Stop the war!Остановите войну!
for scientists:
default search action
Google
Google Scholar
Semantic Scholar
Internet Archive Scholar
CiteSeerX
ORCIDSunil Gupta 0001
Sunil Kumar Gupta 0001
Person information
- affiliation: Deakin University, Center for Pattern Recognition and Data Analytics, Australia
Other persons with the same name
- Sunil Gupta — disambiguation page
- Sunil Kumar Gupta 0002
![[0000-0002-7200-9923]](https://dblp.org/img/orcid-mark.12x12.png "0000-0002-7200-9923")
— Beant College of Engineering And Technology, Department of Computer Science, Gurdaspur, India - Sunil Kumar Gupta 0003 — Bioinformatics Centre, Lucknow, India
- Sunil Kumar Gupta 0004 — Indian Institute of Technology (Indian School of Mines), Department of Environmental Science & Engineering, Dhanbad, India
Refine list
refinements active!
zoomed in on ?? of ?? records
view refined list in
export refined list as
showing all ?? records
2020 – today
- 2023
[j33]Thommen George Karimpanal, Hung Le, Majid Abdolshah, Santu Rana, Sunil Gupta, Truyen Tran, Svetha Venkatesh:
Balanced Q-learning: Combining the influence of optimistic and pessimistic targets. Artif. Intell. 325: 104021 (2023)- [j32]Dat Phan-Trong, Hung Tran-The, Sunil Gupta:
NeuralBO: A black-box optimization algorithm using deep neural networks. Neurocomputing 559: 126776 (2023) - [c100]Thanh Nguyen-Tang, Ming Yin, Sunil Gupta, Svetha Venkatesh, Raman Arora:
On Instance-Dependent Bounds for Offline Reinforcement Learning with Linear Function Approximation. AAAI 2023: 9310-9318 - [c99]Alistair Shilton, Sunil Gupta, Santu Rana, Svetha Venkatesh:
Gradient Descent in Neural Networks as Sequential Learning in Reproducing Kernel Banach Space. ICML 2023: 31435-31488 - [c98]Dupati Srikar Chandra, Sakshi Varshney, P. K. Srijith, Sunil Gupta:
Continual Learning with Dependency Preserving Hypernetworks. WACV 2023: 2338-2347 - [c97]Thao Minh Le, Vuong Le, Sunil Gupta, Svetha Venkatesh, Truyen Tran:
Guiding Visual Question Answering with Attention Priors. WACV 2023: 4370-4379 - [i54]Alistair Shilton, Sunil Gupta, Santu Rana, Svetha Venkatesh:
Gradient Descent in Neural Networks as Sequential Learning in RKBS. CoRR abs/2302.00205 (2023) - [i53]Dat Phan-Trong, Hung Tran-The, Sunil Gupta:
Neural-BO: A Black-box Optimization Algorithm using Deep Neural Networks. CoRR abs/2303.01682 (2023) - [i52]Sunil Gupta, Alistair Shilton, Arun Kumar A. V., Shannon Ryan, Majid Abdolshah, Hung Le, Santu Rana, Julian Berk, Mahad Rashid, Svetha Venkatesh:
BO-Muse: A human expert and AI teaming framework for accelerated experimental design. CoRR abs/2303.01684 (2023) - [i51]Manisha Senadeera, Thommen Karimpanal George, Sunil Gupta, Stephan Jacobs, Santu Rana:
EMOTE: An Explainable architecture for Modelling the Other Through Empathy. CoRR abs/2306.00295 (2023) - [i50]Manisha Senadeera, Santu Rana, Sunil Gupta, Svetha Venkatesh:
Predictive Modeling through Hyper-Bayesian Optimization. CoRR abs/2308.00285 (2023) - [i49]Thommen George Karimpanal, Buddhika Laknath Semage, Santu Rana, Hung Le, Truyen Tran, Sunil Gupta, Svetha Venkatesh:
LaGR-SEQ: Language-Guided Reinforcement Learning with Sample-Efficient Querying. CoRR abs/2308.13542 (2023) - 2022
