Santu Rana
Publication record assembled from the DBLP archive of ranked conferences.
Papers indexed
76
Venues
23
Active years
2008–2026
Best venue rank
A*
Where they publish
- BPAKDD14 papers
- BICPR13 papers
- A*ICDM6 papers
- A*ICML5 papers
- A*AAAI5 papers
- AAISTATS5 papers
- AECAI3 papers
- A*IJCAI3 papers
- BPRICAI3 papers
- ASDM3 papers
- A*ECCV2 papers
- CACML2 papers
- CADMA2 papers
- AEACL1 paper
- BLREC1 paper
- ANAACL1 paper
- BACCV1 paper
- BHAI1 paper
- AWACV1 paper
- A*ICCV1 paper
- BIJCNN1 paper
- AUAI1 paper
- A*CVPR1 paper
Papers
76 indexed papers, newest first.
| Year | Venue | Title | Authors |
|---|---|---|---|
| 2026 | EACL | The Unintended Trade-off of AI Alignment: Balancing Hallucination Mitigation and Safety in LLMs. | Omar Mahmoud, Ali Khalil, Thommen George Karimpanal, Buddhika Laknath Semage, Santu Rana |
| 2026 | ICPR | Leveraging Human Feedback for Semantically-Relevant Skill Discovery. | Maxence Hussonnois, Thommen George Karimpanal, Santu Rana |
| 2026 | LREC | Improving Multilingual Language Models by Aligning Representations through Steering. | Omar Mohamed Mahmoud, Buddhika Laknath Semage, Thommen George Karimpanal, Santu Rana |
| 2025 | ECAI | MAGIK: Mapping to Analogous Goals via Imagination-Enabled Knowledge Transfer. | Ajsal Shereef Palattuparambil, Thommen George Karimpanal, Santu Rana |
| 2025 | NAACL | 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 |
| 2025 | PAKDD | Defense Against Multi-target Multi-trigger Backdoor Attacks. | Haripriya Harikumar, Santu Rana, Kien Do, Sunil Gupta, Wei Zong, Willy Susilo, Svetha Venkatesh |
| 2024 | ACCV | Revisiting Sample Weights Based Method for Noisy-Label Detection and Classification. | Tuan Hoang, Hung Tran, Santu Rana, Sunil Gupta, Svetha Venkatesh |
| 2024 | ECAI | Revisiting the Dataset Bias Problem from a Statistical Perspective. | Kien Do, Dung Nguyen, Hung Le, Thao Le, Dang Nguyen, Haripriya Harikumar, Truyen Tran, Santu Rana, Svetha Venkatesh |
| 2024 | ECAI | A Data-Driven Defense Against Edge-Case Model Poisoning Attacks on Federated Learning. | Kiran Purohit, Soumi Das, Sourangshu Bhattacharya, Santu Rana |
| 2024 | HAI | Personalisation via Dynamic Policy Fusion. | Ajsal Shereef Palattuparambil, Thommen Karimpanal George, Santu Rana |
| 2024 | ICPR | Composite Concept Extraction Through Backdooring. | Banibrata Ghosh, Haripriya Harikumar, Khoa D. Doan, Svetha Venkatesh, Santu Rana |
| 2024 | IJCAI | EMOTE: An Explainable Architecture for Modelling the Other through Empathy. | Manisha Senadeera, Thommen Karimpanal George, Stephan Jacobs, Sunil Gupta, Santu Rana |
| 2024 | WACV | Learn to Unlearn for Deep Neural Networks: Minimizing Unlearning Interference with Gradient Projection. | Tuan Hoang, Santu Rana, Sunil Gupta, Svetha Venkatesh |
| 2023 | ICCV | Multi-weather Image Restoration via Domain Translation. | Prashant W. Patil, Sunil Gupta, Santu Rana, Svetha Venkatesh, Subrahmanyam Murala |
| 2023 | ICML | Gradient Descent in Neural Networks as Sequential Learning in Reproducing Kernel Banach Space. | Alistair Shilton, Sunil Gupta, Santu Rana, Svetha Venkatesh |
| 2022 | AAAI | TRF: Learning Kernels with Tuned Random Features. | Alistair Shilton, Sunil Gupta, Santu Rana, Arun Kumar Anjanapura Venkatesh, Svetha Venkatesh |
