• case-insensitive prefix search: default
  e.g., sig matches "SIGIR" as well as "signal"
• exact word search: append dollar sign ($) to word
  e.g., graph$ matches "graph", but not "graphics"
• boolean and: separate words by space
  e.g., codd model
• boolean or: connect words by pipe symbol (|)
  e.g., graph|network

Update May 7, 2017: Please note that we had to disable the phrase search operator (.) and the boolean not operator (-) due to technical problems. For the time being, phrase search queries will yield regular prefix search result, and search terms preceded by a minus will be interpreted as regular (positive) search terms.

found 21 matches

• 2023
• 
  Konstantin Burlachenko, Abdulmajeed Alrowithi, Fahad Ali Albalawi, Peter Richtárik:
  Federated Learning is Better with Non-Homomorphic Encryption. DistributedML@CoNEXT 2023: 49-84
• 
  Grigory Malinovsky, Konstantin Mishchenko, Peter Richtárik:
  Server-Side Stepsizes and Sampling Without Replacement Provably Help in Federated Optimization. DistributedML@CoNEXT 2023: 85-104
• 
  Hongrui Shi, Valentin Radu, Po Yang:
  Lightweight Workloads in Heterogeneous Federated Learning via Few-shot Learning. DistributedML@CoNEXT 2023: 21-26
• 
  Sanjay Sri Vallabh Singapuram, Chuheng Hu, Fan Lai, Chengsong Zhang, Mosharaf Chowdhury:
  Flamingo: A User-Centric System for Fast and Energy-Efficient DNN Training on Smartphones. DistributedML@CoNEXT 2023: 1-10
• 
  Dimitris Stripelis, Chrysovalantis Anastasiou, Patrick Toral, Armaghan Asghar, José Luis Ambite:
  MetisFL: An Embarrassingly Parallelized Controller for Scalable & Efficient Federated Learning Workflows. DistributedML@CoNEXT 2023: 11-19
• 
  Lars Wulfert, Navidreza Asadi, Wen-Yu Chung, Christian Wiede, Anton Grabmaier:
  Adaptive Decentralized Federated Gossip Learning for Resource-Constrained IoT Devices. DistributedML@CoNEXT 2023: 27-33
• 
  Jihao Xin, Ivan Ilin, Shunkang Zhang, Marco Canini, Peter Richtárik:
  Kimad: Adaptive Gradient Compression with Bandwidth Awareness. DistributedML@CoNEXT 2023: 35-48
• 
  Stefanos Laskaridis, Alexey Tumanov, Nathalie Baracaldo, Dimitrios Vytiniotis:
  Proceedings of the 4th International Workshop on Distributed Machine Learning, DistributedML 2023, Paris, France, 8 December 2023. ACM 2023 [contents]
• 2021
• 
  Adarsh Kumar, Kausik Subramanian, Shivaram Venkataraman, Aditya Akella:
  Doing more by doing less: how structured partial backpropagation improves deep learning clusters. DistributedML@CoNEXT 2021: 15-21
• 
  Hadjer Benkraouda, Klara Nahrstedt:
  Image reconstruction attacks on distributed machine learning models. DistributedML@CoNEXT 2021: 29-35
• 
  Konstantin Burlachenko, Samuel Horváth, Peter Richtárik:
  FL_PyTorch: optimization research simulator for federated learning. DistributedML@CoNEXT 2021: 1-7
• 
  Kwing Hei Li, Pedro Porto Buarque de Gusmão, Daniel J. Beutel, Nicholas D. Lane:
  Secure aggregation for federated learning in flower. DistributedML@CoNEXT 2021: 8-14
• 
  Oliver Thompson, Anna Maria Mandalari, Hamed Haddadi:
  Rapid IoT device identification at the edge. DistributedML@CoNEXT 2021: 22-28
• 
  DistributedML '21: Proceedings of the 2nd ACM International Workshop on Distributed Machine Learning, Virtual Event / Munich, Germany, 7 December 2021. ACM 2021, ISBN 978-1-4503-9134-4 [contents]
• 2020
• 
  Rishikesh R. Gajjala, Shashwat Banchhor, Ahmed M. Abdelmoniem, Aritra Dutta, Marco Canini, Panos Kalnis:
  Huffman Coding Based Encoding Techniques for Fast Distributed Deep Learning. DistributedML@CoNEXT 2020: 21-27
• 
  Nicolas Kourtellis, Kleomenis Katevas, Diego Perino:
  FLaaS: Federated Learning as a Service. DistributedML@CoNEXT 2020: 7-13
• 
  Royson Lee, Stylianos I. Venieris, Nicholas D. Lane:
  Neural Enhancement in Content Delivery Systems: The State-of-the-Art and Future Directions. DistributedML@CoNEXT 2020: 34-41
• 
  Duowen Liu:
  Accelerating Intra-Party Communication in Vertical Federated Learning with RDMA. DistributedML@CoNEXT 2020: 14-20
• 
  Moritz Meister, Sina Sheikholeslami, Amir Hossein Payberah, Vladimir Vlassov, Jim Dowling:
  Maggy: Scalable Asynchronous Parallel Hyperparameter Search. DistributedML@CoNEXT 2020: 28-33
• 
  Yongjin Shin, Gihun Lee, Seungjae Shin, Seyoung Yun, Il-Chul Moon:
  FEWER: Federated Weight Recovery. DistributedML@CoNEXT 2020: 1-6
• 
  DistributedML@CoNEXT 2020: Proceedings of the 1st Workshop on Distributed Machine Learning, Barcelona, Spain, December 1, 2020. ACM 2020, ISBN 978-1-4503-8182-6 [contents]