| An introduction to computational networks and the computational network toolkit D Yu, A Eversole, M Seltzer, K Yao, Z Huang, B Guenter, O Kuchaiev, ... Microsoft Technical Report MSR-TR-2014–112, 2014 | 453 | 2014 |
| How to scale up kernel methods to be as good as deep neural nets Z Lu, A May, K Liu, AB Garakani, D Guo, A Bellet, L Fan, M Collins, ... arXiv preprint arXiv:1411.4000, 2014 | 59 | 2014 |
| Low-precision random Fourier features for memory-constrained kernel approximation J Zhang, A May, T Dao, C Ré The 22nd International Conference on Artificial Intelligence and Statistics …, 2019 | 26 | 2019 |
| Contextual embeddings: When are they worth it? S Arora, A May, J Zhang, C Ré arXiv preprint arXiv:2005.09117, 2020 | 23 | 2020 |
| Filter & follow: How social media foster content curation A May, A Chaintreau, N Korula, S Lattanzi The 2014 ACM international conference on Measurement and modeling of …, 2014 | 18 | 2014 |
| On the downstream performance of compressed word embeddings A May, J Zhang, T Dao, C Ré Advances in neural information processing systems 32, 2019 | 17 | 2019 |
| Kernel approximation methods for speech recognition A May Columbia University, 2018 | 17 | 2018 |
| A comparison between deep neural nets and kernel acoustic models for speech recognition Z Lu, D Quo, AB Garakani, K Liu, A May, A Bellet, L Fan, M Collins, ... 2016 IEEE International Conference on Acoustics, Speech and Signal …, 2016 | 13 | 2016 |
| Understanding the downstream instability of word embeddings M Leszczynski, A May, J Zhang, S Wu, C Aberger, C Ré Proceedings of Machine Learning and Systems 2, 262-290, 2020 | 11 | 2020 |
| Kernel approximation methods for speech recognition A May, AB Garakani, Z Lu, D Guo, K Liu, A Bellet, L Fan, M Collins, D Hsu, ... The Journal of Machine Learning Research 20 (1), 2121-2156, 2019 | 8 | 2019 |
| Compact kernel models for acoustic modeling via random feature selection A May, M Collins, D Hsu, B Kingsbury 2016 IEEE International Conference on Acoustics, Speech and Signal …, 2016 | 6 | 2016 |
| Fei Sha A May, AB Garakani, Z Lu, D Guo, K Liu, A Bellet, L Fan, M Collins, ... Kernel approximation methods for speech recognition. CoRR, abs/1701.03577, 2017 | 5 | 2017 |
| Game in the newsroom: Greedy bloggers for picky audience A May, A Chaintreau, N Korula, S Lattanzi Proc. of the 20th International Conference Companion on World Wide Web, 16-20, 2013 | 4 | 2013 |
| Self-stabilized deep neural network JG Droppo, P Ghahremani, A May US Patent 10,885,438, 2021 | | 2021 |
| Kernel Approximation Methods for Speech Recognition AB Garakani, A May, B Kingsbury, D Hsu, D Guo, F Sha, K Liu, L Fan, ... | | 2019 |
| Filter & Follow: Do Social Media Encourage Efficient News Curation? N Korula, A Chaintreau, A May, S Lattanzi | | 2014 |
| On the Downstream Performance of Compressed Word Embeddings Download PDF A May, J Zhang, T Dao, C Re | | |
| Low-Precision Random Fourier Features for Memory-Constrained Kernel Approximation Download PDF J Zhang, A May, T Dao, C Re | | |
| Contextual Embeddings: When Are They Worth It? Download PDF S Arora, A May, J Zhang, C Ré | | |
| Anatomy of News Popularity on Social Media A May, A Chaintreau, N Korula, S Lattanzi | | |
Christopher RéComputer Science, Stanford UniversityVahvistettu sähköpostiosoite verkkotunnuksessa cs.stanford.edu
