Rana, Santu

46 publications

NeurIPS 2025 Reproducing Kernel Banach Space Models for Neural Networks with Application to Rademacher Complexity Analysis Alistair Shilton, Sunil Gupta, Santu Rana, Svetha Venkatesh

NeurIPSW 2024 Alpaca Against Vicuna: Using LLMs to Uncover Memorization of LLMs Aly M. Kassem, Omar Mahmoud, Niloofar Mireshghallah, Hyunwoo Kim, Yulia Tsvetkov, Yejin Choi, Sherif Saad, Santu Rana

IJCAI 2024 EMOTE: An Explainable Architecture for Modelling the Other Through Empathy Manisha Senadeera, Thommen Karimpanal George, Stephan Jacobs, Sunil Gupta, Santu Rana

ECML-PKDD 2024 Enhanced Bayesian Optimization via Preferential Modeling of Abstract Properties A. V. Arun Kumar, Alistair Shilton, Sunil Gupta, Santu Rana, Stewart Greenhill, Svetha Venkatesh

WACV 2024 Learn to Unlearn for Deep Neural Networks: Minimizing Unlearning Interference with Gradient Projection Tuan Hoang, Santu Rana, Sunil Gupta, Svetha Venkatesh

ICML 2023 Gradient Descent in Neural Networks as Sequential Learning in Reproducing Kernel Banach Space Alistair Shilton, Sunil Gupta, Santu Rana, Svetha Venkatesh

NeurIPSW 2023 Hierarchical GFlowNet for Crystal Structure Generation Tri Minh Nguyen, Sherif Abdulkader Tawfik, Truyen Tran, Sunil Gupta, Santu Rana, Svetha Venkatesh

ICCV 2023 Multi-Weather Image Restoration via Domain Translation Prashant W. Patil, Sunil Gupta, Santu Rana, Svetha Venkatesh, Subrahmanyam Murala

AISTATS 2022 Regret Bounds for Expected Improvement Algorithms in Gaussian Process Bandit Optimization Hung Tran-The, Sunil Gupta, Santu Rana, Svetha Venkatesh

NeurIPS 2022 Expected Improvement for Contextual Bandits Hung Tran-The, Sunil Gupta, Santu Rana, Tuan Truong, Long Tran-Thanh, Svetha Venkatesh

NeurIPS 2022 Human-AI Collaborative Bayesian Optimisation A V Arun Kumar, Santu Rana, Alistair Shilton, Svetha Venkatesh

NeurIPS 2022 Momentum Adversarial Distillation: Handling Large Distribution Shifts in Data-Free Knowledge Distillation Kien Do, Thai Hung Le, Dung Nguyen, Dang Nguyen, Haripriya Harikumar, Truyen Tran, Santu Rana, Svetha Venkatesh

AAAI 2022 TRF: Learning Kernels with Tuned Random Features Alistair Shilton, Sunil Gupta, Santu Rana, Arun Kumar Anjanapura Venkatesh, Svetha Venkatesh

ECCV 2022 Towards Effective and Robust Neural Trojan Defenses via Input Filtering Kien Do, Haripriya Harikumar, Hung Le, Dung Nguyen, Truyen Tran, Santu Rana, Dang Nguyen, Willy Susilo, Svetha Venkatesh

ECCV 2022 Video Restoration Framework and Its Meta-Adaptations to Data-Poor Conditions Prashant W Patil, Sunil Gupta, Santu Rana, Svetha Venkatesh

ICML 2021 A New Representation of Successor Features for Transfer Across Dissimilar Environments Majid Abdolshah, Hung Le, Thommen Karimpanal George, Sunil Gupta, Santu Rana, Svetha Venkatesh

ICML 2021 Bayesian Optimistic Optimisation with Exponentially Decaying Regret Hung Tran-The, Sunil Gupta, Santu Rana, Svetha Venkatesh

ECML-PKDD 2021 Fast Conditional Network Compression Using Bayesian HyperNetworks Phuoc Nguyen, Truyen Tran, Ky Le, Sunil Gupta, Santu Rana, Dang Nguyen, Trong Nguyen, Shannon Ryan, Svetha Venkatesh

AAAI 2021 High Dimensional Level Set Estimation with Bayesian Neural Network Huong Ha, Sunil Gupta, Santu Rana, Svetha Venkatesh

NeurIPS 2021 Kernel Functional Optimisation Arun Kumar Anjanapura Venkatesh, Alistair Shilton, Santu Rana, Sunil Gupta, Svetha Venkatesh

ECML-PKDD 2021 Knowledge Distillation with Distribution Mismatch Dang Nguyen, Sunil Gupta, Trong Nguyen, Santu Rana, Phuoc Nguyen, Truyen Tran, Ky Le, Shannon Ryan, Svetha Venkatesh

ECML-PKDD 2021 Variational Hyper-Encoding Networks Phuoc Nguyen, Truyen Tran, Sunil Gupta, Santu Rana, Hieu-Chi Dam, Svetha Venkatesh

