Training Set Debugging Using Trusted Items

24 January 2018

Papers citing "Training Set Debugging Using Trusted Items"

12 / 12 papers shown

Title
Learning from Uncertain Data: From Possible Worlds to Possible Models Jiongli Zhu Su Feng Boris Glavic Babak Salimi 37 0 0 28 May 2024
Certifying Data-Bias Robustness in Linear Regression Anna P. Meyer Aws Albarghouthi Loris Dántoni 29 3 0 07 Jun 2022
Poisoning Attacks and Defenses on Artificial Intelligence: A Survey M. A. Ramírez Song-Kyoo Kim H. A. Hamadi Ernesto Damiani Young-Ji Byon Tae-Yeon Kim C. Cho C. Yeun AAML 19 37 0 21 Feb 2022
Iterative Teaching by Label Synthesis Weiyang Liu Zhen Liu Hanchen Wang Liam Paull Bernhard Schölkopf Adrian Weller 48 16 0 27 Oct 2021
CHEF: A Cheap and Fast Pipeline for Iteratively Cleaning Label Uncertainties (Technical Report) Yinjun Wu James Weimer S. Davidson 20 4 0 19 Jul 2021
De-Pois: An Attack-Agnostic Defense against Data Poisoning Attacks Jian Chen Xuxin Zhang Rui Zhang Chen Wang Ling Liu AAML 19 86 0 08 May 2021
Defense Against Reward Poisoning Attacks in Reinforcement Learning Kiarash Banihashem Adish Singla Goran Radanović AAML 27 26 0 10 Feb 2021
Efficient Estimation of Influence of a Training Instance Sosuke Kobayashi Sho Yokoi Jun Suzuki Kentaro Inui TDI 32 15 0 08 Dec 2020
Provable Training Set Debugging for Linear Regression Xiaomin Zhang Xiaojin Zhu Po-Ling Loh 24 0 0 16 Jun 2020
Complaint-driven Training Data Debugging for Query 2.0 Weiyuan Wu Lampros Flokas Eugene Wu Jiannan Wang 32 43 0 12 Apr 2020
FR-Train: A Mutual Information-Based Approach to Fair and Robust Training Yuji Roh Kangwook Lee Steven Euijong Whang Changho Suh 16 78 0 24 Feb 2020
Data Cleansing for Models Trained with SGD Satoshi Hara Atsushi Nitanda Takanori Maehara TDI 31 68 0 20 Jun 2019