Sunil Gupta

ORCID

Publication Activity (10 Years)

Years Active: 2013-2024
Publications (10 Years): 168

Top Venues

Publications

A. V. Arun Kumar, Alistair Shilton, Sunil Gupta, Santu Rana, Stewart Greenhill, Svetha Venkatesh
Enhanced Bayesian Optimization via Preferential Modeling of Abstract Properties. CoRR (2024)
Tuan Hoang, Santu Rana, Sunil Gupta, Svetha Venkatesh
Learn to Unlearn for Deep Neural Networks: Minimizing Unlearning Interference with Gradient Projection. WACV (2024)
Linh Le Pham Van, Hung The Tran, Sunil Gupta
Policy Learning for Off-Dynamics RL with Deficient Support. CoRR (2024)
Phuoc Nguyen, Truyen Tran, Sunil Gupta, Thin Nguyen, Svetha Venkatesh
Root Cause Explanation of Outliers under Noisy Mechanisms. AAAI (2024)
Alistair Shilton, Sunil Gupta, Santu Rana, Svetha Venkatesh
Novel Kernel Models and Exact Representor Theory for Neural Networks Beyond the Over-Parameterized Regime. CoRR (2024)
Giang Ngo, Dang Nguyen, Dat Phan-Trong, Sunil Gupta
Active Level Set Estimation for Continuous Search Space with Theoretical Guarantee. CoRR (2024)
Dat Phan-Trong, Hung The Tran, Alistair Shilton, Sunil Gupta
PINN-BO: A Black-box Optimization Algorithm using Physics-Informed Neural Networks. CoRR (2024)
Linh Le Pham Van, Hung The Tran, Sunil Gupta
Policy Learning for Off-Dynamics RL with Deficient Support. AAMAS (2024)
Manisha Senadeera, Thommen Karimpanal George, Sunil Gupta, Stephan Jacobs, Santu Rana
EMOTE: An Explainable architecture for Modelling the Other Through Empathy. CoRR (2023)
Dat Phan-Trong, Hung Tran-The, Sunil Gupta
Neural-BO: A Black-box Optimization Algorithm using Deep Neural Networks. CoRR (2023)
Alistair Shilton, Sunil Gupta, Santu Rana, Svetha Venkatesh
Gradient Descent in Neural Networks as Sequential Learning in Reproducing Kernel Banach Space. ICML (2023)
Alistair Shilton, Sunil Gupta, Santu Rana, Svetha Venkatesh
Gradient Descent in Neural Networks as Sequential Learning in RKBS. CoRR (2023)
Giang Ngo, Dang Nguyen, Dat Phan-Trong, Sunil Gupta
Active Level Set Estimation for Continuous Search Space with Theoretical Guarantee. ACML (2023)
Dat Phan-Trong, Hung Tran-The, Sunil Gupta
NeuralBO: A black-box optimization algorithm using deep neural networks. Neurocomputing 559 (2023)
Manisha Senadeera, Santu Rana, Sunil Gupta, Svetha Venkatesh
Predictive Modeling through Hyper-Bayesian Optimization. CoRR (2023)
Phuoc Nguyen, Truyen Tran, Sunil Gupta, Thin Nguyen, Svetha Venkatesh
Root Cause Explanation of Outliers under Noisy Mechanisms. CoRR (2023)
Tuan Hoang, Santu Rana, Sunil Gupta, Svetha Venkatesh
Learn to Unlearn for Deep Neural Networks: Minimizing Unlearning Interference with Gradient Projection. CoRR (2023)
Prashant W. Patil, Sunil Gupta, Santu Rana, Svetha Venkatesh, Subrahmanyam Murala
Multi-weather Image Restoration via Domain Translation. ICCV (2023)
Ashutosh Kulkarni, Prashant W. Patil, Subrahmanyam Murala, Sunil Gupta
Unified Multi-Weather Visibility Restoration. IEEE Trans. Multim. 25 (2023)
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)
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 (2023)
Thao Minh Le, Vuong Le, Sunil Gupta, Svetha Venkatesh, Truyen Tran
Guiding Visual Question Answering with Attention Priors. WACV (2023)
Ragja Palakkadavath, Thanh Nguyen-Tang, Hung Le, Svetha Venkatesh, Sunil Gupta
Domain Generalization with Interpolation Robustness. ACML (2023)
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 (2023)
