Papers citing "Advances and Open Problems in Federated Learning"

43 / 193 papers shown

Title
Neural Architecture Optimization Renqian Luo Fei Tian Tao Qin Enhong Chen Tie-Yan Liu 3DV 62 651 0 22 Aug 2018
An Economic Analysis of Privacy Protection and Statistical Accuracy as Social Choices John M. Abowd Ian M. Schmutte 22 124 0 20 Aug 2018
Subsampled Rényi Differential Privacy and Analytical Moments Accountant Yu Wang Borja Balle S. Kasiviswanathan 59 397 0 31 Jul 2018
BOHB: Robust and Efficient Hyperparameter Optimization at Scale Stefan Falkner Aaron Klein Frank Hutter BDL 157 1,077 0 04 Jul 2018
DARTS: Differentiable Architecture Search Hanxiao Liu Karen Simonyan Yiming Yang 167 4,326 0 24 Jun 2018
Local SGD Converges Fast and Communicates Little Sebastian U. Stich FedML 152 1,056 0 24 May 2018
Algorithms and Theory for Multiple-Source Adaptation Judy Hoffman M. Mohri Ningshan Zhang OOD 49 171 0 20 May 2018
Federated Learning for Ultra-Reliable Low-Latency V2V Communications S. Samarakoon M. Bennis Walid Saad Merouane Debbah 44 228 0 11 May 2018
Exploiting Unintended Feature Leakage in Collaborative Learning Luca Melis Congzheng Song Emiliano De Cristofaro Vitaly Shmatikov FedML 131 1,461 0 10 May 2018
Efficient Multi-objective Neural Architecture Search via Lamarckian Evolution T. Elsken J. H. Metzen Frank Hutter 179 499 0 24 Apr 2018
Sever: A Robust Meta-Algorithm for Stochastic Optimization Ilias Diakonikolas Gautam Kamath D. Kane Jerry Li Jacob Steinhardt Alistair Stewart 51 288 0 07 Mar 2018
Slow and Stale Gradients Can Win the Race: Error-Runtime Trade-offs in Distributed SGD Sanghamitra Dutta Gauri Joshi Soumyadip Ghosh Parijat Dube P. Nagpurkar 53 194 0 03 Mar 2018
Learning Adversarially Fair and Transferable Representations David Madras Elliot Creager T. Pitassi R. Zemel FaML 323 678 0 17 Feb 2018
Efficient Neural Architecture Search via Parameter Sharing Hieu H. Pham M. Guan Barret Zoph Quoc V. Le J. Dean 78 2,761 0 09 Feb 2018
Targeted Backdoor Attacks on Deep Learning Systems Using Data Poisoning Xinyun Chen Chang-rui Liu Yue Liu Kimberly Lu D. Song AAML SILM 80 1,822 0 15 Dec 2017
Deep Gradient Compression: Reducing the Communication Bandwidth for Distributed Training Chengyue Wu Song Han Huizi Mao Yu Wang W. Dally 104 1,399 0 05 Dec 2017
To prune, or not to prune: exploring the efficacy of pruning for model compression Michael Zhu Suyog Gupta 132 1,262 0 05 Oct 2017
Prochlo: Strong Privacy for Analytics in the Crowd Andrea Bittau Ulfar Erlingsson Petros Maniatis Ilya Mironov A. Raghunathan David Lie Mitch Rudominer Ushasree Kode J. Tinnés B. Seefeld 106 279 0 02 Oct 2017
Neural Optimizer Search with Reinforcement Learning Irwan Bello Barret Zoph Vijay Vasudevan Quoc V. Le ODL 45 385 0 21 Sep 2017
BadNets: Identifying Vulnerabilities in the Machine Learning Model Supply Chain Tianyu Gu Brendan Dolan-Gavitt S. Garg SILM 72 1,758 0 22 Aug 2017
Evasion Attacks against Machine Learning at Test Time Battista Biggio Igino Corona Davide Maiorca B. Nelson Nedim Srndic Pavel Laskov Giorgio Giacinto Fabio Roli AAML 101 2,142 0 21 Aug 2017