- [j31]Haripriya Harikumar, Santu Rana, Sunil Gupta, Thin Nguyen, Ramachandra Kaimal, Svetha Venkatesh:
Prescriptive analytics with differential privacy. Int. J. Data Sci. Anal. 13(2): 123-138 (2022) - [j30]Deepthi Praveenlal Kuttichira, Sunil Gupta, Dang Nguyen, Santu Rana, Svetha Venkatesh:
Verification of integrity of deployed deep learning models using Bayesian Optimization. Knowl. Based Syst. 241: 108238 (2022) - [j29]Prashant W. Patil, Sunil Gupta, Santu Rana, Svetha Venkatesh:
Dual-frame spatio-temporal feature modulation for video enhancement. Pattern Recognit. 130: 108822 (2022) - [j28]Thanh Nguyen-Tang, Sunil Gupta, Hung Tran-The, Svetha Venkatesh:
On Sample Complexity of Offline Reinforcement Learning with Deep ReLU Networks in Besov Spaces. Trans. Mach. Learn. Res. 2022 (2022) - [c96]Alistair Shilton, Sunil Gupta, Santu Rana, Arun Kumar Anjanapura Venkatesh, Svetha Venkatesh:
TRF: Learning Kernels with Tuned Random Features. AAAI 2022: 8286-8294 - [c95]Hung Tran-The, Sunil Gupta, Santu Rana, Svetha Venkatesh:
Regret Bounds for Expected Improvement Algorithms in Gaussian Process Bandit Optimization. AISTATS 2022: 8715-8737 - [c94]Manisha Senadeera, Thommen George Karimpanal, Sunil Gupta, Santu Rana:
Sympathy-based Reinforcement Learning Agents. AAMAS 2022: 1164-1172 - [c93]Prashant W. Patil, Sunil Gupta, Santu Rana, Svetha Venkatesh:
Video Restoration Framework and Its Meta-adaptations to Data-Poor Conditions. ECCV (28) 2022: 143-160 - [c92]Dang Nguyen, Sunil Gupta, Kien Do, Svetha Venkatesh:
Black-Box Few-Shot Knowledge Distillation. ECCV (21) 2022: 196-211 - [c91]Thanh Nguyen-Tang, Sunil Gupta, A. Tuan Nguyen, Svetha Venkatesh:
Offline Neural Contextual Bandits: Pessimism, Optimization and Generalization. ICLR 2022 - [c90]Stewart Greenhill, Majid Abdolshah, Vuong Le, Sunil Gupta, Svetha Venkatesh:
Semantic Control of Generative Musical Attributes. ISMIR 2022: 817-824 - [c89]Thai Hung Le, Thommen Karimpanal George, Majid Abdolshah, Dung Nguyen, Kien Do, Sunil Gupta, Svetha Venkatesh:
Learning to Constrain Policy Optimization with Virtual Trust Region. NeurIPS 2022 - [c88]Hung Tran-The, Sunil Gupta, Santu Rana, Tuan Truong, Long Tran-Thanh, Svetha Venkatesh:
Expected Improvement for Contextual Bandits. NeurIPS 2022 - [c87]Preeti Gopal, Sunil Gupta, Santu Rana, Vuong Le, Trong Nguyen, Svetha Venkatesh:
Real-Time Skill Discovery in Intelligent Virtual Assistants. PAKDD (1) 2022: 315-327 - [i48]Hung Tran-The, Sunil Gupta, Santu Rana, Svetha Venkatesh:
Regret Bounds for Expected Improvement Algorithms in Gaussian Process Bandit Optimization. CoRR abs/2203.07875 (2022) - [i47]Hung Le, Thommen George Karimpanal, Majid Abdolshah, Dung Nguyen, Kien Do, Sunil Gupta, Svetha Venkatesh:
Memory-Constrained Policy Optimization. CoRR abs/2204.09315 (2022) - [i46]Phuoc Nguyen, Truyen Tran, Ky Le, Sunil Gupta, Santu Rana, Dang Nguyen, Trong Nguyen, Shannon Ryan, Svetha Venkatesh:
Fast Conditional Network Compression Using Bayesian HyperNetworks. CoRR abs/2205.06404 (2022) - [i45]Thao Minh Le, Vuong Le, Sunil Gupta, Svetha Venkatesh, Truyen Tran:
Guiding Visual Question Answering with Attention Priors. CoRR abs/2205.12616 (2022) - [i44]Haripriya Harikumar, Santu Rana, Kien Do, Sunil Gupta, Wei Zong, Willy Susilo, Svetha Venkatesh:
Defense Against Multi-target Trojan Attacks. CoRR abs/2207.03895 (2022) - [i43]Dang Nguyen, Sunil Gupta, Kien Do, Svetha Venkatesh:
Black-box Few-shot Knowledge Distillation. CoRR abs/2207.12106 (2022) - [i42]Dupati Srikar Chandra, Sakshi Varshney, P. K. Srijith, Sunil Gupta:
Continual Learning with Dependency Preserving Hypernetworks. CoRR abs/2209.07712 (2022) - [i41]Thanh Nguyen-Tang, Ming Yin, Sunil Gupta, Svetha Venkatesh, Raman Arora:
On Instance-Dependent Bounds for Offline Reinforcement Learning with Linear Function Approximation. CoRR abs/2211.13208 (2022) - 2021
- [j27]Haripriya Harikumar, Thomas P. Quinn, Santu Rana, Sunil Gupta, Svetha Venkatesh:
Personalized single-cell networks: a framework to predict the response of any gene to any drug for any patient. BioData Min. 14(1) (2021) - [j26]Dang Nguyen, Sunil Gupta, Santu Rana, Alistair Shilton, Svetha Venkatesh:
Fairness improvement for black-box classifiers with Gaussian process. Inf. Sci. 576: 542-556 (2021) - [j25]Phuc Luong, Dang Nguyen, Sunil Gupta, Santu Rana, Svetha Venkatesh:
Adaptive cost-aware Bayesian optimization. Knowl. Based Syst. 232: 107481 (2021) - [j24]Prashant W. Patil, Akshay Dudhane, Ashutosh Kulkarni, Subrahmanyam Murala, Anil Balaji Gonde, Sunil Gupta:
An Unified Recurrent Video Object Segmentation Framework for Various Surveillance Environments. IEEE Trans. Image Process. 30: 7889-7902 (2021) - [c86]Thanh Nguyen-Tang, Sunil Gupta, Svetha Venkatesh:
Distributional Reinforcement Learning via Moment Matching. AAAI 2021: 9144-9152 - [c85]Huong Ha, Sunil Gupta, Santu Rana, Svetha Venkatesh:
High Dimensional Level Set Estimation with Bayesian Neural Network. AAAI 2021: 12095-12103 - [c84]Majid Abdolshah, Hung Le, Thommen George Karimpanal, Sunil Gupta, Santu Rana, Svetha Venkatesh:
A New Representation of Successor Features for Transfer across Dissimilar Environments. ICML 2021: 1-9 - [c83]Hung Tran-The, Sunil Gupta, Santu Rana, Svetha Venkatesh:
Bayesian Optimistic Optimisation with Exponentially Decaying Regret. ICML 2021: 10390-10400 - [c82]Arun Kumar Anjanapura Venkatesh, Alistair Shilton, Santu Rana, Sunil Gupta, Svetha Venkatesh:
Kernel Functional Optimisation. NeurIPS 2021: 4725-4737 - [c81]Ang Yang, Cheng Li, Santu Rana, Sunil Gupta, Svetha Venkatesh:
Sparse Spectrum Gaussian Process for Bayesian Optimization. PAKDD (2) 2021: 257-268 - [c80]Phuoc Nguyen, Truyen Tran, Sunil Gupta, Santu Rana, Hieu-Chi Dam, Svetha Venkatesh:
Variational Hyper-encoding Networks. ECML/PKDD (2) 2021: 100-115 - [c79]Dang Nguyen, Sunil Gupta, Trong Nguyen, Santu Rana, Phuoc Nguyen, Truyen Tran, Ky Le, Shannon Ryan, Svetha Venkatesh:
Knowledge Distillation with Distribution Mismatch. ECML/PKDD (2) 2021: 250-265 - [c78]Phuoc Nguyen, Truyen Tran, Ky Le, Sunil Gupta, Santu Rana, Dang Nguyen, Trong Nguyen, Shannon Ryan, Svetha Venkatesh:
Fast Conditional Network Compression Using Bayesian HyperNetworks. ECML/PKDD (3) 2021: 330-345 - [i40]Thanh Nguyen-Tang, Sunil Gupta, Hung Tran-The, Svetha Venkatesh:
On Finite-Sample Analysis of Offline Reinforcement Learning with Deep ReLU Networks. CoRR abs/2103.06671 (2021) - [i39]Huong Ha, Sunil Gupta, Santu Rana, Svetha Venkatesh:
ALT-MAS: A Data-Efficient Framework for Active Testing of Machine Learning Algorithms. CoRR abs/2104.04999 (2021) - [i38]Hung Tran-The, Sunil Gupta, Santu Rana, Svetha Venkatesh:
Bayesian Optimistic Optimisation with Exponentially Decaying Regret. CoRR abs/2105.04332 (2021) - [i37]Majid Abdolshah, Hung Le, Thommen George Karimpanal, Sunil Gupta, Santu Rana, Svetha Venkatesh:
A New Representation of Successor Features for Transfer across Dissimilar Environments. CoRR abs/2107.08426 (2021) - [i36]Hung Tran-The, Sunil Gupta, Thanh Nguyen-Tang, Santu Rana, Svetha Venkatesh:
Combining Online Learning and Offline Learning for Contextual Bandits with Deficient Support. CoRR abs/2107.11533 (2021) - [i35]Majid Abdolshah, Hung Le, Thommen George Karimpanal, Sunil Gupta, Santu Rana, Svetha Venkatesh:
Plug and Play, Model-Based Reinforcement Learning. CoRR abs/2108.08960 (2021) - [i34]Thomas P. Quinn, Sunil Gupta, Svetha Venkatesh, Vuong Le:
A Field Guide to Scientific XAI: Transparent and Interpretable Deep Learning for Bioinformatics Research. CoRR abs/2110.08253 (2021) - [i33]Haripriya Harikumar, Kien Do, Santu Rana, Sunil Gupta, Svetha Venkatesh:
Semantic Host-free Trojan Attack. CoRR abs/2110.13414 (2021) - [i32]Thommen George Karimpanal, Hung Le, Majid Abdolshah, Santu Rana, Sunil Gupta, Truyen Tran, Svetha Venkatesh:
Balanced Q-learning: Combining the Influence of Optimistic and Pessimistic Targets. CoRR abs/2111.02787 (2021) - [i31]Thanh Nguyen-Tang, Sunil Gupta, A. Tuan Nguyen, Svetha Venkatesh:
Offline Neural Contextual Bandits: Pessimism, Optimization and Generalization. CoRR abs/2111.13807 (2021) - 2020
- [j23]Stewart Greenhill, Santu Rana, Sunil Gupta, Pratibha Vellanki, Svetha Venkatesh:
Bayesian Optimization for Adaptive Experimental Design: A Review. IEEE Access 8: 13937-13948 (2020) - [j22]Tinu Theckel Joy, Santu Rana, Sunil Gupta, Svetha Venkatesh:
Batch Bayesian optimization using multi-scale search. Knowl. Based Syst. 187 (2020) - [j21]Julian Berk, Sunil Gupta, Santu Rana, Vu Nguyen, Svetha Venkatesh:
Bayesian optimisation in unknown bounded search domains. Knowl. Based Syst. 195: 105645 (2020) - [j20]Anil Ramachandran, Sunil Gupta, Santu Rana, Cheng Li, Svetha Venkatesh:
Incorporating expert prior in Bayesian optimisation via space warping. Knowl. Based Syst. 195: 105663 (2020) - [j19]Tinu Theckel Joy, Santu Rana, Sunil Gupta, Svetha Venkatesh:
Fast hyperparameter tuning using Bayesian optimization with directional derivatives. Knowl. Based Syst. 205: 106247 (2020) - [j18]Steven Allender, Joshua Hayward, Sunil Gupta, A. Sanigorski, Santu Rana, Hugh Seward, Stephan Jacobs, Svetha Venkatesh:
Bayesian strategy selection identifies optimal solutions to complex problems using an example from GP prescribing. npj Digit. Medicine 3 (2020) - [c77]Hung Tran-The, Sunil Gupta, Santu Rana, Svetha Venkatesh:
Trading Convergence Rate with Computational Budget in High Dimensional Bayesian Optimization. AAAI 2020: 2425-2432 - [c76]Dang Nguyen, Sunil Gupta, Santu Rana, Alistair Shilton, Svetha Venkatesh:
Bayesian Optimization for Categorical and Category-Specific Continuous Inputs. AAAI 2020: 5256-5263 - [c75]Alistair Shilton, Sunil Gupta, Santu Rana, Pratibha Vellanki, Cheng Li, Svetha Venkatesh, Laurence Park, Alessandra Sutti, David Rubin, Thomas Dorin, Alireza Vahid, Murray Height, Teo Slezak:
