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ORCIDJakub Konecný
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- unicode name: Jakub Konečný
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2020 – today
- 2023
[c8]Nicole Mitchell, Johannes Ballé, Zachary Charles, Jakub Konecný:
A Rate-Distortion View on Model Updates. Tiny Papers @ ICLR 2023- 2022
- [c7]Chen Zhu, Zheng Xu, Mingqing Chen, Jakub Konecný, Andrew Hard, Tom Goldstein:
Diurnal or Nocturnal? Federated Learning of Multi-branch Networks from Periodically Shifting Distributions. ICLR 2022 - [i27]Nicole Mitchell, Johannes Ballé, Zachary Charles, Jakub Konecný:
Optimizing the Communication-Accuracy Trade-off in Federated Learning with Rate-Distortion Theory. CoRR abs/2201.02664 (2022) - 2021
- [j7]Peter Kairouz, H. Brendan McMahan, Brendan Avent, Aurélien Bellet, Mehdi Bennis
, Arjun Nitin Bhagoji, Kallista A. Bonawitz, Zachary Charles, Graham Cormode, Rachel Cummings, Rafael G. L. D'Oliveira, Hubert Eichner, Salim El Rouayheb, David Evans, Josh Gardner, Zachary Garrett, Adrià Gascón, Badih Ghazi, Phillip B. Gibbons, Marco Gruteser, Zaïd Harchaoui, Chaoyang He, Lie He, Zhouyuan Huo, Ben Hutchinson, Justin Hsu, Martin Jaggi, Tara Javidi, Gauri Joshi, Mikhail Khodak, Jakub Konecný, Aleksandra Korolova, Farinaz Koushanfar, Sanmi Koyejo, Tancrède Lepoint, Yang Liu, Prateek Mittal, Mehryar Mohri, Richard Nock, Ayfer Özgür, Rasmus Pagh, Hang Qi, Daniel Ramage, Ramesh Raskar, Mariana Raykova, Dawn Song, Weikang Song, Sebastian U. Stich, Ziteng Sun, Ananda Theertha Suresh, Florian Tramèr, Praneeth Vepakomma, Jianyu Wang, Li Xiong, Zheng Xu, Qiang Yang, Felix X. Yu, Han Yu, Sen Zhao:
Advances and Open Problems in Federated Learning. Found. Trends Mach. Learn. 14(1-2): 1-210 (2021) - [c6]Zachary Charles, Jakub Konecný:
Convergence and Accuracy Trade-Offs in Federated Learning and Meta-Learning. AISTATS 2021: 2575-2583 - [c5]Sashank J. Reddi, Zachary Charles, Manzil Zaheer, Zachary Garrett, Keith Rush, Jakub Konecný, Sanjiv Kumar, Hugh Brendan McMahan:
Adaptive Federated Optimization. ICLR 2021 - [i26]Zachary Charles, Jakub Konecný:
Convergence and Accuracy Trade-Offs in Federated Learning and Meta-Learning. CoRR abs/2103.05032 (2021) - [i25]Jianyu Wang, Zachary Charles, Zheng Xu, Gauri Joshi, H. Brendan McMahan, Blaise Agüera y Arcas, Maruan Al-Shedivat, Galen Andrew, Salman Avestimehr, Katharine Daly, Deepesh Data, Suhas N. Diggavi, Hubert Eichner, Advait Gadhikar, Zachary Garrett, Antonious M. Girgis, Filip Hanzely, Andrew Hard, Chaoyang He, Samuel Horváth, Zhouyuan Huo, Alex Ingerman, Martin Jaggi, Tara Javidi, Peter Kairouz, Satyen Kale, Sai Praneeth Karimireddy, Jakub Konecný, Sanmi Koyejo, Tian Li, Luyang Liu, Mehryar Mohri, Hang Qi, Sashank J. Reddi, Peter Richtárik, Karan Singhal, Virginia Smith, Mahdi Soltanolkotabi, Weikang Song, Ananda Theertha Suresh, Sebastian U. Stich, Ameet Talwalkar, Hongyi Wang, Blake E. Woodworth, Shanshan Wu, Felix X. Yu, Honglin Yuan, Manzil Zaheer, Mi Zhang, Tong Zhang, Chunxiang Zheng, Chen Zhu, Wennan Zhu:
A Field Guide to Federated Optimization. CoRR abs/2107.06917 (2021) - 2020
- [i24]Sashank J. Reddi, Zachary Charles, Manzil Zaheer, Zachary Garrett, Keith Rush, Jakub Konecný, Sanjiv Kumar, H. Brendan McMahan:
Adaptive Federated Optimization. CoRR abs/2003.00295 (2020) - [i23]Zachary Charles, Jakub Konecný:
On the Outsized Importance of Learning Rates in Local Update Methods. CoRR abs/2007.00878 (2020)
2010 – 2019
- 2019
- [c4]Kallista A. Bonawitz, Fariborz Salehi, Jakub Konecný, Brendan McMahan, Marco Gruteser:
