Suivre
Matthew Fahrbach
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Submodular maximization with nearly optimal approximation, adaptivity and query complexity
M Fahrbach, V Mirrokni, M Zadimoghaddam
ACM-SIAM Symposium on Discrete Algorithms (SODA), 255-273, 2019
862019
Edge-weighted online bipartite matching
M Fahrbach, Z Huang, R Tao, M Zadimoghaddam
Journal of the ACM 69 (6), 45:1-45:35, 2022
832022
Non-monotone submodular maximization with nearly optimal adaptivity and query complexity
M Fahrbach, V Mirrokni, M Zadimoghaddam
International Conference on Machine Learning (ICML), 1833-1842, 2019
63*2019
Faster graph embeddings via coarsening
M Fahrbach, G Goranci, R Peng, S Sachdeva, C Wang
International Conference on Machine Learning (ICML), 2953-2963, 2020
302020
Subquadratic Kronecker regression with applications to tensor decomposition
M Fahrbach, G Fu, M Ghadiri
Advances in Neural Information Processing Systems (NeurIPS), 28776-28789, 2022
24*2022
Coefficients and roots of peak polynomials
S Billey, M Fahrbach, A Talmage
Experimental Mathematics 25 (2), 165-175, 2016
182016
Sequential attention for feature selection
T Yasuda, MH Bateni, L Chen, M Fahrbach, G Fu, V Mirrokni
International Conference on Learning Representations (ICLR), 2023
132023
Graph sketching against adaptive adversaries applied to the minimum degree algorithm
M Fahrbach, GL Miller, R Peng, S Sawlani, J Wang, SC Xu
IEEE Symposium on Foundations of Computer Science (FOCS), 101-112, 2018
132018
Unified Embedding: Battle-tested feature representations for web-scale ML systems
B Coleman, WC Kang, M Fahrbach, R Wang, L Hong, E Chi, D Cheng
Advances in Neural Information Processing Systems (NeurIPS), 56234-56255, 2023
102023
Approximately sampling elements with fixed rank in graded posets
P Bhakta, B Cousins, M Fahrbach, D Randall
ACM-SIAM Symposium on Discrete Algorithms (SODA), 1828-1838, 2017
82017
Learning rate schedules in the presence of distribution shift
M Fahrbach, A Javanmard, V Mirrokni, P Worah
International Conference on Machine Learning (ICML), 9523-9546, 2023
72023
Approximately optimal core shapes for tensor decompositions
M Ghadiri, M Fahrbach, G Fu, V Mirrokni
International Conference on Machine Learning (ICML), 11237-11254, 2023
72023
Slow mixing of Glauber dynamics for the six-vertex model in the ordered phases
M Fahrbach, D Randall
International Conference on Randomization and Computation (RANDOM), 37:1-37:20, 2019
62019
Analyzing Boltzmann samplers for Bose–Einstein condensates with Dirichlet generating functions
M Bernstein, M Fahrbach, D Randall
Meeting on Analytic Algorithmics and Combinatorics (ANALCO), 107-117, 2018
62018
Nearly tight bounds for sandpile transience on the grid
D Durfee, M Fahrbach, Y Gao, T Xiao
ACM-SIAM Symposium on Discrete Algorithms (SODA), 605-624, 2018
52018
Practical performance guarantees for pipelined DNN inference
A Archer, M Fahrbach, K Liu, P Prabhu
International Conference on Machine Learning (ICML), 2024
4*2024
A fast minimum degree algorithm and matching lower bound
R Cummings, M Fahrbach, A Fatehpuria
ACM-SIAM Symposium on Discrete Algorithms (SODA), 724-734, 2021
42021
PriorBoost: An adaptive algorithm for learning from aggregate responses
A Javanmard, M Fahrbach, V Mirrokni
International Conference on Machine Learning (ICML), 2024
22024
GIST: Greedy independent set thresholding for diverse data summarization
M Fahrbach, S Ramalingam, M Zadimoghaddam, S Ahmadian, ...
arXiv preprint arXiv:2405.18754, 2024
2024
Greedy PIG: Adaptive integrated gradients
K Axiotis, S Abu-al-haija, L Chen, M Fahrbach, G Fu
arXiv preprint arXiv:2311.06192, 2023
2023
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