Accelerated Bayesian Optimisation through Weight-Prior Tuning. AISTATS 2020: 635-645 - [c74]Thanh Tang Nguyen, Sunil Gupta, Huong Ha, Santu Rana, Svetha Venkatesh:
Distributionally Robust Bayesian Quadrature Optimization. AISTATS 2020: 1921-1931 - [c73]Thomas P. Quinn, Dang Nguyen, Santu Rana, Sunil Gupta, Svetha Venkatesh:
DeepCoDA: personalized interpretability for compositional health data. ICML 2020: 7877-7886 - [c72]Cheng Li, Santu Rana, Andrew Gill, Dang Nguyen, Sunil Gupta, Svetha Venkatesh:
Factor Screening using Bayesian Active Learning and Gaussian Process Meta-Modelling. ICPR 2020: 3288-3295 - [c71]Julian Berk, Sunil Gupta, Santu Rana, Svetha Venkatesh:
Randomised Gaussian Process Upper Confidence Bound for Bayesian Optimisation. IJCAI 2020: 2284-2290 - [c70]Thommen George Karimpanal, Santu Rana, Sunil Gupta, Truyen Tran, Svetha Venkatesh:
Learning Transferable Domain Priors for Safe Exploration in Reinforcement Learning. IJCNN 2020: 1-10 - [c69]Hung Tran-The, Sunil Gupta, Santu Rana, Huong Ha, Svetha Venkatesh:
Sub-linear Regret Bounds for Bayesian Optimisation in Unknown Search Spaces. NeurIPS 2020 - [c68]Manisha Senadeera, Santu Rana, Sunil Gupta, Svetha Venkatesh:
Level Set Estimation with Search Space Warping. PAKDD (2) 2020: 827-839 - [c67]Haripriya Harikumar, Vuong Le, Santu Rana, Sourangshu Bhattacharya, Sunil Gupta, Svetha Venkatesh:
Scalable Backdoor Detection in Neural Networks. ECML/PKDD (2) 2020: 289-304 - [c66]Phuc Luong, Dang Nguyen, Sunil Gupta, Santu Rana, Svetha Venkatesh:
Bayesian Optimization with Missing Inputs. ECML/PKDD (2) 2020: 691-706 - [c65]Duc Nguyen, Phuoc Nguyen, Kien Do, Santu Rana, Sunil Gupta, Truyen Tran:
Unsupervised Anomaly Detection on Temporal Multiway Data. SSCI 2020: 1059-1066 - [i30]Thanh Tang Nguyen, Sunil Gupta, Huong Ha, Santu Rana, Svetha Venkatesh:
Distributionally Robust Bayesian Quadrature Optimization. CoRR abs/2001.06814 (2020) - [i29]Cheng Li, Sunil Gupta, Santu Rana, Vu Nguyen, Antonio Robles-Kelly, Svetha Venkatesh:
Incorporating Expert Prior Knowledge into Experimental Design via Posterior Sampling. CoRR abs/2002.11256 (2020) - [i28]Anil Ramachandran, Sunil Gupta, Santu Rana, Cheng Li, Svetha Venkatesh:
Incorporating Expert Prior in Bayesian Optimisation via Space Warping. CoRR abs/2003.12250 (2020) - [i27]Phuoc Nguyen, Truyen Tran, Sunil Gupta, Santu Rana, Hieu-Chi Dam, Svetha Venkatesh:
HyperVAE: A Minimum Description Length Variational Hyper-Encoding Network. CoRR abs/2005.08482 (2020) - [i26]Thomas P. Quinn, Dang Nguyen, Santu Rana, Sunil Gupta, Svetha Venkatesh:
DeepCoDA: personalized interpretability for compositional health data. CoRR abs/2006.01392 (2020) - [i25]Julian Berk, Sunil Gupta, Santu Rana, Svetha Venkatesh:
Randomised Gaussian Process Upper Confidence Bound for Bayesian Optimisation. CoRR abs/2006.04296 (2020) - [i24]Haripriya Harikumar, Vuong Le, Santu Rana, Sourangshu Bhattacharya, Sunil Gupta, Svetha Venkatesh:
Scalable Backdoor Detection in Neural Networks. CoRR abs/2006.05646 (2020) - [i23]Phuc Luong, Dang Nguyen, Sunil Gupta, Santu Rana, Svetha Venkatesh:
