no code implementations • 10 Mar 2024 • Hamid Mozaffari, Sunav Choudhary, Amir Houmansadr
Federated learning (FL) is a distributed machine learning paradigm that enables training models on decentralized data.
no code implementations • 4 Feb 2024 • Harshita Chopra, Atanu R. Sinha, Sunav Choudhary, Ryan A. Rossi, Paavan Kumar Indela, Veda Pranav Parwatala, Srinjayee Paul, Aurghya Maiti
Following the discovery of segments, delivery of messages to users through preferred media channels like Facebook and Google can be challenging, as only a portion of users in a behavior segment find match in a medium, and only a fraction of those matched actually see the message (exposure).
no code implementations • 28 Nov 2022 • Kunjal Panchal, Sunav Choudhary, Nisarg Parikh, Lijun Zhang, Hui Guan
Current approaches to personalization in FL are at a coarse granularity, i. e. all the input instances of a client use the same personalized model.
no code implementations • CVPR 2022 • Haoyu Ma, Handong Zhao, Zhe Lin, Ajinkya Kale, Zhangyang Wang, Tong Yu, Jiuxiang Gu, Sunav Choudhary, Xiaohui Xie
recommendation, and marketing services.
4 code implementations • 2 Dec 2019 • Manoj Ghuhan Arivazhagan, Vinay Aggarwal, Aaditya Kumar Singh, Sunav Choudhary
The emerging paradigm of federated learning strives to enable collaborative training of machine learning models on the network edge without centrally aggregating raw data and hence, improving data privacy.
no code implementations • 28 Nov 2019 • Ramit Pahwa, Manoj Ghuhan Arivazhagan, Ankur Garg, Siddarth Krishnamoorthy, Rohit Saxena, Sunav Choudhary
Designing and training a CNN architecture that does well on all three metrics is highly non-trivial and can be very time-consuming if done by hand.