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 (2023)
Thanh Nguyen-Tang, Sunil Gupta, A. Tuan Nguyen, Svetha Venkatesh
Offline Neural Contextual Bandits: Pessimism, Optimization and Generalization. ICLR (2022)
Prashant W. Patil, Sunil Gupta, Santu Rana, Svetha Venkatesh
Video Restoration Framework and Its Meta-adaptations to Data-Poor Conditions. ECCV (28) (2022)
Hung Tran-The, Sunil Gupta, Santu Rana, Tuan Truong, Long Tran-Thanh, Svetha Venkatesh
Expected Improvement for Contextual Bandits. NeurIPS (2022)
Hung Tran-The, Sunil Gupta, Santu Rana, Svetha Venkatesh
Regret Bounds for Expected Improvement Algorithms in Gaussian Process Bandit Optimization. AISTATS (2022)
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 (2022)
Hung Le, Thommen George Karimpanal, Majid Abdolshah, Dung Nguyen, Kien Do, Sunil Gupta, Svetha Venkatesh
Memory-Constrained Policy Optimization. CoRR (2022)
Thanh Nguyen-Tang, Ming Yin, Sunil Gupta, Svetha Venkatesh, Raman Arora
On Instance-Dependent Bounds for Offline Reinforcement Learning with Linear Function Approximation. CoRR (2022)
Stewart Greenhill, Majid Abdolshah, Vuong Le, Sunil Gupta, Svetha Venkatesh
Semantic Control of Generative Musical Attributes. ISMIR (2022)
Hung Tran-The, Sunil Gupta, Santu Rana, Svetha Venkatesh
Regret Bounds for Expected Improvement Algorithms in Gaussian Process Bandit Optimization. CoRR (2022)
Haripriya Harikumar, Santu Rana, Sunil Gupta, Thin Nguyen, Ramachandra Kaimal, Svetha Venkatesh
Prescriptive analytics with differential privacy. Int. J. Data Sci. Anal. 13 (2) (2022)
Prashant W. Patil, Sunil Gupta, Santu Rana, Svetha Venkatesh
Dual-frame spatio-temporal feature modulation for video enhancement. Pattern Recognit. 130 (2022)
Dang Nguyen, Sunil Gupta, Kien Do, Svetha Venkatesh
Black-box Few-shot Knowledge Distillation. CoRR (2022)
Manisha Senadeera, Thommen George Karimpanal, Sunil Gupta, Santu Rana
Sympathy-based Reinforcement Learning Agents. AAMAS (2022)
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 (2022)
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)
Dang Nguyen, Sunil Gupta, Kien Do, Svetha Venkatesh
Black-Box Few-Shot Knowledge Distillation. ECCV (21) (2022)
Alistair Shilton, Sunil Gupta, Santu Rana, Arun Kumar Anjanapura Venkatesh, Svetha Venkatesh
TRF: Learning Kernels with Tuned Random Features. AAAI (2022)
Haripriya Harikumar, Santu Rana, Kien Do, Sunil Gupta, Wei Zong, Willy Susilo, Svetha Venkatesh
Defense Against Multi-target Trojan Attacks. CoRR (2022)
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)
Thao Minh Le, Vuong Le, Sunil Gupta, Svetha Venkatesh, Truyen Tran
Guiding Visual Question Answering with Attention Priors. CoRR (2022)
Preeti Gopal, Sunil Gupta, Santu Rana, Vuong Le, Trong Nguyen, Svetha Venkatesh
Real-Time Skill Discovery in Intelligent Virtual Assistants. PAKDD (1) (2022)
Huong Ha, Sunil Gupta, Santu Rana, Svetha Venkatesh
High Dimensional Level Set Estimation with Bayesian Neural Network. AAAI (2021)
Thomas P. Quinn, Sunil Gupta, Svetha Venkatesh, Vuong Le
A Field Guide to Scientific XAI: Transparent and Interpretable Deep Learning for Bioinformatics Research. CoRR (2021)
Phuoc Nguyen, Truyen Tran, Sunil Gupta, Santu Rana, Hieu-Chi Dam, Svetha Venkatesh
Variational Hyper-encoding Networks. ECML/PKDD (2) (2021)
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 (2021)