Bayesian Optimization with Missing Inputs. CoRR abs/2006.10948 (2020) - [i22]Thanh Tang Nguyen, Sunil Gupta, Svetha Venkatesh:
Distributional Reinforcement Learning with Maximum Mean Discrepancy. CoRR abs/2007.12354 (2020) - [i21]Hung Tran-The, Sunil Gupta, Santu Rana, Huong Ha, Svetha Venkatesh:
Sub-linear Regret Bounds for Bayesian Optimisation in Unknown Search Spaces. CoRR abs/2009.02539 (2020) - [i20]Alistair Shilton, Sunil Gupta, Santu Rana, Svetha Venkatesh:
Sequential Subspace Search for Functional Bayesian Optimization Incorporating Experimenter Intuition. CoRR abs/2009.03543 (2020) - [i19]Duc Nguyen, Phuoc Nguyen, Kien Do, Santu Rana, Sunil Gupta, Truyen Tran:
Unsupervised Anomaly Detection on Temporal Multiway Data. CoRR abs/2009.09443 (2020) - [i18]Anh-Cat Le-Ngo, Truyen Tran, Santu Rana, Sunil Gupta, Svetha Venkatesh:
Logically Consistent Loss for Visual Question Answering. CoRR abs/2011.10094 (2020) - [i17]Huong Ha, Sunil Gupta, Santu Rana, Svetha Venkatesh:
High Dimensional Level Set Estimation with Bayesian Neural Network. CoRR abs/2012.09973 (2020)
2010 – 2019
- 2019
- [j17]Tinu Theckel Joy, Santu Rana, Sunil Gupta, Svetha Venkatesh:
A flexible transfer learning framework for Bayesian optimization with convergence guarantee. Expert Syst. Appl. 115: 656-672 (2019) - [j16]Vu Nguyen, Sunil Gupta, Santu Rana, Cheng Li, Svetha Venkatesh:
Filtering Bayesian optimization approach in weakly specified search space. Knowl. Inf. Syst. 60(1): 385-413 (2019) - [c64]Pratibha Vellanki, Santu Rana, Sunil Gupta, David Rubin de Celis Leal, Alessandra Sutti, Murray Height, Svetha Venkatesh:
Bayesian Functional Optimisation with Shape Prior. AAAI 2019: 1617-1624 - [c63]A. V. Arun Kumar, Santu Rana, Cheng Li, Sunil Gupta, Alistair Shilton, Svetha Venkatesh:
Bayesian Optimisation for Objective Functions with Varying Smoothness. Australasian Conference on Artificial Intelligence 2019: 460-472 - [c62]Phuc Luong, Sunil Gupta, Dang Nguyen, Santu Rana, Svetha Venkatesh:
Bayesian Optimization with Discrete Variables. Australasian Conference on Artificial Intelligence 2019: 473-484 - [c61]Deepthi Praveenlal Kuttichira, Sunil Gupta, Dang Nguyen, Santu Rana, Svetha Venkatesh:
Detection of Compromised Models Using Bayesian Optimization. Australasian Conference on Artificial Intelligence 2019: 485-496 - [c60]Anil Ramachandran, Sunil Gupta, Santu Rana, Svetha Venkatesh:
Information-Theoretic Multi-task Learning Framework for Bayesian Optimisation. Australasian Conference on Artificial Intelligence 2019: 497-509 - [c59]Vu Nguyen, Sunil Gupta, Santu Rana, My T. Thai, Cheng Li, Svetha Venkatesh:
Efficient Bayesian Optimization for Uncertainty Reduction Over Perceived Optima Locations. ICDM 2019: 1270-1275 - [c58]Huong Ha, Santu Rana, Sunil Gupta, Thanh Tang Nguyen, Hung Tran-The, Svetha Venkatesh:
Bayesian Optimization with Unknown Search Space. NeurIPS 2019: 11772-11781 - [c57]Majid Abdolshah, Alistair Shilton, Santu Rana, Sunil Gupta, Svetha Venkatesh:
Multi-objective Bayesian optimisation with preferences over objectives. NeurIPS 2019: 12214-12224 - [c56]Deepthi Praveenlal Kuttichira, Sunil Gupta, Cheng Li, Santu Rana, Svetha Venkatesh:
