Články se zplnomocněním k veřejnému přístupu - Benjamin MoseleyDalší informace
Dostupné někde: 73
Online scheduling via learned weights
S Lattanzi, T Lavastida, B Moseley, S Vassilvitskii
Proceedings of the Fourteenth Annual ACM-SIAM Symposium on Discrete …, 2020
Zplnomocnění: US National Science Foundation
Approximation bounds for hierarchical clustering: Average linkage, bisecting k-means, and local search
B Moseley, JR Wang
Journal of Machine Learning Research 24 (1), 1-36, 2023
Zplnomocnění: US National Science Foundation
Local search methods for k-means with outliers
S Gupta, R Kumar, K Lu, B Moseley, S Vassilvitskii
Proceedings of the VLDB Endowment 10 (7), 757-768, 2017
Zplnomocnění: US National Science Foundation
Efficient massively parallel methods for dynamic programming
S Im, B Moseley, X Sun
Proceedings of the 49th Annual ACM SIGACT Symposium on Theory of Computing …, 2017
Zplnomocnění: US National Science Foundation
Efficient nonmyopic active search
S Jiang, G Malkomes, G Converse, A Shofner, B Moseley, R Garnett
International Conference on Machine Learning, 1714-1723, 2017
Zplnomocnění: US National Science Foundation
Functional aggregate queries with additive inequalities
MA Khamis, RR Curtin, B Moseley, HQ Ngo, XL Nguyen, D Olteanu, ...
ACM Transactions on Database Systems (TODS) 45 (4), 1-41, 2020
Zplnomocnění: US National Science Foundation, European Commission
Fair hierarchical clustering
S Ahmadian, A Epasto, M Knittel, R Kumar, M Mahdian, B Moseley, ...
Advances in Neural Information Processing Systems 33, 21050-21060, 2020
Zplnomocnění: US National Science Foundation
Scheduling parallel DAG jobs online to minimize average flow time
K Agrawal, J Li, K Lu, B Moseley
Proceedings of the Twenty-Seventh Annual ACM-SIAM Symposium on Discrete …, 2016
Zplnomocnění: US National Science Foundation
Backprop with approximate activations for memory-efficient network training
A Chakrabarti, B Moseley
Advances in Neural Information Processing Systems 32, 2019
Zplnomocnění: US National Science Foundation
Energy efficient scheduling of parallelizable jobs
K Fox, S Im, B Moseley
Theoretical Computer Science 726, 30-40, 2018
Zplnomocnění: US National Science Foundation, US Department of Energy
Fast noise removal for k-means clustering
S Im, MM Qaem, B Moseley, X Sun, R Zhou
International Conference on Artificial Intelligence and Statistics, 456-466, 2020
Zplnomocnění: US National Science Foundation
Greed works—online algorithms for unrelated machine stochastic scheduling
V Gupta, B Moseley, M Uetz, Q Xie
Mathematics of operations research 45 (2), 497-516, 2020
Zplnomocnění: US National Science Foundation
Efficient nonmyopic batch active search
S Jiang, G Malkomes, M Abbott, B Moseley, R Garnett
Advances in Neural Information Processing Systems 31, 2018
Zplnomocnění: US National Science Foundation
Scheduling for weighted flow and completion times in reconfigurable networks
M Dinitz, B Moseley
IEEE INFOCOM 2020-IEEE Conference on Computer Communications, 1043-1052, 2020
Zplnomocnění: US National Science Foundation
Faster matchings via learned duals
M Dinitz, S Im, T Lavastida, B Moseley, S Vassilvitskii
Advances in neural information processing systems 34, 10393-10406, 2021
Zplnomocnění: US National Science Foundation
Two-level main memory co-design: Multi-threaded algorithmic primitives, analysis, and simulation
MA Bender, JW Berry, SD Hammond, KS Hemmert, S McCauley, B Moore, ...
Journal of Parallel and Distributed Computing 102, 213-228, 2017
Zplnomocnění: US National Science Foundation, US Department of Energy
Competitively scheduling tasks with intermediate parallelizability
S Im, B Moseley, K Pruhs, E Torng
ACM Transactions on Parallel Computing (TOPC) 3 (1), 1-19, 2016
Zplnomocnění: US National Science Foundation
Stochastic online scheduling on unrelated machines
V Gupta, B Moseley, M Uetz, Q Xie
Integer Programming and Combinatorial Optimization: 19th International …, 2017
Zplnomocnění: US National Science Foundation
Rk-means: Fast clustering for relational data
R Curtin, B Moseley, H Ngo, XL Nguyen, D Olteanu, M Schleich
International Conference on Artificial Intelligence and Statistics, 2742-2752, 2020
Zplnomocnění: US National Science Foundation, European Commission
Robust online correlation clustering
S Lattanzi, B Moseley, S Vassilvitskii, Y Wang, R Zhou
Advances in Neural Information Processing Systems 34, 4688-4698, 2021
Zplnomocnění: US National Science Foundation
Informace o publikování a financování jsou automaticky vybírány počítačovým programem