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ORCIDMatthew Fahrbach
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2020 – today
- 2024
[c18]Aaron Archer, Matthew Fahrbach, Kuikui Liu, Prakash Prabhu:
Practical Performance Guarantees for Pipelined DNN Inference. ICML 2024- [c17]Adel Javanmard, Matthew Fahrbach, Vahab Mirrokni:
PriorBoost: An Adaptive Algorithm for Learning from Aggregate Responses. ICML 2024 - [i21]Adel Javanmard, Matthew Fahrbach, Vahab Mirrokni:
PriorBoost: An Adaptive Algorithm for Learning from Aggregate Responses. CoRR abs/2402.04987 (2024) - [i20]Matthew Fahrbach, Srikumar Ramalingam, Morteza Zadimoghaddam, Sara Ahmadian, Gui Citovsky, Giulia DeSalvo:
GIST: Greedy Independent Set Thresholding for Diverse Data Summarization. CoRR abs/2405.18754 (2024) - 2023
- [c16]Taisuke Yasuda, Mohammad Hossein Bateni, Lin Chen, Matthew Fahrbach, Gang Fu, Vahab Mirrokni:
Sequential Attention for Feature Selection. ICLR 2023 - [c15]Matthew Fahrbach, Adel Javanmard, Vahab Mirrokni, Pratik Worah:
Learning Rate Schedules in the Presence of Distribution Shift. ICML 2023: 9523-9546 - [c14]Mehrdad Ghadiri, Matthew Fahrbach, Gang Fu, Vahab Mirrokni:
Approximately Optimal Core Shapes for Tensor Decompositions. ICML 2023: 11237-11254 - [c13]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 - [i19]Mehrdad Ghadiri, Matthew Fahrbach, Gang Fu, Vahab Mirrokni:
Approximately Optimal Core Shapes for Tensor Decompositions. CoRR abs/2302.03886 (2023) - [i18]Matthew Fahrbach, Adel Javanmard, Vahab Mirrokni, Pratik Worah:
Learning Rate Schedules in the Presence of Distribution Shift. CoRR abs/2303.15634 (2023) - [i17]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 abs/2305.12102 (2023) - [i16]Aaron Archer, Matthew Fahrbach, Kuikui Liu, Prakash Prabhu:
Pipeline Parallelism for DNN Inference with Practical Performance Guarantees. CoRR abs/2311.03703 (2023) - [i15]Kyriakos Axiotis, Sami Abu-El-Haija, Lin Chen, Matthew Fahrbach, Gang Fu:
Greedy PIG: Adaptive Integrated Gradients. CoRR abs/2311.06192 (2023) - 2022
- [j2]Matthew Fahrbach
, Zhiyi Huang, Runzhou Tao, Morteza Zadimoghaddam:
Edge-Weighted Online Bipartite Matching. J. ACM 69(6): 45:1-45:35 (2022) - [c12]Matthew Fahrbach, Gang Fu, Mehrdad Ghadiri:
Subquadratic Kronecker Regression with Applications to Tensor Decomposition. NeurIPS 2022 - [i14]Matthew Fahrbach, Thomas Fu, Mehrdad Ghadiri:
Subquadratic Kronecker Regression with Applications to Tensor Decomposition. CoRR abs/2209.04876 (2022) - [i13]MohammadHossein Bateni, Lin Chen, Matthew Fahrbach, Gang Fu, Vahab Mirrokni, Taisuke Yasuda:
Sequential Attention for Feature Selection. CoRR abs/2209.14881 (2022) - 2021
- [c11]Robert Cummings, Matthew Fahrbach, Animesh Fatehpuria:
A Fast Minimum Degree Algorithm and Matching Lower Bound. SODA 2021: 724-734 - [i12]Matthew Fahrbach, Mehrdad Ghadiri, Thomas Fu:
Fast Low-Rank Tensor Decomposition by Ridge Leverage Score Sampling. CoRR abs/2107.10654 (2021) - 2020
- [c10]Matthew Fahrbach, Zhiyi Huang, Runzhou Tao, Morteza Zadimoghaddam:
Edge-Weighted Online Bipartite Matching. FOCS 2020: 412-423 - [c9]Matthew Fahrbach, Gramoz Goranci, Richard Peng, Sushant Sachdeva, Chi Wang:
Faster Graph Embeddings via Coarsening. ICML 2020: 2953-2963 - [i11]Matthew Fahrbach, Zhiyi Huang, Runzhou Tao, Morteza Zadimoghaddam:
Edge-Weighted Online Bipartite Matching. CoRR abs/2005.01929 (2020) - [i10]Matthew Fahrbach, Gramoz Goranci, Richard Peng, Sushant Sachdeva, Chi Wang:
Faster Graph Embeddings via Coarsening. CoRR abs/2007.02817 (2020)
2010 – 2019
- 2019
- [c8]Matthew Fahrbach, Dana Randall:
Slow Mixing of Glauber Dynamics for the Six-Vertex Model in the Ordered Phases. APPROX-RANDOM 2019: 37:1-37:20 - [c7]Matthew Fahrbach, Vahab S. Mirrokni, Morteza Zadimoghaddam:
Non-monotone Submodular Maximization with Nearly Optimal Adaptivity and Query Complexity. ICML 2019: 1833-1842 - [c6]Matthew Fahrbach, Vahab S. Mirrokni, Morteza Zadimoghaddam:
Submodular Maximization with Nearly Optimal Approximation, Adaptivity and Query Complexity. SODA 2019: 255-273 - [i9]Matthew Fahrbach, Dana Randall:
Slow Mixing of Glauber Dynamics for the Six-Vertex Model in the Ferroelectric and Antiferroelectric Phases. CoRR abs/1904.01495 (2019) - [i8]Robert Cummings, Matthew Fahrbach, Animesh Fatehpuria:
A Fast Minimum Degree Algorithm and Matching Lower Bound. CoRR abs/1907.12119 (2019) - 2018
- [c5]Megan Bernstein, Matthew Fahrbach, Dana Randall:
Analyzing Boltzmann Samplers for Bose-Einstein Condensates with Dirichlet Generating Functions. ANALCO 2018: 107-117 - [c4]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: 101-112 - [c3]David Durfee, Matthew Fahrbach, Yu Gao, Tao Xiao:
Nearly Tight Bounds for Sandpile Transience on the Grid. SODA 2018: 605-624 - [i7]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 abs/1804.04239 (2018) - [i6]Matthew Fahrbach, Vahab S. Mirrokni, Morteza Zadimoghaddam:
Submodular Maximization with Optimal Approximation, Adaptivity and Query Complexity. CoRR abs/1807.07889 (2018) - [i5]Matthew Fahrbach, Vahab S. Mirrokni, Morteza Zadimoghaddam:
Non-monotone Submodular Maximization with Nearly Optimal Adaptivity Complexity. CoRR abs/1808.06932 (2018) - 2017
- [c2]Prateek Bhakta, Ben Cousins, Matthew Fahrbach, Dana Randall:
Approximately Sampling Elements with Fixed Rank in Graded Posets. SODA 2017: 1828-1838 - [i4]David Durfee, Matthew Fahrbach, Yu Gao, Tao Xiao:
Tight Bounds for Sandpile Transience on the Two-Dimensional Grid up to Polylogarithmic Factors. CoRR abs/1704.04830 (2017) - [i3]Megan Bernstein, Matthew Fahrbach, Dana Randall:
Analyzing Boltzmann Samplers for Bose-Einstein Condensates with Dirichlet Generating Functions. CoRR abs/1708.02266 (2017) - [i2]Matthew Fahrbach, Gary L. Miller, Richard Peng, Saurabh Sawlani, Junxing Wang, Shen Chen Xu:
On Computing Min-Degree Elimination Orderings. CoRR abs/1711.08446 (2017) - 2016
- [j1]Sara C. Billey, Matthew Fahrbach, Alan Talmage:
Coefficients and Roots of Peak Polynomials. Exp. Math. 25(2): 165-175 (2016) - [i1]Prateek Bhakta, Ben Cousins, Matthew Fahrbach, Dana Randall:
Approximately Sampling Elements with Fixed Rank in Graded Posets. CoRR abs/1611.03385 (2016) - 2014
- [c1]Matthew Fahrbach, Jerzy W. Jaromczyk, Roy David Mobley, Neil Moore:
Video game bots as a theme for student software competitions. CGAMES 2014: 1-4
Coauthor Index
aka: Vahab Mirrokni
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