Federated Learning with Autotuned Communication-Efficient Secure Aggregation. ACSSC 2019: 1222-1226 - [c3]Kallista A. Bonawitz, Hubert Eichner, Wolfgang Grieskamp, Dzmitry Huba, Alex Ingerman, Vladimir Ivanov, Chloé Kiddon, Jakub Konecný, Stefano Mazzocchi, Brendan McMahan, Timon Van Overveldt, David Petrou, Daniel Ramage, Jason Roselander:
Towards Federated Learning at Scale: System Design. SysML 2019 - [i22]Filip Hanzely, Jakub Konecný, Nicolas Loizou, Peter Richtárik, Dmitry Grishchenko:
A Privacy Preserving Randomized Gossip Algorithm via Controlled Noise Insertion. CoRR abs/1901.09367 (2019) - [i21]Kallista A. Bonawitz, Hubert Eichner, Wolfgang Grieskamp, Dzmitry Huba, Alex Ingerman, Vladimir Ivanov, Chloé Kiddon, Jakub Konecný, Stefano Mazzocchi, H. Brendan McMahan, Timon Van Overveldt, David Petrou, Daniel Ramage, Jason Roselander:
Towards Federated Learning at Scale: System Design. CoRR abs/1902.01046 (2019) - [i20]Alexander Ratner, Dan Alistarh, Gustavo Alonso, David G. Andersen, Peter Bailis, Sarah Bird, Nicholas Carlini, Bryan Catanzaro, Eric S. Chung, Bill Dally, Jeff Dean, Inderjit S. Dhillon, Alexandros G. Dimakis, Pradeep Dubey, Charles Elkan, Grigori Fursin, Gregory R. Ganger, Lise Getoor, Phillip B. Gibbons, Garth A. Gibson, Joseph E. Gonzalez, Justin Gottschlich, Song Han, Kim M. Hazelwood, Furong Huang, Martin Jaggi, Kevin G. Jamieson, Michael I. Jordan, Gauri Joshi, Rania Khalaf, Jason Knight, Jakub Konecný, Tim Kraska, Arun Kumar, Anastasios Kyrillidis, Jing Li, Samuel Madden, H. Brendan McMahan, Erik Meijer, Ioannis Mitliagkas, Rajat Monga, Derek Gordon Murray, Dimitris S. Papailiopoulos, Gennady Pekhimenko, Theodoros Rekatsinas, Afshin Rostamizadeh, Christopher Ré, Christopher De Sa, Hanie Sedghi, Siddhartha Sen, Virginia Smith, Alex Smola, Dawn Song, Evan Randall Sparks, Ion Stoica, Vivienne Sze, Madeleine Udell, Joaquin Vanschoren, Shivaram Venkataraman, Rashmi Vinayak, Markus Weimer, Andrew Gordon Wilson, Eric P. Xing, Matei Zaharia, Ce Zhang, Ameet Talwalkar:
SysML: The New Frontier of Machine Learning Systems. CoRR abs/1904.03257 (2019) - [i19]Yihan Jiang, Jakub Konecný, Keith Rush, Sreeram Kannan:
Improving Federated Learning Personalization via Model Agnostic Meta Learning. CoRR abs/1909.12488 (2019) - [i18]Kallista A. Bonawitz, Fariborz Salehi, Jakub Konecný, Brendan McMahan, Marco Gruteser:
Federated Learning with Autotuned Communication-Efficient Secure Aggregation. CoRR abs/1912.00131 (2019) - [i17]Peter Kairouz, H. Brendan McMahan, Brendan Avent, Aurélien Bellet, Mehdi Bennis, Arjun Nitin Bhagoji, Kallista A. Bonawitz, Zachary Charles, Graham Cormode, Rachel Cummings, Rafael G. L. D'Oliveira, Salim El Rouayheb, David Evans, Josh Gardner, Zachary Garrett, Adrià Gascón, Badih Ghazi, Phillip B. Gibbons, Marco Gruteser, Zaïd Harchaoui, Chaoyang He, Lie He, Zhouyuan Huo, Ben Hutchinson, Justin Hsu, Martin Jaggi, Tara Javidi, Gauri Joshi, Mikhail Khodak, Jakub Konecný, Aleksandra Korolova, Farinaz Koushanfar, Sanmi Koyejo, Tancrède Lepoint, Yang Liu, Prateek Mittal, Mehryar Mohri, Richard Nock, Ayfer Özgür, Rasmus Pagh, Mariana Raykova, Hang Qi, Daniel Ramage, Ramesh Raskar, Dawn Song, Weikang Song, Sebastian U. Stich, Ziteng Sun, Ananda Theertha Suresh, Florian Tramèr, Praneeth Vepakomma, Jianyu Wang, Li Xiong, Zheng Xu, Qiang Yang, Felix X. Yu, Han Yu, Sen Zhao:
Advances and Open Problems in Federated Learning. CoRR abs/1912.04977 (2019) - 2018
- [j6]Jakub Konecný, Peter Richtárik:
Randomized Distributed Mean Estimation: Accuracy vs. Communication. Frontiers Appl. Math. Stat. 4: 62 (2018) - [i16]Sebastian Caldas, Peter Wu, Tian Li, Jakub Konecný, H. Brendan McMahan, Virginia Smith, Ameet Talwalkar:
LEAF: A Benchmark for Federated Settings. CoRR abs/1812.01097 (2018) - [i15]Sebastian Caldas, Jakub Konecný, H. Brendan McMahan, Ameet Talwalkar:
