← Authors

Santu Rana

35 papers · 2016–2026 · 11 conferences · across top CS/AI conferences

Achievements

🌍 Conference Polyglot (10) 🐝 Cross-Pollinator (14) 🐣 Hot Topic Early Bird 🌈 Renaissance Researcher (5) πŸŒ‰ Interdisciplinary Bridge πŸƒ Academic Marathon (9) πŸ—ΊοΈ Taxonomy Completionist (14) 🧭 Keyword Pioneer 🀝 Dynamic Duo (32) 🌱 Topic Pioneer πŸ”¬ Deep Specialist (20) 🧬 Topic Evolution πŸ† Keyword Champion (6) ⚑ Prolific Year (7) πŸ—ƒοΈ Keyword Collector (129) πŸ’Ž Century Club (34) πŸ“ˆ Trend Setter πŸ”₯ Unstoppable (10) πŸš€ Conference Pioneer

Conferences

NIPS (9) AAAI (5) AISTATS (5) ICML (5) IJCAI (3) ACML (2) ECCV (2) EACL (1) ICCV (1) NAACL (1) WACV (1)

Top co-authors

Svetha Venkatesh (32) Sunil Gupta (30) Alistair Shilton (10) Hung Tran-The (6) Cheng Li (5) Vu Nguyen (5) Huong Ha (4) Dang Nguyen (4) Murray Height (3) Alessandra Sutti (3)

Keywords

bayesian optimization (18) gaussian process (12) regret bound (11) acquisition function (8) hyperparameter tuning (6) bayesian optimisation (4) black-box optimization (3) active learning (3) kernel methods (3) expected improvement (3) transfer learning (3) black-box function (2) multi-objective optimization (2) neural tangent kernel (2) search space (2) hyperparameter optimization (2) high dimensional optimization (2) reward function (2) global optimization (2) high-dimensional optimization (2)

Papers

The Unintended Trade-off of AI Alignment: Balancing Hallucination Mitigation and Safety in LLMs EACL 2026
ALPACA AGAINST VICUNA: Using LLMs to Uncover Memorization of LLMs NAACL 2025
Learn To Unlearn for Deep Neural Networks: Minimizing Unlearning Interference With Gradient Projection WACV 2024
EMOTE: An Explainable Architecture for Modelling the Other through Empathy IJCAI 2024
Gradient Descent in Neural Networks as Sequential Learning in Reproducing Kernel Banach Space ICML 2023
Multi-weather Image Restoration via Domain Translation ICCV 2023
Regret Bounds for Expected Improvement Algorithms in Gaussian Process Bandit Optimization AISTATS 2022
Momentum Adversarial Distillation: Handling Large Distribution Shifts in Data-Free Knowledge Distillation NIPS 2022
Video Restoration Framework and Its Meta-Adaptations to Data-Poor Conditions ECCV 2022
Towards Effective and Robust Neural Trojan Defenses via Input Filtering ECCV 2022
TRF: Learning Kernels with Tuned Random Features AAAI 2022
Human-AI Collaborative Bayesian Optimisation NIPS 2022
Expected Improvement for Contextual Bandits NIPS 2022
A New Representation of Successor Features for Transfer across Dissimilar Environments ICML 2021
Kernel Functional Optimisation NIPS 2021
High Dimensional Level Set Estimation with Bayesian Neural Network AAAI 2021
Bayesian Optimistic Optimisation with Exponentially Decaying Regret ICML 2021
Trading Convergence Rate with Computational Budget in High Dimensional Bayesian Optimization AAAI 2020
Accelerated Bayesian Optimisation through Weight-Prior Tuning AISTATS 2020
Distributionally Robust Bayesian Quadrature Optimization AISTATS 2020
Randomised Gaussian Process Upper Confidence Bound for Bayesian Optimisation IJCAI 2020
DeepCoDA: personalized interpretability for compositional health data ICML 2020
Bayesian Optimization for Categorical and Category-Specific Continuous Inputs AAAI 2020
Sub-linear Regret Bounds for Bayesian Optimisation in Unknown Search Spaces NIPS 2020
Bayesian Functional Optimisation with Shape Prior AAAI 2019
Multi-objective Bayesian optimisation with preferences over objectives NIPS 2019
Bayesian Optimization with Unknown Search Space NIPS 2019
Exploiting Strategy-Space Diversity for Batch Bayesian Optimization AISTATS 2018
Algorithmic Assurance: An Active Approach to Algorithmic Testing using Bayesian Optimisation NIPS 2018
High Dimensional Bayesian Optimization using Dropout IJCAI 2017
High Dimensional Bayesian Optimization with Elastic Gaussian Process ICML 2017
Process-constrained batch Bayesian optimisation NIPS 2017
Regret Bounds for Transfer Learning in Bayesian Optimisation AISTATS 2017
Regret for Expected Improvement over the Best-Observed Value and Stopping Condition ACML 2017
A Bayesian Nonparametric Approach for Multi-label Classification ACML 2016