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Results for: Sunil Gupta

Explaining Black-box Machine Learning Models using Interpretable Surrogates

D. Kuttichira, S. Gupta, R. Santu, C. Li, S. Venkatesh

2019 / pp. (to appear) / Pacific Rim International Conference on Artificial Intelligence

Bayesian functional optimisation with shape prior

P. Vellanki, S. Rana, S. Gupta, D. Leal, A. Sutti, M. Height, S. Venkatesh

2019 / pp. (Accepted 1 Nov 2018) / The AAAI Conference on Artificial Intelligence (AAAI)

A flexible transfer learning framework for Bayesian optimization with convergence guarantee

T. Joy, S. Rana, S. Gupta, S. Venkatesh

2019 / Vol. 115, pp. 656 - 672 / Expert Systems with Applications

Multi-Target Optimisation via Bayesian Optimisation and Linear Programming

A. Shilton, S. Rana, S. Gupta, S. Venkatesh

2018 / UAI 2018: Proceedings of the 34th Conference on Uncertainty in Artificial Intelligence

Differentially Private Prescriptive Analytics

H. Harikumar, S. Rana, S. Gupta, T. Nguyen, R. Kaimal, S. Venkatesh

2018 / pp. 995 - 1000 / 2018 IEEE International Conference on Data Mining (ICDM)

Accelerating Experimental Design by Incorporating Experimenter Hunches.

C. Li, S. Rana, S. Gupta, V. Nguyen, S. Venkatesh, A. Sutti, C. de, T. Slezak, M. Height, M. Mohammed, O.

2018 / pp. 257 - 266 / 2018 IEEE International Conference on Data Mining (ICDM)

Expected Hypervolume Improvement with Constraints

M. Abdolshah, A. Shilton, S. Rana, S. Gupta, S. Venkatesh

2018 / pp. 3238 - 3243 / International Conference on Pattern Recognition (ICPR)

Information-theoretic Transfer Learning framework for Bayesian Optimisation

A. Ramachandran, S. Gupta, R. Santu, S. Venkatesh

2018 / pp. 827 - 842 / The European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD)

Filtering Bayesian optimization approach in weakly specified search space

V. Nguyen, S. Gupta, S. Rana, C. Li, S. Venkatesh

2018 / pp. 1 - 29 / Knowledge and Information Systems

Microstructure and mechanical properties of new recycled high performance 7xxx-series alloys

A. Vahid, S. Rana, S. Gupta, P. Vellanki, S. Venkatesh, T. Dorin

2018 / Materials Science and Engineering: A - Journal - Elsevier (under review)

Efficient Bayesian Optimisation Using Derivative Meta-Model

A. Yang, C. Li, S. Rana, S. Gupta, S. Venkatesh

2018 / pp. 252 - 264 / The 15th Pacific Rim International Conference on Artificial Intelligence

Sparse Approximation for {Gaussian} Process with Derivative Observations

A. Yang, C. Li, S. Rana, S. Gupta, S. Venkatesh

2018 / Australasian AI

Exploration Enhanced Expected Improvement for Bayesian Optimization

J. Berk, V. Nguyen, S. Gupta, R. Santu, S. Venkatesh

2018 / pp. 621 - 637 / The European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD)

A Privacy Preserving Bayesian Optimization with High Efficiency

N. Dai, S. Gupta, S. Rana, S. Venkatesh

2018 / pp. 543 - 555 / Pacific-Asia Conference on Knowledge Discovery and Data Mining

Stable bayesian optimization

N. Dai, S. Gupta, S. Rana, S. Venkatesh

2018 / Vol. 6, pp. 327 - 339 / International Journal of Data Science and Analytics

New Bayesian-Optimization-Based Design of High-Strength 7xxx-Series Alloys from Recycled Aluminum

A. Vahid, S. Rana, S. Gupta, P. Vellanki, S. Venkatesh, T. Dorin

2018 / Vol. 70, pp. 2704 - 2709 / The Journal of The Minerals, Metals and Materials Society (JOM)

Selecting Optimal Source for Transfer Learning in Bayesian Optimisation

A. Ramachandran, S. Gupta, R. Santu, S. Venkatesh

2018 / pp. 42 - 56 / The 15th Pacific Rim International Conference on Artificial Intelligence

Distance Exploration for Scalable Batch Bayesian Optimization

V. Nguyen, S. Gupta, S. Rana, C. Li, S. Venkatesh

2017 / 31st Conference on Neural Information Processing Systems