FLOW Seminar #101: Martin Takáč (MBZUAI) A Second-Order Framework via Compression and Sketching

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FLOW Seminar #27: Honglin Yuan (Stanford) Federated Composite Optimization

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FLOW Seminar #79: Anastasia Koloskova (EPFL) Sharper Convergence Guarantees for Asynchronous SGD

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FLOW Seminar #13: Tian Li (CMU) Learning in Heterogeneous Networks: Optimization and Fairness

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FLOW Seminar #104: Dan Alistarh (IST Austria) FedAvg Made Asynchronous and Communication-Efficient

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FLOW Seminar #56: Sebastian Stich (CISPA) New Methods for More Effective Bidirectional Compression

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FLOW Seminar #1: Ahmed Khaled (Cairo University), On the convergence of Local SGD

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Computer Architecture - Lecture 29: Systolic Array Architectures (Fall 2024)

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FLOW Seminar #40: Peter Richtárik (KAUST) Beyond Local and Gradient Methods for Federated Learning

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FLOW Seminar #105: Peter Richtárik (KAUST) On the 5th Generation of Local Training Methods in FL

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FLOW Seminar #88: Arto Maranjyan (KAUST and Yerevan State University) GradSkip

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FLOW Seminar #95: Chandra Thapa (CSIRO Data61) Combining federated learning and split learning

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FLOW Seminar #76: Anwar Hithnawi (ETH) Security and Robustness of Collaborative Learning Systems

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FLOW Seminar #31: Richard Nock (Google) The Impact of Record Linkage from Feature Partitioned Data

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Model United Nations Flow of Debate Training Video

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FLOW Seminar #94: Slavomír Hanzely (KAUST) Convergence of First-Order Algorithms for Meta-Learning

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FLOW Seminar #120: Nic Lane (Cambridge, Flower Labs) The Future of LLMs is Federated

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FLOW Seminar #20: Eduard Gorbunov (MIPT) Linearly Converging Error Compensated SGD

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FLOW Seminar #87: Praneeth Vepakomma (MIT) Recently engineered variants of split learning

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