Arun Kumar Anjanapura Venkatesh, Alistair Shilton, Santu Rana, Sunil Gupta, Svetha Venkatesh
Kernel Functional Optimisation. NeurIPS (2021)
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)
Thanh Nguyen-Tang, Sunil Gupta, Hung Tran-The, Svetha Venkatesh
On Finite-Sample Analysis of Offline Reinforcement Learning with Deep ReLU Networks. CoRR (2021)
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)
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)
Ang Yang, Cheng Li, Santu Rana, Sunil Gupta, Svetha Venkatesh
Sparse Spectrum Gaussian Process for Bayesian Optimization. PAKDD (2) (2021)
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 (2021)
Dang Nguyen, Sunil Gupta, Santu Rana, Alistair Shilton, Svetha Venkatesh
Fairness improvement for black-box classifiers with Gaussian process. Inf. Sci. 576 (2021)
Thanh Nguyen-Tang, Sunil Gupta, A. Tuan Nguyen, Svetha Venkatesh
Offline Neural Contextual Bandits: Pessimism, Optimization and Generalization. CoRR (2021)
Hung Tran-The, Sunil Gupta, Santu Rana, Svetha Venkatesh
Bayesian Optimistic Optimisation with Exponentially Decaying Regret. ICML (2021)
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 (2021)
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 (2021)
Hung Tran-The, Sunil Gupta, Santu Rana, Svetha Venkatesh
Bayesian Optimistic Optimisation with Exponentially Decaying Regret. CoRR (2021)
Huong Ha, Sunil Gupta, Santu Rana, Svetha Venkatesh
ALT-MAS: A Data-Efficient Framework for Active Testing of Machine Learning Algorithms. CoRR (2021)
Majid Abdolshah, Hung Le, Thommen George Karimpanal, Sunil Gupta, Santu Rana, Svetha Venkatesh
Plug and Play, Model-Based Reinforcement Learning. CoRR (2021)
Haripriya Harikumar, Kien Do, Santu Rana, Sunil Gupta, Svetha Venkatesh
Semantic Host-free Trojan Attack. CoRR (2021)
Phuc Luong, Dang Nguyen, Sunil Gupta, Santu Rana, Svetha Venkatesh
Adaptive cost-aware Bayesian optimization. Knowl. Based Syst. 232 (2021)
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)
Thanh Nguyen-Tang, Sunil Gupta, Svetha Venkatesh
Distributional Reinforcement Learning via Moment Matching. AAAI (2021)
Phuoc Nguyen, Truyen Tran, Sunil Gupta, Santu Rana, Hieu-Chi Dam, Svetha Venkatesh
HyperVAE: A Minimum Description Length Variational Hyper-Encoding Network. CoRR (2020)
Phuc Luong, Dang Nguyen, Sunil Gupta, Santu Rana, Svetha Venkatesh
Bayesian Optimization with Missing Inputs. CoRR (2020)
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)
Manisha Senadeera, Santu Rana, Sunil Gupta, Svetha Venkatesh
Level Set Estimation with Search Space Warping. PAKDD (2) (2020)
Duc Nguyen, Phuoc Nguyen, Kien Do, Santu Rana, Sunil Gupta, Truyen Tran
Unsupervised Anomaly Detection on Temporal Multiway Data. SSCI (2020)
Anil Ramachandran, Sunil Gupta, Santu Rana, Cheng Li, Svetha Venkatesh
Incorporating Expert Prior in Bayesian Optimisation via Space Warping. CoRR (2020)
Anh-Cat Le-Ngo, Truyen Tran, Santu Rana, Sunil Gupta, Svetha Venkatesh
Logically Consistent Loss for Visual Question Answering. CoRR (2020)
Julian Berk, Sunil Gupta, Santu Rana, Vu Nguyen, Svetha Venkatesh
Bayesian optimisation in unknown bounded search domains. Knowl. Based Syst. 195 (2020)
Thommen George Karimpanal, Santu Rana, Sunil Gupta, Truyen Tran, Svetha Venkatesh
Learning Transferable Domain Priors for Safe Exploration in Reinforcement Learning. IJCNN (2020)
Julian Berk, Sunil Gupta, Santu Rana, Svetha Venkatesh
Randomised Gaussian Process Upper Confidence Bound for Bayesian Optimisation. CoRR (2020)
