Fahrbach, Matthew

13 publications

ICML 2025 Fast Tensor Completion via Approximate Richardson Iteration Mehrdad Ghadiri, Matthew Fahrbach, Yunbum Kook, Ali Jadbabaie

NeurIPS 2025 GIST: Greedy Independent Set Thresholding for Max-Min Diversification with Submodular Utility Matthew Fahrbach, Srikumar Ramalingam, Morteza Zadimoghaddam, Sara Ahmadian, Gui Citovsky, Giulia DeSalvo

ICML 2024 Practical Performance Guarantees for Pipelined DNN Inference Aaron Archer, Matthew Fahrbach, Kuikui Liu, Prakash Prabhu

ICML 2024 PriorBoost: An Adaptive Algorithm for Learning from Aggregate Responses Adel Javanmard, Matthew Fahrbach, Vahab Mirrokni

ICML 2023 Approximately Optimal Core Shapes for Tensor Decompositions Mehrdad Ghadiri, Matthew Fahrbach, Gang Fu, Vahab Mirrokni

ICML 2023 Learning Rate Schedules in the Presence of Distribution Shift Matthew Fahrbach, Adel Javanmard, Vahab Mirrokni, Pratik Worah

ICLR 2023 Sequential Attention for Feature Selection Taisuke Yasuda, Mohammadhossein Bateni, Lin Chen, Matthew Fahrbach, Gang Fu, Vahab Mirrokni

ICMLW 2023 Sequential Attention for Feature Selection Taisuke Yasuda, Mohammadhossein Bateni, Lin Chen, Matthew Fahrbach, Gang Fu, Vahab Mirrokni

ICMLW 2023 Tensor Proxies for Efficient Feature Cross Search Taisuke Yasuda, Mohammadhossein Bateni, Lin Chen, Matthew Fahrbach, Gang Fu

NeurIPS 2023 Unified Embedding: Battle-Tested Feature Representations for Web-Scale ML Systems Benjamin Coleman, Wang-Cheng Kang, Matthew Fahrbach, Ruoxi Wang, Lichan Hong, Ed Chi, Derek Cheng

NeurIPS 2022 Subquadratic Kronecker Regression with Applications to Tensor Decomposition Matthew Fahrbach, Gang Fu, Mehrdad Ghadiri

ICML 2020 Faster Graph Embeddings via Coarsening Matthew Fahrbach, Gramoz Goranci, Richard Peng, Sushant Sachdeva, Chi Wang

ICML 2019 Non-Monotone Submodular Maximization with Nearly Optimal Adaptivity and Query Complexity Matthew Fahrbach, Vahab Mirrokni, Morteza Zadimoghaddam