Theoretical and Practical Perspectives on what Influence Functions Do

Theoretical and Practical Perspectives on what Influence Functions Do

26 May 2023

Andrea Schioppa

Katja Filippova

Polina Zablotskaia

Papers citing "Theoretical and Practical Perspectives on what Influence Functions Do"

11 / 11 papers shown

Title
Addressing Delayed Feedback in Conversion Rate Prediction via Influence Functions Chenlu Ding Jiancan Wu Yancheng Yuan Junfeng Fang Cunchun Li Xiang Wang Xiangnan He 66 1 0 01 Feb 2025
LayerMatch: Do Pseudo-labels Benefit All Layers? Chaoqi Liang Guanglei Yang Lifeng Qiao Zitong Huang Hongliang Yan Yunchao Wei W. Zuo 36 0 0 20 Jun 2024
Causal Estimation of Memorisation Profiles Pietro Lesci Clara Meister Thomas Hofmann Andreas Vlachos Tiago Pimentel 43 5 0 06 Jun 2024
Training Data Attribution via Approximate Unrolled Differentiation Juhan Bae Wu Lin Jonathan Lorraine Roger C. Grosse TDI MU 49 12 0 20 May 2024
Outlier Gradient Analysis: Efficiently Identifying Detrimental Training Samples for Deep Learning Models Anshuman Chhabra Bo Li Jian Chen Prasant Mohapatra Hongfu Liu TDI 18 0 0 06 May 2024
Unveiling Privacy, Memorization, and Input Curvature Links Deepak Ravikumar Efstathia Soufleri Abolfazl Hashemi Kaushik Roy 49 5 0 28 Feb 2024
Unlearning Traces the Influential Training Data of Language Models Masaru Isonuma Ivan Titov MU 24 6 0 26 Jan 2024
SoK: Memorisation in machine learning Dmitrii Usynin Moritz Knolle Georgios Kaissis 9 1 0 06 Nov 2023
Simfluence: Modeling the Influence of Individual Training Examples by Simulating Training Runs Kelvin Guu Albert Webson Ellie Pavlick Lucas Dixon Ian Tenney Tolga Bolukbasi TDI 66 33 0 14 Mar 2023
Make Every Example Count: On the Stability and Utility of Self-Influence for Learning from Noisy NLP Datasets Irina Bejan Artem Sokolov Katja Filippova TDI 11 8 0 27 Feb 2023
Training Data Influence Analysis and Estimation: A Survey Zayd Hammoudeh Daniel Lowd TDI 29 82 0 09 Dec 2022