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)
Hung Tran-The, Sunil Gupta, Santu Rana, Huong Ha, Svetha Venkatesh
Sub-linear Regret Bounds for Bayesian Optimisation in Unknown Search Spaces. NeurIPS (2020)
Stewart Greenhill, Santu Rana, Sunil Gupta, Pratibha Vellanki, Svetha Venkatesh
Bayesian Optimization for Adaptive Experimental Design: A Review. IEEE Access 8 (2020)
Cheng Li, Sunil Gupta, Santu Rana, Vu Nguyen, Antonio Robles-Kelly, Svetha Venkatesh
Incorporating Expert Prior Knowledge into Experimental Design via Posterior Sampling. CoRR (2020)
Thanh Tang Nguyen, Sunil Gupta, Svetha Venkatesh
Distributional Reinforcement Learning with Maximum Mean Discrepancy. CoRR (2020)
Tinu Theckel Joy, Santu Rana, Sunil Gupta, Svetha Venkatesh
Fast hyperparameter tuning using Bayesian optimization with directional derivatives. Knowl. Based Syst. 205 (2020)
Haripriya Harikumar, Vuong Le, Santu Rana, Sourangshu Bhattacharya, Sunil Gupta, Svetha Venkatesh
Scalable Backdoor Detection in Neural Networks. CoRR (2020)
Hung Tran-The, Sunil Gupta, Santu Rana, Huong Ha, Svetha Venkatesh
Sub-linear Regret Bounds for Bayesian Optimisation in Unknown Search Spaces. CoRR (2020)
Thanh Tang Nguyen, Sunil Gupta, Huong Ha, Santu Rana, Svetha Venkatesh
Distributionally Robust Bayesian Quadrature Optimization. CoRR (2020)
Anil Ramachandran, Sunil Gupta, Santu Rana, Cheng Li, Svetha Venkatesh
Incorporating expert prior in Bayesian optimisation via space warping. Knowl. Based Syst. 195 (2020)
Phuc Luong, Dang Nguyen, Sunil Gupta, Santu Rana, Svetha Venkatesh
Bayesian Optimization with Missing Inputs. ECML/PKDD (2) (2020)
Steven Allender, J. Hayward, Sunil Gupta, A. Sanigorski, Santu Rana, Hugh Seward, S. Jacobs, Svetha Venkatesh
Bayesian strategy selection identifies optimal solutions to complex problems using an example from GP prescribing. npj Digit. Medicine 3 (2020)
Thomas P. Quinn, Dang Nguyen, Santu Rana, Sunil Gupta, Svetha Venkatesh
DeepCoDA: personalized interpretability for compositional health data. CoRR (2020)
Julian Berk, Sunil Gupta, Santu Rana, Svetha Venkatesh
Randomised Gaussian Process Upper Confidence Bound for Bayesian Optimisation. IJCAI (2020)
Haripriya Harikumar, Vuong Le, Santu Rana, Sourangshu Bhattacharya, Sunil Gupta, Svetha Venkatesh
Scalable Backdoor Detection in Neural Networks. ECML/PKDD (2) (2020)
Hung Tran-The, Sunil Gupta, Santu Rana, Svetha Venkatesh
Trading Convergence Rate with Computational Budget in High Dimensional Bayesian Optimization. AAAI (2020)
Duc Nguyen, Phuoc Nguyen, Kien Do, Santu Rana, Sunil Gupta, Truyen Tran
Unsupervised Anomaly Detection on Temporal Multiway Data. CoRR (2020)
Huong Ha, Sunil Gupta, Santu Rana, Svetha Venkatesh
High Dimensional Level Set Estimation with Bayesian Neural Network. CoRR (2020)
Alistair Shilton, Sunil Gupta, Santu Rana, Svetha Venkatesh
Sequential Subspace Search for Functional Bayesian Optimization Incorporating Experimenter Intuition. CoRR (2020)
Thomas P. Quinn, Dang Nguyen, Santu Rana, Sunil Gupta, Svetha Venkatesh
DeepCoDA: personalized interpretability for compositional health data. ICML (2020)
Tinu Theckel Joy, Santu Rana, Sunil Gupta, Svetha Venkatesh
Batch Bayesian optimization using multi-scale search. Knowl. Based Syst. 187 (2020)

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Publication Activity (10 Years)

Top Topics

Top Venues

Sunil Gupta