Publications

(2021). CodedReduce: A Fast and Robust Framework for Gradient Aggregation in Distributed Learning. In IEEE/ACM Transactions on Networking.

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(2021). Basil: A Fast and Byzantine-Resilient Approach for Decentralized Training. arXiv:2109.07706.

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(2021). Systems and methods for distributed learning for wireless edge dynamics. Patent App. PCT/US2020/067068.

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(2021). Byzantine-Resilient Federated Learning with Heterogeneous Data Distribution. arXiv:2010.07541.

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(2020). Coded computing for low-latency federated learning over wireless edge networks. In IEEE Journal on Selected Areas in Communications.

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(2020). Hierarchical coded gradient aggregation for learning at the edge. In IEEE International Symposium on Information Theory.

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(2020). Coded computing for distributed graph analytics. In IEEE Transactions on Information Theory.

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(2020). Coded federated learning. In IEEE Globecom Workshops.

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(2019). pSConv: A pre-defined sparse kernel based convolution for deep CNNs. In 57th Annual Allerton Conference on Communication, Control, and Computing (Allerton).

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(2019). Coded computing for distributed machine learning in wireless edge network. In IEEE 90th Vehicular Technology Conference (VTC2019-Fall).

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(2019). Tree gradient coding. In IEEE International Symposium on Information Theory.

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(2019). Technologies for distributing iterative computations in heterogeneous computing environments. US Patent App. 16/368,716.

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(2019). Technologies for distributing gradient descent computation in a heterogeneous multi-access edge computing (MEC) networks. US Patent App. 16/235,682.

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(2019). Coded computation over heterogeneous clusters. In IEEE Transactions on Information Theory.

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(2018). Coded computing for distributed graph analytics. In IEEE International Symposium on Information Theory.

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(2017). Coded computation over heterogeneous clusters. In IEEE International Symposium on Information Theory.

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