Explaining Black-Box Models Using Interpretable Surrogates. PRICAI (1) 2019: 3-15 - [c55]Phuoc Nguyen, Truyen Tran, Sunil Gupta, Santu Rana, Matthew Barnett, Svetha Venkatesh:
Incomplete Conditional Density Estimation for Fast Materials Discovery. SDM 2019: 549-557 - [i16]Tinu Theckel Joy, Santu Rana, Sunil Gupta, Svetha Venkatesh:
Fast Hyperparameter Tuning using Bayesian Optimization with Directional Derivatives. CoRR abs/1902.02416 (2019) - [i15]Majid Abdolshah, Alistair Shilton, Santu Rana, Sunil Gupta, Svetha Venkatesh:
Multi-objective Bayesian optimisation with preferences over objectives. CoRR abs/1902.04228 (2019) - [i14]Alistair Shilton, Sunil Gupta, Santu Rana, Svetha Venkatesh, Majid Abdolshah, Dang Nguyen:
Stable Bayesian Optimisation via Direct Stability Quantification. CoRR abs/1902.07846 (2019) - [i13]Ang Yang, Cheng Li, Santu Rana, Sunil Gupta, Svetha Venkatesh:
Sparse Spectrum Gaussian Process for Bayesian Optimisation. CoRR abs/1906.08898 (2019) - [i12]Cheng Li, Santu Rana, Sunil Gupta, Vu Nguyen, Svetha Venkatesh, Alessandra Sutti, David Rubin de Celis Leal, Teo Slezak, Murray Height, Mazher Mohammed, Ian Gibson:
Accelerating Experimental Design by Incorporating Experimenter Hunches. CoRR abs/1907.09065 (2019) - [i11]Majid Abdolshah, Alistair Shilton, Santu Rana, Sunil Gupta, Svetha Venkatesh:
Cost-aware Multi-objective Bayesian optimisation. CoRR abs/1909.03600 (2019) - [i10]Thommen George Karimpanal, Santu Rana, Sunil Gupta, Truyen Tran, Svetha Venkatesh:
Learning Transferable Domain Priors for Safe Exploration in Reinforcement Learning. CoRR abs/1909.04307 (2019) - [i9]Huong Ha, Santu Rana, Sunil Gupta, Thanh Tang Nguyen, Hung Tran-The, Svetha Venkatesh:
Bayesian Optimization with Unknown Search Space. CoRR abs/1910.13092 (2019) - [i8]Hung Tran-The, Sunil Gupta, Santu Rana, Svetha Venkatesh:
Trading Convergence Rate with Computational Budget in High Dimensional Bayesian Optimization. CoRR abs/1911.11950 (2019) - [i7]Dang Nguyen, Sunil Gupta, Santu Rana, Alistair Shilton, Svetha Venkatesh:
Bayesian Optimization for Categorical and Category-Specific Continuous Inputs. CoRR abs/1911.12473 (2019) - 2018
- [j15]Thanh Dai Nguyen, Sunil Gupta, Santu Rana, Svetha Venkatesh:
Stable Bayesian optimization. Int. J. Data Sci. Anal. 6(4): 327-339 (2018) - [c54]Sunil Gupta, Alistair Shilton, Santu Rana, Svetha Venkatesh:
Exploiting Strategy-Space Diversity for Batch Bayesian Optimization. AISTATS 2018: 538-547 - [c53]Ang Yang, Cheng Li, Santu Rana, Sunil Gupta, Svetha Venkatesh:
Sparse Approximation for Gaussian Process with Derivative Observations. Australasian Conference on Artificial Intelligence 2018: 507-518 - [c52]Cheng Li, Santu Rana, Sunil Gupta, Vu Nguyen, Svetha Venkatesh, Alessandra Sutti, David Rubin de Celis Leal, Teo Slezak, Murray Height, Mazher Mohammed, Ian Gibson:
Accelerating Experimental Design by Incorporating Experimenter Hunches. ICDM 2018: 257-266 - [c51]Haripriya Harikumar, Santu Rana, Sunil Gupta, Thin Nguyen, Ramachandra Kaimal, Svetha Venkatesh:
Differentially Private Prescriptive Analytics. ICDM 2018: 995-1000 - [c50]Majid Abdolshah, Alistair Shilton, Santu Rana, Sunil Gupta, Svetha Venkatesh:
Expected Hypervolume Improvement with Constraints. ICPR 2018: 3238-3243 - [c49]