Kirthevasan Kandasamy
Kirthevasan Kandasamy
University of California, Berkeley
Verified email at cs.cmu.edu - Homepage
Title
Cited by
Cited by
Year
Neural architecture search with bayesian optimisation and optimal transport
K Kandasamy, W Neiswanger, J Schneider, B Poczos, E Xing
arXiv preprint arXiv:1802.07191, 2018
3022018
High dimensional Bayesian optimisation and bandits via additive models
K Kandasamy, J Schneider, B Póczos
International conference on machine learning, 295-304, 2015
2082015
Parallelised Bayesian Optimisation via Thompson Sampling
K Kandasamy, A Krishnamurthy, J Schneider, B Póczos
International Conference on Artificial Intelligence and Statistics, 133-142, 2018
125*2018
Multi-fidelity bayesian optimisation with continuous approximations
K Kandasamy, G Dasarathy, J Schneider, B Póczos
International Conference on Machine Learning, 1799-1808, 2017
1122017
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
1042016
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
100*2015
Nonparametric estimation of renyi divergence and friends
A Krishnamurthy, K Kandasamy, B Poczos, L Wasserman
International Conference on Machine Learning, 919-927, 2014
752014
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
572020
High dimensional Bayesian optimization via restricted projection pursuit models
CL Li, K Kandasamy, B Póczos, J Schneider
Artificial Intelligence and Statistics, 884-892, 2016
542016
A flexible framework for multi-objective bayesian optimization using random scalarizations
B Paria, K Kandasamy, B Póczos
Uncertainty in Artificial Intelligence, 766-776, 2020
422020
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
382019
Additive approximations in high dimensional nonparametric regression via the SALSA
K Kandasamy, Y Yu
International conference on machine learning, 69-78, 2016
382016
Multi-fidelity black-box optimization with hierarchical partitions
R Sen, K Kandasamy, S Shakkottai
International conference on machine learning, 4538-4547, 2018
322018
Bayesian active learning for posterior estimation
K Kandasamy, J Schneider, B Póczos
Twenty-Fourth International Joint Conference on Artificial Intelligence, 2015
312015
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
292020
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
272017
The multi-fidelity multi-armed bandit
K Kandasamy, G Dasarathy, B Poczos, J Schneider
Advances in neural information processing systems 29, 1777-1785, 2016
232016
Query efficient posterior estimation in scientific experiments via Bayesian active learning
K Kandasamy, J Schneider, B Póczos
Artificial Intelligence 243, 45-56, 2017
212017
Probo: a framework for using probabilistic programming in bayesian optimization
W Neiswanger, K Kandasamy, B Poczos, J Schneider, E Xing
arXiv preprint arXiv:1901.11515 9, 2019
172019
On Estimating L_2^ 2 Divergence
A Krishnamurthy, K Kandasamy, B Poczos, L Wasserman
Artificial Intelligence and Statistics, 498-506, 2015
142015
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Articles 1–20