| 2022 | AISTATS | Regret Bounds for Expected Improvement Algorithms in Gaussian Process Bandit Optimization. | Hung Tran-The, Sunil Gupta, Santu Rana, Svetha Venkatesh |
| 2022 | ECCV | 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 |
| 2022 | ECCV | Video Restoration Framework and Its Meta-adaptations to Data-Poor Conditions. | Prashant W. Patil, Sunil Gupta, Santu Rana, Svetha Venkatesh |
| 2022 | ICPR | Fast Model-based Policy Search for Universal Policy Networks. | Buddhika Laknath Semage, Thommen George Karimpanal, Santu Rana, Svetha Venkatesh |
| 2022 | ICPR | Uncertainty Aware System Identification with Universal Policies. | Buddhika Laknath Semage, Thommen George Karimpanal, Santu Rana, Svetha Venkatesh |
| 2022 | ICPR | Intuitive Physics Guided Exploration for Sample Efficient Sim2real Transfer. | Buddhika Laknath Semage, Thommen George Karimpanal, Santu Rana, Svetha Venkatesh |
| 2022 | PAKDD | Real-Time Skill Discovery in Intelligent Virtual Assistants. | Preeti Gopal, Sunil Gupta, Santu Rana, Vuong Le, Trong Nguyen, Svetha Venkatesh |
| 2021 | AAAI | High Dimensional Level Set Estimation with Bayesian Neural Network. | Huong Ha, Sunil Gupta, Santu Rana, Svetha Venkatesh |
| 2021 | ICML | A New Representation of Successor Features for Transfer across Dissimilar Environments. | Majid Abdolshah, Hung Le, Thommen George Karimpanal, Sunil Gupta, Santu Rana, Svetha Venkatesh |
| 2021 | ICML | Bayesian Optimistic Optimisation with Exponentially Decaying Regret. | Hung Tran-The, Sunil Gupta, Santu Rana, Svetha Venkatesh |
| 2021 | PAKDD | Sparse Spectrum Gaussian Process for Bayesian Optimization. | Ang Yang, Cheng Li, Santu Rana, Sunil Gupta, Svetha Venkatesh |
| 2020 | AAAI | Bayesian Optimization for Categorical and Category-Specific Continuous Inputs. | Dang Nguyen, Sunil Gupta, Santu Rana, Alistair Shilton, Svetha Venkatesh |
| 2020 | AAAI | Trading Convergence Rate with Computational Budget in High Dimensional Bayesian Optimization. | Hung Tran-The, Sunil Gupta, Santu Rana, Svetha Venkatesh |
| 2020 | AISTATS | Distributionally Robust Bayesian Quadrature Optimization. | Thanh Tang Nguyen, Sunil Gupta, Huong Ha, Santu Rana, Svetha Venkatesh |
| 2020 | AISTATS | 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 |
| 2020 | ICML | DeepCoDA: personalized interpretability for compositional health data. | Thomas P. Quinn, Dang Nguyen, Santu Rana, Sunil Gupta, Svetha Venkatesh |
| 2020 | ICPR | Factor Screening using Bayesian Active Learning and Gaussian Process Meta-Modelling. | Cheng Li, Santu Rana, Andrew Gill, Dang Nguyen, Sunil Gupta, Svetha Venkatesh |
| 2020 | IJCAI | Randomised Gaussian Process Upper Confidence Bound for Bayesian Optimisation. | Julian Berk, Sunil Gupta, Santu Rana, Svetha Venkatesh |
| 2020 | IJCNN | Learning Transferable Domain Priors for Safe Exploration in Reinforcement Learning. | Thommen George Karimpanal, Santu Rana, Sunil Gupta, Truyen Tran, Svetha Venkatesh |
| 2020 | PAKDD | Level Set Estimation with Search Space Warping. | Manisha Senadeera, Santu Rana, Sunil Gupta, Svetha Venkatesh |