Expanding the Reach of Federated Learning by Reducing Client Resource Requirements. CoRR abs/1812.07210 (2018) - 2017
- [b1]Jakub Konecný:
Stochastic, distributed and federated optimization for machine learning. University of Edinburgh, UK, 2017 - [j5]Jakub Konecný, Peter Richtárik:
Semi-Stochastic Gradient Descent Methods. Frontiers Appl. Math. Stat. 3: 9 (2017) - [j4]Chenxin Ma, Jakub Konecný, Martin Jaggi, Virginia Smith, Michael I. Jordan, Peter Richtárik, Martin Takác:
Distributed optimization with arbitrary local solvers. Optim. Methods Softw. 32(4): 813-848 (2017) - [j3]Jakub Konecný, Zheng Qu, Peter Richtárik:
Semi-stochastic coordinate descent. Optim. Methods Softw. 32(5): 993-1005 (2017) - [c2]Lukas Malina, Jakub Konecný, Petr Dzurenda, Jan Hajny:
On practical deployment of smart card based authenticated key agreement schemes. ICUMT 2017: 277-282 - [p1]Jakub Konecný, Michal Hagara:
One-Shot-Learning Gesture Recognition Using HOG-HOF Features. Gesture Recognition 2017: 365-385 - [i14]Jakub Konecný:
Stochastic, Distributed and Federated Optimization for Machine Learning. CoRR abs/1707.01155 (2017) - 2016
- [j2]Jakub Konecný, Jie Liu, Peter Richtárik, Martin Takác:
Mini-Batch Semi-Stochastic Gradient Descent in the Proximal Setting. IEEE J. Sel. Top. Signal Process. 10(2): 242-255 (2016) - [i13]Sashank J. Reddi, Jakub Konecný, Peter Richtárik, Barnabás Póczos, Alexander J. Smola:
AIDE: Fast and Communication Efficient Distributed Optimization. CoRR abs/1608.06879 (2016) - [i12]Jakub Konecný, H. Brendan McMahan, Daniel Ramage, Peter Richtárik:
Federated Optimization: Distributed Machine Learning for On-Device Intelligence. CoRR abs/1610.02527 (2016) - [i11]Jakub Konecný, H. Brendan McMahan, Felix X. Yu, Peter Richtárik, Ananda Theertha Suresh, Dave Bacon:
Federated Learning: Strategies for Improving Communication Efficiency. CoRR abs/1610.05492 (2016) - [i10]Jakub Konecný, Peter Richtárik:
Randomized Distributed Mean Estimation: Accuracy vs Communication. CoRR abs/1611.07555 (2016) - 2015
- [c1]Reza Babanezhad, Mohamed Osama Ahmed, Alim Virani, Mark Schmidt, Jakub Konecný, Scott Sallinen:
StopWasting My Gradients: Practical SVRG. NIPS 2015: 2251-2259 - [i9]Jakub Konecný, Jie Liu, Peter Richtárik, Martin Takác:
Mini-Batch Semi-Stochastic Gradient Descent in the Proximal Setting. CoRR abs/1504.04407 (2015) - [i8]Reza Babanezhad, Mohamed Osama Ahmed, Alim Virani, Mark Schmidt, Jakub Konecný, Scott Sallinen:
Stop Wasting My Gradients: Practical SVRG. CoRR abs/1511.01942 (2015) - [i7]Jakub Konecný, Brendan McMahan, Daniel Ramage:
Federated Optimization: Distributed Optimization Beyond the Datacenter. CoRR abs/1511.03575 (2015) - [i6]Chenxin Ma, Jakub Konecný, Martin Jaggi, Virginia Smith, Michael I. Jordan, Peter Richtárik, Martin Takác:
Distributed Optimization with Arbitrary Local Solvers. CoRR abs/1512.04039 (2015) - 2014
- [j1]Jakub Konecný, Michal Hagara:
One-shot-learning gesture recognition using HOG-HOF features. J. Mach. Learn. Res. 15(1): 2513-2532 (2014) - [i5]Jakub Konecný, Peter Richtárik:
Simple Complexity Analysis of Direct Search. CoRR abs/1410.0390 (2014) - [i4]Jakub Konecný, Jie Liu, Peter Richtárik, Martin Takác:
mS2GD: Mini-Batch Semi-Stochastic Gradient Descent in the Proximal Setting. CoRR abs/1410.4744 (2014) - [i3]Jakub Konecný, Zheng Qu, Peter Richtárik:
Semi-Stochastic Coordinate Descent. CoRR abs/1412.6293 (2014) - 2013
- [i2]Jakub Konecný, Peter Richtárik:
Semi-Stochastic Gradient Descent Methods. CoRR abs/1312.1666 (2013) - [i1]Jakub Konecný, Michal Hagara:
One-Shot-Learning Gesture Recognition using HOG-HOF Features. CoRR abs/1312.4190 (2013)
Coauthor Index
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