Artigos com autorizações de acesso público - Dan AlistarhSaiba mais
5 artigos não disponíveis publicamente
Forkscan: Conservative memory reclamation for modern operating systems
D Alistarh, W Leiserson, A Matveev, N Shavit
Proceedings of the Twelfth European Conference on Computer Systems, 483-498, 2017
Autorizações: US National Science Foundation, Swiss National Science Foundation
Gradient compression for communication-limited convex optimization
S Khirirat, M Johansson, D Alistarh
2018 IEEE Conference on Decision and Control (CDC), 166-171, 2018
Autorizações: Knut and Alice Wallenberg Foundation
Federated SGD with Local Asynchrony
B Chatterjee, V Kungurtsev, D Alistarh
2024 IEEE 44th International Conference on Distributed Computing Systems …, 2024
Autorizações: Department of Science & Technology, India
Elastic Consistency: A Consistency Criterion for Distributed Optimization
D Alistarh, I Markov, G Nadiradze
ACM SIGACT News 53 (2), 64-82, 2022
Autorizações: European Commission
Brief announcement: are lock-free concurrent algorithms practically wait-free?
D Alistarh, K Censor-Hillel, N Shavit
Proceedings of the 2014 ACM symposium on Principles of distributed computing …, 2014
Autorizações: Swiss National Science Foundation
77 artigos disponíveis publicamente
QSGD: Communication-efficient SGD via gradient quantization and encoding
D Alistarh, D Grubic, J Li, R Tomioka, M Vojnovic
Advances in neural information processing systems 30, 2017
Autorizações: US National Science Foundation, Swiss National Science Foundation
Gptq: Accurate post-training quantization for generative pre-trained transformers
E Frantar, S Ashkboos, T Hoefler, D Alistarh
arXiv preprint arXiv:2210.17323, 2022
Autorizações: European Commission
The convergence of sparsified gradient methods
D Alistarh, T Hoefler, M Johansson, N Konstantinov, S Khirirat, C Renggli
Advances in Neural Information Processing Systems 31, 2018
Autorizações: European Commission
Sparsegpt: Massive language models can be accurately pruned in one-shot
E Frantar, D Alistarh
International Conference on Machine Learning, 10323-10337, 2023
Autorizações: European Commission
Byzantine stochastic gradient descent
D Alistarh, Z Allen-Zhu, J Li
Advances in neural information processing systems 31, 2018
Autorizações: US National Science Foundation
ZipML: Training linear models with end-to-end low precision, and a little bit of deep learning
H Zhang, J Li, K Kara, D Alistarh, J Liu, C Zhang
International Conference on Machine Learning, 4035-4043, 2017
Autorizações: Swiss National Science Foundation
Optimal brain compression: A framework for accurate post-training quantization and pruning
E Frantar, D Alistarh
Advances in Neural Information Processing Systems 35, 4475-4488, 2022
Autorizações: European Commission
Woodfisher: Efficient second-order approximation for neural network compression
SP Singh, D Alistarh
Advances in Neural Information Processing Systems 33, 18098-18109, 2020
Autorizações: European Commission
SparCML: High-performance sparse communication for machine learning
C Renggli, S Ashkboos, M Aghagolzadeh, D Alistarh, T Hoefler
Proceedings of the International Conference for High Performance Computing …, 2019
Autorizações: European Commission
Time-space trade-offs in population protocols
D Alistarh, J Aspnes, D Eisenstat, R Gelashvili, RL Rivest
Proceedings of the twenty-eighth annual ACM-SIAM symposium on discrete …, 2017
Autorizações: US National Science Foundation, US Department of Energy, Swiss National …
The spraylist: A scalable relaxed priority queue
D Alistarh, J Kopinsky, J Li, N Shavit
Proceedings of the 20th ACM SIGPLAN Symposium on Principles and Practice of …, 2015
Autorizações: US Department of Energy
Space-optimal majority in population protocols
D Alistarh, J Aspnes, R Gelashvili
Proceedings of the Twenty-Ninth Annual ACM-SIAM Symposium on Discrete …, 2018
Autorizações: US National Science Foundation, US Department of Energy, Swiss National …
Polylogarithmic-time leader election in population protocols
D Alistarh, R Gelashvili
International Colloquium on Automata, Languages, and Programming, 479-491, 2015
Autorizações: US Department of Energy
Adaptive gradient quantization for data-parallel sgd
F Faghri, I Tabrizian, I Markov, D Alistarh, DM Roy, A Ramezani-Kebrya
Advances in neural information processing systems 33, 3174-3185, 2020
Autorizações: Natural Sciences and Engineering Research Council of Canada, European Commission
Ac/dc: Alternating compressed/decompressed training of deep neural networks
A Peste, E Iofinova, A Vladu, D Alistarh
Advances in neural information processing systems 34, 8557-8570, 2021
Autorizações: European Commission
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