AISTATS 2020 Accelerated Bayesian Optimisation Through Weight-Prior Tuning 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

AAAI 2020 Bayesian Optimization for Categorical and Category-Specific Continuous Inputs Dang Nguyen, Sunil Gupta, Santu Rana, Alistair Shilton, Svetha Venkatesh

ECML-PKDD 2020 Bayesian Optimization with Missing Inputs Phuc Luong, Dang Nguyen, Sunil Gupta, Santu Rana, Svetha Venkatesh

ICML 2020 DeepCoDA: Personalized Interpretability for Compositional Health Data Thomas Quinn, Dang Nguyen, Santu Rana, Sunil Gupta, Svetha Venkatesh

AISTATS 2020 Distributionally Robust Bayesian Quadrature Optimization Thanh Nguyen, Sunil Gupta, Huong Ha, Santu Rana, Svetha Venkatesh

IJCAI 2020 Randomised Gaussian Process Upper Confidence Bound for Bayesian Optimisation Julian Berk, Sunil Gupta, Santu Rana, Svetha Venkatesh

ECML-PKDD 2020 Scalable Backdoor Detection in Neural Networks Haripriya Harikumar, Vuong Le, Santu Rana, Sourangshu Bhattacharya, Sunil Gupta, Svetha Venkatesh

NeurIPS 2020 Sub-Linear Regret Bounds for Bayesian Optimisation in Unknown Search Spaces Hung Tran-The, Sunil Gupta, Santu Rana, Huong Ha, Svetha Venkatesh

AAAI 2020 Trading Convergence Rate with Computational Budget in High Dimensional Bayesian Optimization Hung Tran-The, Sunil Gupta, Santu Rana, Svetha Venkatesh

AAAI 2019 Bayesian Functional Optimisation with Shape Prior Pratibha Vellanki, Santu Rana, Sunil Gupta, David Rubin de Celis Leal, Alessandra Sutti, Murray Height, Svetha Venkatesh

NeurIPS 2019 Bayesian Optimization with Unknown Search Space Huong Ha, Santu Rana, Sunil Gupta, Thanh Nguyen, Hung Tran-The, Svetha Venkatesh

NeurIPS 2019 Multi-Objective Bayesian Optimisation with Preferences over Objectives Majid Abdolshah, Alistair Shilton, Santu Rana, Sunil Gupta, Svetha Venkatesh

NeurIPS 2018 Algorithmic Assurance: An Active Approach to Algorithmic Testing Using Bayesian Optimisation Shivapratap Gopakumar, Sunil Gupta, Santu Rana, Vu Nguyen, Svetha Venkatesh

AISTATS 2018 Exploiting Strategy-Space Diversity for Batch Bayesian Optimization Sunil Gupta, Alistair Shilton, Santu Rana, Svetha Venkatesh

ECML-PKDD 2018 Exploration Enhanced Expected Improvement for Bayesian Optimization Julian Berk, Vu Nguyen, Sunil Gupta, Santu Rana, Svetha Venkatesh

ECML-PKDD 2018 Information-Theoretic Transfer Learning Framework for Bayesian Optimisation Anil Ramachandran, Sunil Gupta, Santu Rana, Svetha Venkatesh

UAI 2018 Multi-Target Optimisation via Bayesian Optimisation and Linear Programming Alistair Shilton, Santu Rana, Sunil Gupta, Svetha Venkatesh

IJCAI 2017 High Dimensional Bayesian Optimization Using Dropout Cheng Li, Sunil Gupta, Santu Rana, Vu Nguyen, Svetha Venkatesh, Alistair Shilton

ICML 2017 High Dimensional Bayesian Optimization with Elastic Gaussian Process Santu Rana, Cheng Li, Sunil Gupta, Vu Nguyen, Svetha Venkatesh

NeurIPS 2017 Process-Constrained Batch Bayesian Optimisation Pratibha Vellanki, Santu Rana, Sunil Gupta, David Rubin, Alessandra Sutti, Thomas Dorin, Murray Height, Paul Sanders, Svetha Venkatesh

AISTATS 2017 Regret Bounds for Transfer Learning in Bayesian Optimisation Alistair Shilton, Sunil Gupta, Santu Rana, Svetha Venkatesh

ACML 2017 Regret for Expected Improvement over the Best-Observed Value and Stopping Condition Vu Nguyen, Sunil Gupta, Santu Rana, Cheng Li, Svetha Venkatesh

ACML 2016 A Bayesian Nonparametric Approach for Multi-Label Classification Vu Nguyen, Sunil Gupta, Santu Rana, Cheng Li, Svetha Venkatesh

CVPR 2008 Recognising Faces in Unseen Modes: A Tensor Based Approach Santu Rana, Wanquan Liu, Mihai M. Lazarescu, Svetha Venkatesh