| 2019 | AAAI | Bayesian Functional Optimisation with Shape Prior. | Pratibha Vellanki, Santu Rana, Sunil Gupta, David Rubin de Celis Leal, Alessandra Sutti, Murray Height, Svetha Venkatesh |
| 2019 | ICDM | Efficient Bayesian Optimization for Uncertainty Reduction Over Perceived Optima Locations. | Vu Nguyen, Sunil Gupta, Santu Rana, My T. Thai, Cheng Li, Svetha Venkatesh |
| 2019 | PRICAI | Explaining Black-Box Models Using Interpretable Surrogates. | Deepthi Praveenlal Kuttichira, Sunil Gupta, Cheng Li, Santu Rana, Svetha Venkatesh |
| 2019 | SDM | Incomplete Conditional Density Estimation for Fast Materials Discovery. | Phuoc Nguyen, Truyen Tran, Sunil Gupta, Santu Rana, Matthew Barnett, Svetha Venkatesh |
| 2018 | AISTATS | Exploiting Strategy-Space Diversity for Batch Bayesian Optimization. | Sunil Gupta, Alistair Shilton, Santu Rana, Svetha Venkatesh |
| 2018 | ICDM | Accelerating Experimental Design by Incorporating Experimenter Hunches. | 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 |
| 2018 | ICDM | Differentially Private Prescriptive Analytics. | Haripriya Harikumar, Santu Rana, Sunil Gupta, Thin Nguyen, Ramachandra Kaimal, Svetha Venkatesh |
| 2018 | ICPR | Expected Hypervolume Improvement with Constraints. | Majid Abdolshah, Alistair Shilton, Santu Rana, Sunil Gupta, Svetha Venkatesh |
| 2018 | PAKDD | Prescriptive Analytics Through Constrained Bayesian Optimization. | Haripriya Harikumar, Santu Rana, Sunil Gupta, Thin Nguyen, Ramachandra Kaimal, Svetha Venkatesh |
| 2018 | PAKDD | A Privacy Preserving Bayesian Optimization with High Efficiency. | Thanh Dai Nguyen, Sunil Gupta, Santu Rana, Svetha Venkatesh |
| 2018 | PRICAI | Selecting Optimal Source for Transfer Learning in Bayesian Optimisation. | Anil Ramachandran, Sunil Gupta, Santu Rana, Svetha Venkatesh |
| 2018 | PRICAI | Efficient Bayesian Optimisation Using Derivative Meta-model. | Ang Yang, Cheng Li, Santu Rana, Sunil Gupta, Svetha Venkatesh |
| 2018 | UAI | Multi-Target Optimisation via Bayesian Optimisation and Linear Programming. | Alistair Shilton, Santu Rana, Sunil Gupta, Svetha Venkatesh |
| 2017 | ACML | Regret for Expected Improvement over the Best-Observed Value and Stopping Condition. | Vu Nguyen, Sunil Gupta, Santu Rana, Cheng Li, Svetha Venkatesh |
| 2017 | AISTATS | Regret Bounds for Transfer Learning in Bayesian Optimisation. | Alistair Shilton, Sunil Gupta, Santu Rana, Svetha Venkatesh |
| 2017 | ICDM | Bayesian Optimization in Weakly Specified Search Space. | Vu Nguyen, Sunil Gupta, Santu Rana, Cheng Li, Svetha Venkatesh |
| 2017 | ICML | High Dimensional Bayesian Optimization with Elastic Gaussian Process. | Santu Rana, Cheng Li, Sunil Gupta, Vu Nguyen, Svetha Venkatesh |
| 2017 | IJCAI | High Dimensional Bayesian Optimization using Dropout. | Cheng Li, Sunil Gupta, Santu Rana, Vu Nguyen, Svetha Venkatesh, Alistair Shilton |
| 2017 | PAKDD | Stable Bayesian Optimization. | Thanh Dai Nguyen, Sunil Gupta, Santu Rana, Svetha Venkatesh |
| 2016 | ACML | A Bayesian Nonparametric Approach for Multi-label Classification. | Vu Nguyen, Sunil Gupta, Santu Rana, Cheng Li, Svetha Venkatesh |
