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Federated Classification in Hyperbolic Spaces via Secure Aggregation of Convex Hulls
Hierarchical and tree-like data sets arise in many relevant applications, including language processing, graph data mining, phylogeny …
Saurav Prakash, Jin Sima, Chao Pan, Eli Chien, Olgica Milenkovic
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Lottery Aware Sparsity Hunting: Enabling Federated Learning on Resource-Limited Edge
Limited computation and communication capabilities of clients pose significant challenges in federated learning (FL) over …
Sara Babakniya, Souvik Kundu, Saurav Prakash, Yue Niu, Salman Avestimehr
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Federated Learning of Large Models at the Edge via Principal Sub-Model Training
Limited compute, memory, and communication capabilities of edge users create a significant bottleneck for federated learning (FL) of …
Yue Niu, Saurav Prakash, Souvik Kundu, Sunwoo Lee, Salman Avestimehr
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Secure and Fault Tolerant Decentralized Learning
Federated learning (FL) is a promising paradigm for training a global model over data distributed across multiple data owners without …
Saurav Prakash, Hanieh Hashemi, Yongqin Wang, Murali Annavaram, Salman Avestimehr
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