| Natural tts synthesis by conditioning wavenet on mel spectrogram predictions J Shen, R Pang, RJ Weiss, M Schuster, N Jaitly, Z Yang, Z Chen, Y Zhang, ... 2018 IEEE international conference on acoustics, speech and signal …, 2018 | 3234 | 2018 |
| CNN architectures for large-scale audio classification S Hershey, S Chaudhuri, DPW Ellis, JF Gemmeke, A Jansen, RC Moore, ... 2017 ieee international conference on acoustics, speech and signal …, 2017 | 3042 | 2017 |
| Prediction of central nervous system embryonal tumour outcome based on gene expression SL Pomeroy, P Tamayo, M Gaasenbeek, LM Sturla, M Angelo, ... Nature 415 (6870), 436-442, 2002 | 2855 | 2002 |
| Multiclass cancer diagnosis using tumor gene expression signatures S Ramaswamy, P Tamayo, R Rifkin, S Mukherjee, CH Yeang, M Angelo, ... Proceedings of the National Academy of Sciences 98 (26), 15149-15154, 2001 | 2604 | 2001 |
| In defense of one-vs-all classification R Rifkin, A Klautau The Journal of Machine Learning Research 5, 101-141, 2004 | 2568 | 2004 |
| Tacotron: Towards end-to-end speech synthesis Y Wang, RJ Skerry-Ryan, D Stanton, Y Wu, RJ Weiss, N Jaitly, Z Yang, ... arXiv preprint arXiv:1703.10135, 2017 | 2450* | 2017 |
| Beyond the imitation game: Quantifying and extrapolating the capabilities of language models A Srivastava, A Rastogi, A Rao, AAM Shoeb, A Abid, A Fisch, AR Brown, ... arXiv preprint arXiv:2206.04615, 2022 | 1000 | 2022 |
| Style tokens: Unsupervised style modeling, control and transfer in end-to-end speech synthesis Y Wang, D Stanton, Y Zhang, RJS Ryan, E Battenberg, J Shor, Y Xiao, ... International conference on machine learning, 5180-5189, 2018 | 962 | 2018 |
| Towards end-to-end prosody transfer for expressive speech synthesis with tacotron RJ Skerry-Ryan, E Battenberg, Y Xiao, Y Wang, D Stanton, J Shor, ... international conference on machine learning, 4693-4702, 2018 | 683 | 2018 |
| Tensorflow distributions JV Dillon, I Langmore, D Tran, E Brevdo, S Vasudevan, D Moore, B Patton, ... arXiv preprint arXiv:1711.10604, 2017 | 638 | 2017 |
| Fixing a broken ELBO A Alemi, B Poole, I Fischer, J Dillon, RA Saurous, K Murphy International conference on machine learning, 159-168, 2018 | 582 | 2018 |
| Regularized least-squares classification R Rifkin, G Yeo, T Poggio Nato Science Series Sub Series III Computer and Systems Sciences 190, 131-154, 2003 | 551 | 2003 |
| Voicefilter: Targeted voice separation by speaker-conditioned spectrogram masking Q Wang, H Muckenhirn, K Wilson, P Sridhar, Z Wu, J Hershey, ... arXiv preprint arXiv:1810.04826, 2018 | 426 | 2018 |
| Molecular classification of multiple tumor types CH Yeang, S Ramaswamy, P Tamayo, S Mukherjee, RM Rifkin, M Angelo, ... ISMB (Supplement of Bioinformatics) 2001, 316-322, 2001 | 395 | 2001 |
| General conditions for predictivity in learning theory T Poggio, R Rifkin, S Mukherjee, P Niyogi Nature 428 (6981), 419-422, 2004 | 374 | 2004 |
| Estimating dataset size requirements for classifying DNA microarray data S Mukherjee, P Tamayo, S Rogers, R Rifkin, A Engle, C Campbell, ... Journal of computational biology 10 (2), 119-142, 2003 | 369 | 2003 |
| Everything old is new again: a fresh look at historical approaches in machine learning RM Rifkin MaSSachuSettS InStitute of Technology, 2002 | 324 | 2002 |
| Learning theory: stability is sufficient for generalization and necessary and sufficient for consistency of empirical risk minimization S Mukherjee, P Niyogi, T Poggio, R Rifkin Advances in Computational Mathematics 25, 161-193, 2006 | 281 | 2006 |
| Deep probabilistic programming D Tran, MD Hoffman, RA Saurous, E Brevdo, K Murphy, DM Blei arXiv preprint arXiv:1701.03757, 2017 | 238 | 2017 |
| Improving multiclass text classification with the support vector machine JDM Rennie, R Rifkin | 227 | 2001 |
Ron J WeissGoogleVerified email at google.com
