Tay Rishi Bommasani Colin Raffel Barret Zoph ... Tatsunori Hashimoto Oriol Vinyals Percy Liang J. Dean W. Fedus ELM ReLM LRM 261 2,462 0 15 Jun 2022
Selective Classification Via Neural Network Training Dynamics Stephan Rabanser Anvith Thudi Kimia Hamidieh Adam Dziedzic Nicolas Papernot 66 22 0 26 May 2022
Evaluating Distributional Distortion in Neural Language Modeling Benjamin LeBrun Alessandro Sordoni Timothy J. O'Donnell 43 22 0 24 Mar 2022
Quantifying Memorization Across Neural Language Models Nicholas Carlini Daphne Ippolito Matthew Jagielski Katherine Lee Florian Tramèr Chiyuan Zhang PILM 100 614 0 15 Feb 2022
Just Train Twice: Improving Group Robustness without Training Group Information Emmy Liu Behzad Haghgoo Annie S. Chen Aditi Raghunathan Pang Wei Koh Shiori Sagawa Percy Liang Chelsea Finn OOD 84 557 0 19 Jul 2021
Deep Learning on a Data Diet: Finding Important Examples Early in Training Mansheej Paul Surya Ganguli Gintare Karolina Dziugaite 105 456 0 15 Jul 2021
Deep Learning Through the Lens of Example Difficulty R. Baldock Hartmut Maennel Behnam Neyshabur 72 160 0 17 Jun 2021
Algorithmic Bias and Data Bias: Understanding the Relation between Distributionally Robust Optimization and Data Curation Agnieszka Słowik Léon Bottou FaML 60 19 0 17 Jun 2021
Beyond Fair Pay: Ethical Implications of NLP Crowdsourcing Boaz Shmueli Jan Fell Soumya Ray Lun-Wei Ku 149 87 0 20 Apr 2021
Learning Light-Weight Translation Models from Deep Transformer Bei Li Ziyang Wang Hui Liu Quan Du Tong Xiao Chunliang Zhang Jingbo Zhu VLM 139 40 0 27 Dec 2020
Environment Inference for Invariant Learning Elliot Creager J. Jacobsen R. Zemel OOD 57 382 0 14 Oct 2020
What Neural Networks Memorize and Why: Discovering the Long Tail via Influence Estimation Vitaly Feldman Chiyuan Zhang TDI 132 459 0 09 Aug 2020
DivideMix: Learning with Noisy Labels as Semi-supervised Learning Junnan Li R. Socher Guosheng Lin NoLa 94 1,026 0 18 Feb 2020
How Much Knowledge Can You Pack Into the Parameters of a Language Model? Adam Roberts Colin Raffel Noam M. Shazeer KELM 104 888 0 10 Feb 2020
Characterizing Structural Regularities of Labeled Data in Overparameterized Models Ziheng Jiang Chiyuan Zhang Kunal Talwar Michael C. Mozer TDI 56 102 0 08 Feb 2020
Scaling Laws for Neural Language Models Jared Kaplan Sam McCandlish T. Henighan Tom B. Brown B. Chess R. Child Scott Gray Alec Radford Jeff Wu Dario Amodei 522 4,773 0 23 Jan 2020
Scaling Out-of-Distribution Detection for Real-World Settings Dan Hendrycks Steven Basart Mantas Mazeika Andy Zou Joe Kwon Mohammadreza Mostajabi Jacob Steinhardt D. Song OODD 140 465 0 25 Nov 2019
Distributionally Robust Neural Networks for Group Shifts: On the Importance of Regularization for Worst-Case Generalization Shiori Sagawa Pang Wei Koh Tatsunori B. Hashimoto Percy Liang OOD 85 1,234 0 20 Nov 2019
Accelerating Deep Learning by Focusing on the Biggest Losers Angela H. Jiang Daniel L.-K. Wong Giulio Zhou D. Andersen J. Dean ... Gauri Joshi M. Kaminsky M. Kozuch Zachary Chase Lipton Padmanabhan Pillai 54 121 0 02 Oct 2019
Hidden Stratification Causes Clinically Meaningful Failures in Machine Learning for Medical Imaging Luke Oakden-Rayner Jared A. Dunnmon G. Carneiro Christopher Ré OOD 61 379 0 27 Sep 2019
Combating Label Noise in Deep Learning Using Abstention S. Thulasidasan Tanmoy Bhattacharya J. Bilmes Gopinath Chennupati J. Mohd-Yusof NoLa 52 179 0 27 May 2019
Unsupervised Label Noise Modeling and Loss Correction Eric Arazo Sanchez Diego Ortego Paul Albert Noel E. O'Connor Kevin McGuinness NoLa 74 610 0 25 Apr 2019
Probabilistic End-to-end Noise Correction for Learning with Noisy Labels Kun Yi Jianxin Wu NoLa 63 414 0 19 Mar 2019
Deep Learning Predicts Hip Fracture using Confounding Patient and Healthcare Variables Giovanni Sutanto J. Zech Luke Oakden-Rayner Yevgen Chebotar Manway Liu William Gale M. McConnell Ankur Handa Thomas M. Snyder Dieter Fox AI4CE OOD 74 244 0 08 Nov 2018
mixup: Beyond Empirical Risk Minimization Hongyi Zhang Moustapha Cissé Yann N. Dauphin David Lopez-Paz NoLa 269 9,743 0 25 Oct 2017
A Closer Look at Memorization in Deep Networks Devansh Arpit Stanislaw Jastrzebski Nicolas Ballas David M. Krueger Emmanuel Bengio ... Tegan Maharaj Asja Fischer Aaron Courville Yoshua Bengio Simon Lacoste-Julien TDI 118 1,814 0 16 Jun 2017
Understanding Black-box Predictions via Influence Functions Pang Wei Koh Percy Liang TDI 169 2,878 0 14 Mar 2017