A study of BFLOAT16 for deep learning training D Kalamkar, D Mudigere, N Mellempudi, D Das, K Banerjee, S Avancha, ...
arXiv preprint arXiv:1905.12322, 2019
382 2019 Quasi-Monte Carlo feature maps for shift-invariant kernels J Yang, V Sindhwani, H Avron, MW Mahoney
International Conference on Machine Learning (ICML 2014), 2014
206 * 2014 Software-hardware co-design for fast and scalable training of deep learning recommendation models D Mudigere, Y Hao, J Huang, Z Jia, A Tulloch, S Sridharan, X Liu, ...
Proceedings of the 49th Annual International Symposium on Computer …, 2022
177 * 2022 Sub-sampled Newton methods with non-uniform sampling P Xu, J Yang, F Roosta, C Ré, MW Mahoney
Advances in Neural Information Processing Systems 29, 2016
144 2016 Compositional embeddings using complementary partitions for memory-efficient recommendation systems HJM Shi, D Mudigere, M Naumov, J Yang
Proceedings of the 26th ACM SIGKDD International Conference on Knowledge …, 2020
125 2020 Mixed dimension embeddings with application to memory-efficient recommendation systems AA Ginart, M Naumov, D Mudigere, J Yang, J Zou
2021 IEEE International Symposium on Information Theory (ISIT), 2786-2791, 2021
108 2021 Deep learning training in facebook data centers: Design of scale-up and scale-out systems M Naumov, J Kim, D Mudigere, S Sridharan, X Wang, W Zhao, S Yilmaz, ...
arXiv preprint arXiv:2003.09518, 2020
98 2020 Towards automated neural interaction discovery for click-through rate prediction Q Song, D Cheng, H Zhou, J Yang, Y Tian, X Hu
Proceedings of the 26th ACM SIGKDD International Conference on Knowledge …, 2020
94 2020 Matrix factorizations at scale: A comparison of scientific data analytics in Spark and C+ MPI using three case studies A Gittens, A Devarakonda, E Racah, M Ringenburg, L Gerhardt, ...
2016 IEEE International Conference on Big Data (Big Data), 204-213, 2016
87 2016 Implementing randomized matrix algorithms in parallel and distributed environments J Yang, X Meng, MW Mahoney
Proceedings of the IEEE 104 (1), 58-92, 2015
71 2015 Quantile regression for large-scale applications J Yang, X Meng, M Mahoney
International Conference on Machine Learning, 881-887, 2013
65 2013 Online modified greedy algorithm for storage control under uncertainty J Qin, Y Chow, J Yang, R Rajagopal
IEEE Transactions on Power Systems 31 (3), 1729-1743, 2015
64 2015 Random laplace feature maps for semigroup kernels on histograms J Yang, V Sindhwani, Q Fan, H Avron, MW Mahoney
Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2014
64 2014 Weighted SGD for J Yang, YL Chow, C Ré, MW Mahoney
Journal of Machine Learning Research 18 (211), 1-43, 2018
53 2018 Distributed online modified greedy algorithm for networked storage operation under uncertainty J Qin, Y Chow, J Yang, R Rajagopal
IEEE Transactions on Smart Grid 7 (2), 1106-1118, 2015
46 2015 Identifying important ions and positions in mass spectrometry imaging data using CUR matrix decompositions J Yang, O Rubel, Prabhat, MW Mahoney, BP Bowen
Analytical chemistry 87 (9), 4658-4666, 2015
45 2015 Post-training 4-bit quantization on embedding tables H Guan, A Malevich, J Yang, J Park, H Yuen
arXiv preprint arXiv:1911.02079, 2019
38 2019 CPR: Understanding and improving failure tolerant training for deep learning recommendation with partial recovery K Maeng, S Bharuka, I Gao, MC Jeffrey, V Saraph, BY Su, C Trippel, ...
arXiv preprint arXiv:2011.02999, 2020
30 2020 DHEN: A deep and hierarchical ensemble network for large-scale click-through rate prediction B Zhang, L Luo, X Liu, J Li, Z Chen, W Zhang, X Wei, Y Hao, M Tsang, ...
arXiv preprint arXiv:2203.11014, 2022
23 2022 Modeling and online control of generalized energy storage networks J Qin, Y Chow, J Yang, R Rajagopal
Proceedings of the 5th international conference on Future energy systems, 27-38, 2014
21 * 2014 
Michael MahoneyProfessor of Statistics, UC BerkeleyAdresse e-mail validée de stat.berkeley.edu
