Matthew Fahrbach

Publication Activity (10 Years)

Years Active: 2014-2024
Publications (10 Years): 38

Top Topics

Feature Representations

Query Complexity

Top Venues

Publications

Adel Javanmard, Matthew Fahrbach, Vahab Mirrokni
PriorBoost: An Adaptive Algorithm for Learning from Aggregate Responses. CoRR (2024)
Matthew Fahrbach, Srikumar Ramalingam, Morteza Zadimoghaddam, Sara Ahmadian, Gui Citovsky, Giulia DeSalvo
GIST: Greedy Independent Set Thresholding for Diverse Data Summarization. CoRR (2024)
Matthew Fahrbach, Adel Javanmard, Vahab Mirrokni, Pratik Worah
Learning Rate Schedules in the Presence of Distribution Shift. CoRR (2023)
Benjamin Coleman, Wang-Cheng Kang, Matthew Fahrbach, Ruoxi Wang, Lichan Hong, Ed H. Chi, Derek Zhiyuan Cheng
Unified Embedding: Battle-Tested Feature Representations for Web-Scale ML Systems. CoRR (2023)
Matthew Fahrbach, Adel Javanmard, Vahab Mirrokni, Pratik Worah
Learning Rate Schedules in the Presence of Distribution Shift. ICML (2023)
Mehrdad Ghadiri, Matthew Fahrbach, Gang Fu, Vahab Mirrokni
Approximately Optimal Core Shapes for Tensor Decompositions. CoRR (2023)
Taisuke Yasuda, Mohammad Hossein Bateni, Lin Chen, Matthew Fahrbach, Gang Fu, Vahab Mirrokni
Sequential Attention for Feature Selection. ICLR (2023)
Aaron Archer, Matthew Fahrbach, Kuikui Liu, Prakash Prabhu
Pipeline Parallelism for DNN Inference with Practical Performance Guarantees. CoRR (2023)
Mehrdad Ghadiri, Matthew Fahrbach, Gang Fu, Vahab Mirrokni
Approximately Optimal Core Shapes for Tensor Decompositions. ICML (2023)
Kyriakos Axiotis, Sami Abu-El-Haija, Lin Chen, Matthew Fahrbach, Gang Fu
Greedy PIG: Adaptive Integrated Gradients. CoRR (2023)
Benjamin Coleman, Wang-Cheng Kang, Matthew Fahrbach, Ruoxi Wang, Lichan Hong, Ed H. Chi, Derek Zhiyuan Cheng
Unified Embedding: Battle-Tested Feature Representations for Web-Scale ML Systems. NeurIPS (2023)
Matthew Fahrbach, Zhiyi Huang, Runzhou Tao, Morteza Zadimoghaddam
Edge-Weighted Online Bipartite Matching. J. ACM 69 (6) (2022)
Matthew Fahrbach, Gang Fu, Mehrdad Ghadiri
Subquadratic Kronecker Regression with Applications to Tensor Decomposition. NeurIPS (2022)
Matthew Fahrbach, Thomas Fu, Mehrdad Ghadiri
Subquadratic Kronecker Regression with Applications to Tensor Decomposition. CoRR (2022)
MohammadHossein Bateni, Lin Chen, Matthew Fahrbach, Gang Fu, Vahab Mirrokni, Taisuke Yasuda
Sequential Attention for Feature Selection. CoRR (2022)
Robert Cummings, Matthew Fahrbach, Animesh Fatehpuria
A Fast Minimum Degree Algorithm and Matching Lower Bound. SODA (2021)
Matthew Fahrbach, Mehrdad Ghadiri, Thomas Fu
Fast Low-Rank Tensor Decomposition by Ridge Leverage Score Sampling. CoRR (2021)
Matthew Fahrbach, Gramoz Goranci, Richard Peng, Sushant Sachdeva, Chi Wang
Faster Graph Embeddings via Coarsening. ICML (2020)
Matthew Fahrbach, Zhiyi Huang, Runzhou Tao, Morteza Zadimoghaddam
Edge-Weighted Online Bipartite Matching. CoRR (2020)
