Federated and Privacy-Preserving Learning of Accounting Data in Financial Statement Audits

26 August 2022

Papers citing "Federated and Privacy-Preserving Learning of Accounting Data in Financial Statement Audits"

22 / 22 papers shown

Title
Federated Learning: Balancing the Thin Line Between Data Intelligence and Privacy Sherin M. Mathews Samuel A. Assefa FedML 31 5 0 22 Apr 2022
Opacus: User-Friendly Differential Privacy Library in PyTorch Ashkan Yousefpour I. Shilov Alexandre Sablayrolles Davide Testuggine Karthik Prasad ... Sayan Gosh Akash Bharadwaj Jessica Zhao Graham Cormode Ilya Mironov VLM 286 368 0 25 Sep 2021
Multi-view Contrastive Self-Supervised Learning of Accounting Data Representations for Downstream Audit Tasks Marco Schreyer Timur Sattarov Damian Borth MLAU 68 15 0 23 Sep 2021
See through Gradients: Image Batch Recovery via GradInversion Hongxu Yin Arun Mallya Arash Vahdat J. Álvarez Jan Kautz Pavlo Molchanov FedML 89 474 0 15 Apr 2021
Extracting Training Data from Large Language Models Nicholas Carlini Florian Tramèr Eric Wallace Matthew Jagielski Ariel Herbert-Voss ... Tom B. Brown Basel Alomair Ulfar Erlingsson Alina Oprea Colin Raffel MLAU SILM 509 1,953 0 14 Dec 2020
PCAL: A Privacy-preserving Intelligent Credit Risk Modeling Framework Based on Adversarial Learning Yu Zheng Zhenyu Wu Ye Yuan Tianlong Chen Zhangyang Wang 81 12 0 06 Oct 2020
Flower: A Friendly Federated Learning Research Framework Daniel J. Beutel Taner Topal Akhil Mathur Xinchi Qiu Javier Fernandez-Marques ... Lorenzo Sani Kwing Hei Li Titouan Parcollet Pedro Porto Buarque de Gusmão Nicholas D. Lane FedML 140 815 0 28 Jul 2020
Advances and Open Problems in Federated Learning Peter Kairouz H. B. McMahan Brendan Avent A. Bellet M. Bennis ... Zheng Xu Qiang Yang Felix X. Yu Han Yu Sen Zhao FedML AI4CE 270 6,285 0 10 Dec 2019
Adversarial Learning of Deepfakes in Accounting Marco Schreyer Timur Sattarov Bernd Reimer Damian Borth AAML 54 26 0 09 Oct 2019
Detection of Accounting Anomalies in the Latent Space using Adversarial Autoencoder Neural Networks Marco Schreyer Timur Sattarov Christian Schulze Bernd Reimer Damian Borth AAML 35 35 0 02 Aug 2019
Bayesian Nonparametric Federated Learning of Neural Networks Mikhail Yurochkin Mayank Agarwal S. Ghosh Kristjan Greenewald T. Hoang Y. Khazaeni FedML 129 730 0 28 May 2019
Federated Learning for Mobile Keyboard Prediction Andrew Straiton Hard Kanishka Rao Zhifeng Lin Swaroop Indra Ramaswamy Youjie Li S. Augenstein Alex Schwing M. Annavaram A. Avestimehr FedML 136 1,546 0 08 Nov 2018
Distributed learning of deep neural network over multiple agents O. Gupta Ramesh Raskar FedML OOD 69 605 0 14 Oct 2018
Differentially Private Empirical Risk Minimization with Input Perturbation Kazuto Fukuchi Quang Khai Tran Jun Sakuma 57 36 0 20 Oct 2017
Detection of Anomalies in Large Scale Accounting Data using Deep Autoencoder Networks Marco Schreyer Timur Sattarov Damian Borth Andreas Dengel Bernd Reimer 61 106 0 15 Sep 2017
Federated Multi-Task Learning Virginia Smith Chao-Kai Chiang Maziar Sanjabi Ameet Talwalkar FedML 159 1,814 0 30 May 2017
Efficient Private ERM for Smooth Objectives Jiaqi Zhang Kai Zheng Wenlong Mou Liwei Wang 47 145 0 29 Mar 2017
Semi-supervised Knowledge Transfer for Deep Learning from Private Training Data Nicolas Papernot Martín Abadi Ulfar Erlingsson Ian Goodfellow Kunal Talwar 94 1,020 0 18 Oct 2016
Federated Optimization: Distributed Machine Learning for On-Device Intelligence Jakub Konecný H. B. McMahan Daniel Ramage Peter Richtárik FedML 145 1,906 0 08 Oct 2016
Deep Learning with Differential Privacy Martín Abadi Andy Chu Ian Goodfellow H. B. McMahan Ilya Mironov Kunal Talwar Li Zhang FedML SyDa 216 6,162 0 01 Jul 2016
Communication-Efficient Learning of Deep Networks from Decentralized Data H. B. McMahan Eider Moore Daniel Ramage S. Hampson Blaise Agüera y Arcas FedML 408 17,593 0 17 Feb 2016
Representation Learning: A Review and New Perspectives Yoshua Bengio Aaron Courville Pascal Vincent OOD SSL 278 12,458 0 24 Jun 2012