A Survey on Multi-Task Learning Yu Zhang Qiang Yang AIMat 349 2,196 0 25 Jul 2017
BLENDER: Enabling Local Search with a Hybrid Differential Privacy Model Brendan Avent Aleksandra Korolova David Zeber Torgeir Hovden B. Livshits FedML 53 99 0 02 May 2017
Tight Lower Bounds for Differentially Private Selection Thomas Steinke Jonathan R. Ullman 57 73 0 10 Apr 2017
Understanding Black-box Predictions via Influence Functions Pang Wei Koh Percy Liang TDI 136 2,854 0 14 Mar 2017
Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks Chelsea Finn Pieter Abbeel Sergey Levine OOD 759 11,793 0 09 Mar 2017
Optimal Schemes for Discrete Distribution Estimation under Locally Differential Privacy Min Ye A. Barg 54 178 0 02 Feb 2017
Adversarial Machine Learning at Scale Alexey Kurakin Ian Goodfellow Samy Bengio AAML 450 3,124 0 04 Nov 2016
Membership Inference Attacks against Machine Learning Models Reza Shokri M. Stronati Congzheng Song Vitaly Shmatikov SLR MIALM MIACV 203 4,075 0 18 Oct 2016
Federated Learning: Strategies for Improving Communication Efficiency Jakub Konecný H. B. McMahan Felix X. Yu Peter Richtárik A. Suresh Dave Bacon FedML 269 4,620 0 18 Oct 2016
Decentralized Collaborative Learning of Personalized Models over Networks Paul Vanhaesebrouck A. Bellet Marc Tommasi FedML 40 230 0 17 Oct 2016
Decoupled Neural Interfaces using Synthetic Gradients Max Jaderberg Wojciech M. Czarnecki Simon Osindero Oriol Vinyals Alex Graves David Silver Koray Kavukcuoglu 65 356 0 18 Aug 2016
Towards Evaluating the Robustness of Neural Networks Nicholas Carlini D. Wagner OOD AAML 170 8,513 0 16 Aug 2016
Discrete Distribution Estimation under Local Privacy Peter Kairouz Kallista A. Bonawitz Daniel Ramage 27 328 0 24 Feb 2016
Fixed Point Quantization of Deep Convolutional Networks D. Lin S. Talathi V. Annapureddy MQ 71 814 0 19 Nov 2015
Deep Compression: Compressing Deep Neural Networks with Pruning, Trained Quantization and Huffman Coding Song Han Huizi Mao W. Dally 3DGS 203 8,793 0 01 Oct 2015
Communication Lower Bounds for Statistical Estimation Problems via a Distributed Data Processing Inequality M. Braverman A. Garg Tengyu Ma Huy Le Nguyen David P. Woodruff FedML 48 175 0 24 Jun 2015
Local, Private, Efficient Protocols for Succinct Histograms Raef Bassily Adam D. Smith FedML 46 456 0 18 Apr 2015
RAPPOR: Randomized Aggregatable Privacy-Preserving Ordinal Response Ulfar Erlingsson Vasyl Pihur Aleksandra Korolova 59 1,977 0 25 Jul 2014
Differentially Private Distributed Optimization Zhenqi Huang Sayan Mitra Nitin H. Vaidya FedML 51 261 0 12 Jan 2014
Intriguing properties of neural networks Christian Szegedy Wojciech Zaremba Ilya Sutskever Joan Bruna D. Erhan Ian Goodfellow Rob Fergus AAML 183 14,831 1 21 Dec 2013
Poisoning Attacks against Support Vector Machines Battista Biggio B. Nelson Pavel Laskov AAML 92 1,580 0 27 Jun 2012
Better Mini-Batch Algorithms via Accelerated Gradient Methods Andrew Cotter Ohad Shamir Nathan Srebro Karthik Sridharan ODL 93 313 0 22 Jun 2011