| Neural architecture search with bayesian optimisation and optimal transport K Kandasamy, W Neiswanger, J Schneider, B Poczos, EP Xing Advances in neural information processing systems 31, 2018 | 670 | 2018 |
| High dimensional Bayesian optimisation and bandits via additive models K Kandasamy, J Schneider, B Póczos International conference on machine learning, 295-304, 2015 | 402 | 2015 |
| Parallelised Bayesian Optimisation via Thompson Sampling K Kandasamy, A Krishnamurthy, J Schneider, B Póczos International Conference on Artificial Intelligence and Statistics, 133-142, 2018 | 296* | 2018 |
| Multi-fidelity bayesian optimisation with continuous approximations K Kandasamy, G Dasarathy, J Schneider, B Póczos International conference on machine learning, 1799-1808, 2017 | 244 | 2017 |
| Tuning hyperparameters without grad students: Scalable and robust bayesian optimisation with dragonfly K Kandasamy, KR Vysyaraju, W Neiswanger, B Paria, CR Collins, ... Journal of Machine Learning Research 21 (81), 1-27, 2020 | 211 | 2020 |
| Gaussian process optimisation with multi-fidelity evaluations K Kandasamy, G Dasarathy, J Oliva, J Schneider, B Póczos Proceedings of the 30th/International Conference on Advances in Neural …, 2016 | 189* | 2016 |
| A flexible framework for multi-objective bayesian optimization using random scalarizations B Paria, K Kandasamy, B Póczos Uncertainty in Artificial Intelligence, 766-776, 2020 | 161 | 2020 |
| Autonomous discovery of battery electrolytes with robotic experimentation and machine learning A Dave, J Mitchell, K Kandasamy, H Wang, S Burke, B Paria, B Póczos, ... Cell Reports Physical Science 1 (12), 2020 | 147 | 2020 |
| Nonparametric von mises estimators for entropies, divergences and mutual informations K Kandasamy, A Krishnamurthy, B Poczos, L Wasserman Advances in Neural Information Processing Systems, 397-405, 2015 | 140* | 2015 |
| Chembo: Bayesian optimization of small organic molecules with synthesizable recommendations K Korovina, S Xu, K Kandasamy, W Neiswanger, B Poczos, J Schneider, ... International Conference on Artificial Intelligence and Statistics, 3393-3403, 2020 | 131 | 2020 |
| Nonparametric estimation of renyi divergence and friends A Krishnamurthy, K Kandasamy, B Poczos, L Wasserman International Conference on Machine Learning, 919-927, 2014 | 99 | 2014 |
| High dimensional Bayesian optimization via restricted projection pursuit models CL Li, K Kandasamy, B Póczos, J Schneider Artificial Intelligence and Statistics, 884-892, 2016 | 94 | 2016 |
| Multi-fidelity gaussian process bandit optimisation K Kandasamy, G Dasarathy, J Oliva, J Schneider, B Poczos Journal of Artificial Intelligence Research 66, 151-196, 2019 | 92 | 2019 |
| Multi-fidelity black-box optimization with hierarchical partitions R Sen, K Kandasamy, S Shakkottai International conference on machine learning, 4538-4547, 2018 | 58 | 2018 |
| Additive approximations in high dimensional nonparametric regression via the SALSA K Kandasamy, Y Yu International conference on machine learning, 69-78, 2016 | 47 | 2016 |
| Bayesian active learning for posterior estimation K Kandasamy, J Schneider, B Póczos Twenty-Fourth International Joint Conference on Artificial Intelligence, 2015 | 44 | 2015 |
| Offline contextual bayesian optimization I Char, Y Chung, W Neiswanger, K Kandasamy, AO Nelson, M Boyer, ... Advances in Neural Information Processing Systems 32, 2019 | 41 | 2019 |
| The multi-fidelity multi-armed bandit K Kandasamy, G Dasarathy, B Poczos, J Schneider Advances in neural information processing systems 29, 2016 | 38 | 2016 |
| Query efficient posterior estimation in scientific experiments via Bayesian active learning K Kandasamy, J Schneider, B Póczos Artificial Intelligence 243, 45-56, 2017 | 37 | 2017 |
| Batch Policy Gradient Methods for Improving Neural Conversation Models K Kandasamy, Y Bachrach, R Tomioka, D Tarlow, D Carter International Conference on Learning Representations, 2017 | 36 | 2017 |
Barnabas PoczosAssociate professor, Carnegie Mellon University在 cs.cmu.edu 的电子邮件经过验证