| 2016 | ADMA | Understanding Behavioral Differences Between Short and Long-Term Drinking Abstainers from Social Media. | Haripriya Harikumar, Thin Nguyen, Sunil Gupta, Santu Rana, Ramachandra Kaimal, Svetha Venkatesh |
| 2016 | ADMA | Extracting Key Challenges in Achieving Sobriety Through Shared Subspace Learning. | Haripriya Harikumar, Thin Nguyen, Santu Rana, Sunil Gupta, Ramachandra Kaimal, Svetha Venkatesh |
| 2016 | ICDM | Budgeted Batch Bayesian Optimization. | Vu Nguyen, Santu Rana, Sunil Kumar Gupta, Cheng Li, Svetha Venkatesh |
| 2016 | ICPR | Hyperparameter tuning for big data using Bayesian optimisation. | Tinu Theckel Joy, Santu Rana, Sunil Gupta, Svetha Venkatesh |
| 2016 | ICPR | Multiple adverse effects prediction in longitudinal cancer treatment. | Cheng Li, Sunil Gupta, Santu Rana, Vu Nguyen, Svetha Venkatesh, David Ashely, Trish Livingston |
| 2016 | ICPR | Bayesian nonparametric Multiple Instance Regression. | Saravanan Subramanian, Santu Rana, Sunil Gupta, Palaniappan Bagavathi Sivakumar, C. Shunmuga Velayutham, Svetha Venkatesh |
| 2016 | PAKDD | Flexible Transfer Learning Framework for Bayesian Optimisation. | Tinu Theckel Joy, Santu Rana, Sunil Kumar Gupta, Svetha Venkatesh |
| 2016 | PAKDD | Toxicity Prediction in Cancer Using Multiple Instance Learning in a Multi-task Framework. | Cheng Li, Sunil Gupta, Santu Rana, Wei Luo, Svetha Venkatesh, David Ashely, Dinh Q. Phung |
| 2016 | PAKDD | Privacy Aware K-Means Clustering with High Utility. | Thanh Dai Nguyen, Sunil Gupta, Santu Rana, Svetha Venkatesh |
| 2015 | ICDM | Differentially Private Random Forest with High Utility. | Santu Rana, Sunil Kumar Gupta, Svetha Venkatesh |
| 2015 | PAKDD | Collaborating Differently on Different Topics: A Multi-Relational Approach to Multi-Task Learning. | Sunil Kumar Gupta, Santu Rana, Dinh Q. Phung, Svetha Venkatesh |
| 2015 | PAKDD | Small-Variance Asymptotics for Bayesian Nonparametric Models with Constraints. | Cheng Li, Santu Rana, Dinh Q. Phung, Svetha Venkatesh |
| 2015 | SDM | What shall I share and with Whom? - A Multi-Task Learning Formulation using Multi-Faceted Task Relationships. | Sunil Gupta, Santu Rana, Dinh Q. Phung, Svetha Venkatesh |
| 2014 | ICPR | Regularizing Topic Discovery in EMRs with Side Information by Using Hierarchical Bayesian Models. | Cheng Li, Santu Rana, Dinh Q. Phung, Svetha Venkatesh |
| 2014 | PAKDD | Intervention-Driven Predictive Framework for Modeling Healthcare Data. | Santu Rana, Sunil Kumar Gupta, Dinh Q. Phung, Svetha Venkatesh |
| 2014 | SDM | Keeping up with Innovation: A Predictive Framework for Modeling Healthcare Data with Evolving Clinical Interventions. | Sunil Kumar Gupta, Santu Rana, Dinh Q. Phung, Svetha Venkatesh |
| 2013 | PAKDD | Split-Merge Augmented Gibbs Sampling for Hierarchical Dirichlet Processes. | Santu Rana, Dinh Q. Phung, Svetha Venkatesh |
| 2012 | ICPR | Multi-modal abnormality detection in video with unknown data segmentation. | Tien-Vu Nguyen, Dinh Q. Phung, Santu Rana, Duc-Son Pham, Svetha Venkatesh |
| 2008 | CVPR | Recognising faces in unseen modes: A tensor based approach. | Santu Rana, Wanquan Liu, Mihai M. Lazarescu, Svetha Venkatesh |
| 2008 | ICPR | Efficient tensor based face recognition. | Santu Rana, Wanquan Liu, Mihai M. Lazarescu, Svetha Venkatesh |