Matthew Fahrbach, Zhiyi Huang, Runzhou Tao, Morteza Zadimoghaddam
Edge-Weighted Online Bipartite Matching. FOCS (2020)
Matthew Fahrbach, Gramoz Goranci, Richard Peng, Sushant Sachdeva, Chi Wang
Faster Graph Embeddings via Coarsening. CoRR (2020)
Robert Cummings, Matthew Fahrbach, Animesh Fatehpuria
A Fast Minimum Degree Algorithm and Matching Lower Bound. CoRR (2019)
Matthew Fahrbach, Dana Randall
Slow Mixing of Glauber Dynamics for the Six-Vertex Model in the Ferroelectric and Antiferroelectric Phases. CoRR (2019)
Matthew Fahrbach, Dana Randall
Slow Mixing of Glauber Dynamics for the Six-Vertex Model in the Ordered Phases. APPROX-RANDOM (2019)
Matthew Fahrbach, Vahab S. Mirrokni, Morteza Zadimoghaddam
Non-monotone Submodular Maximization with Nearly Optimal Adaptivity and Query Complexity. ICML (2019)
Matthew Fahrbach, Vahab S. Mirrokni, Morteza Zadimoghaddam
Submodular Maximization with Nearly Optimal Approximation, Adaptivity and Query Complexity. SODA (2019)
Matthew Fahrbach, Gary L. Miller, Richard Peng, Saurabh Sawlani, Junxing Wang, Shen Chen Xu
Graph Sketching Against Adaptive Adversaries Applied to the Minimum Degree Algorithm. CoRR (2018)
Matthew Fahrbach, Gary L. Miller, Richard Peng, Saurabh Sawlani, Junxing Wang, Shen Chen Xu
Graph Sketching against Adaptive Adversaries Applied to the Minimum Degree Algorithm. FOCS (2018)
Matthew Fahrbach, Vahab S. Mirrokni, Morteza Zadimoghaddam
Submodular Maximization with Optimal Approximation, Adaptivity and Query Complexity. CoRR (2018)
Megan Bernstein, Matthew Fahrbach, Dana Randall
Analyzing Boltzmann Samplers for Bose-Einstein Condensates with Dirichlet Generating Functions. ANALCO (2018)
Matthew Fahrbach, Vahab S. Mirrokni, Morteza Zadimoghaddam
Non-monotone Submodular Maximization with Nearly Optimal Adaptivity Complexity. CoRR (2018)
David Durfee, Matthew Fahrbach, Yu Gao, Tao Xiao
Nearly Tight Bounds for Sandpile Transience on the Grid. SODA (2018)
David Durfee, Matthew Fahrbach, Yu Gao, Tao Xiao
Tight Bounds for Sandpile Transience on the Two-Dimensional Grid up to Polylogarithmic Factors. CoRR (2017)
Megan Bernstein, Matthew Fahrbach, Dana Randall
Analyzing Boltzmann Samplers for Bose-Einstein Condensates with Dirichlet Generating Functions. CoRR (2017)
Prateek Bhakta, Ben Cousins, Matthew Fahrbach, Dana Randall
Approximately Sampling Elements with Fixed Rank in Graded Posets. SODA (2017)
Matthew Fahrbach, Gary L. Miller, Richard Peng, Saurabh Sawlani, Junxing Wang, Shen Chen Xu
On Computing Min-Degree Elimination Orderings. CoRR (2017)
Sara C. Billey, Matthew Fahrbach, Alan Talmage
Coefficients and Roots of Peak Polynomials. Exp. Math. 25 (2) (2016)
Prateek Bhakta, Ben Cousins, Matthew Fahrbach, Dana Randall
Approximately Sampling Elements with Fixed Rank in Graded Posets. CoRR (2016)
Matthew Fahrbach, Jerzy W. Jaromczyk, Roy David Mobley, Neil Moore
Video game bots as a theme for student software competitions. CGAMES (2014)