| A simple but tough-to-beat baseline for sentence embeddings S Arora, Y Liang, T Ma International conference on learning representations, 2017 | 1745 | 2017 |
| Learning and generalization in overparameterized neural networks, going beyond two layers Z Allen-Zhu, Y Li, Y Liang Advances in neural information processing systems 32, 2019 | 894 | 2019 |
| Generalization and equilibrium in generative adversarial nets (gans) S Arora, R Ge, Y Liang, T Ma, Y Zhang International conference on machine learning, 224-232, 2017 | 833 | 2017 |
| Learning overparameterized neural networks via stochastic gradient descent on structured data Y Li, Y Liang Advances in neural information processing systems 31, 2018 | 749 | 2018 |
| A latent variable model approach to pmi-based word embeddings S Arora, Y Li, Y Liang, T Ma, A Risteski Transactions of the Association for Computational Linguistics 4, 385-399, 2016 | 617 | 2016 |
| Learning relationships between text, audio, and video via deep canonical correlation for multimodal language analysis Z Sun, P Sarma, W Sethares, Y Liang Proceedings of the AAAI conference on artificial intelligence 34 (05), 8992-8999, 2020 | 358 | 2020 |
| Linear algebraic structure of word senses, with applications to polysemy S Arora, Y Li, Y Liang, T Ma, A Risteski Transactions of the Association for Computational Linguistics 6, 483-495, 2018 | 284 | 2018 |
| Scalable kernel methods via doubly stochastic gradients B Dai, B Xie, N He, Y Liang, A Raj, MFF Balcan, L Song Advances in neural information processing systems 27, 2014 | 263 | 2014 |
| Distributed -means and -median Clustering on General Topologies MFF Balcan, S Ehrlich, Y Liang Advances in neural information processing systems 26, 2013 | 222 | 2013 |
| N-gram graph: Simple unsupervised representation for graphs, with applications to molecules S Liu, MF Demirel, Y Liang Advances in neural information processing systems 32, 2019 | 218 | 2019 |
| Robust hierarchical clustering MF Balcan, Y Liang, P Gupta The Journal of Machine Learning Research 15 (1), 3831-3871, 2014 | 174 | 2014 |
| Improved distributed principal component analysis Y Liang, MFF Balcan, V Kanchanapally, D Woodruff Advances in neural information processing systems 27, 2014 | 166 | 2014 |
| Atom: Robustifying out-of-distribution detection using outlier mining J Chen, Y Li, X Wu, Y Liang, S Jha Machine Learning and Knowledge Discovery in Databases. Research Track …, 2021 | 159 | 2021 |
| Loss-balanced task weighting to reduce negative transfer in multi-task learning S Liu, Y Liang, A Gitter Proceedings of the AAAI conference on artificial intelligence 33 (01), 9977-9978, 2019 | 157 | 2019 |
| Diverse neural network learns true target functions B Xie, Y Liang, L Song Artificial Intelligence and Statistics, 1216-1224, 2017 | 154* | 2017 |
| A la carte embedding: Cheap but effective induction of semantic feature vectors M Khodak, N Saunshi, Y Liang, T Ma, B Stewart, S Arora arXiv preprint arXiv:1805.05388, 2018 | 130 | 2018 |
| Clustering under perturbation resilience MF Balcan, Y Liang SIAM Journal on Computing 45 (1), 102-155, 2016 | 121 | 2016 |
| Influence function learning in information diffusion networks N Du, Y Liang, M Balcan, L Song International Conference on Machine Learning, 2016-2024, 2014 | 113 | 2014 |
| Differentially private clustering in high-dimensional euclidean spaces MF Balcan, T Dick, Y Liang, W Mou, H Zhang International Conference on Machine Learning, 322-331, 2017 | 104 | 2017 |
| Robust out-of-distribution detection for neural networks J Chen, Y Li, X Wu, Y Liang, S Jha arXiv preprint arXiv:2003.09711, 2020 | 98 | 2020 |
Maria-Florina BalcanProfessor, School of Computer Science, Carnegie Mellon University在 cs.cmu.edu 的电子邮件经过验证
