Sunil Gupta - RankMe

227 papers A* 41A 19B 11C 6Journal 114Unranked 36

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Adaptive Acquisition Selection for Bayesian Optimization with Large Language Models. CoRR Giang Ngo, Dat Phan-Trong, Dang Nguyen, Sunil Gupta, Svetha Venkatesh
2026	J	`jnl`	High-dimensional Level Set Estimation with Trust Regions and Double Acquisition Functions. CoRR Giang Ngo, Dat Phan-Trong, Dang Nguyen, Sunil Gupta
2026	A*	`conf`	Probabilities Are All You Need: A Probability-Only Approach to Uncertainty Estimation in Large Language Models. AAAI Manh Nguyen, Sunil Gupta, Hung Le
2026	J	`jnl`	Score-based Integrated Gradient for Root Cause Explanations of Outliers. CoRR Phuoc Nguyen, Truyen Tran, Sunil Gupta, Svetha Venkatesh
2025	J	`jnl`	Accelerated experimental design using a human-AI teaming framework. Knowl. Based Syst. Arun Kumar Anjanapura Venkatesh, Alistair Shilton, Sunil Gupta, Shannon Ryan, Majid Abdolshah, Hung Le, Santu Rana, Julian Berk, Mahad Rashid, Svetha Venkatesh
2025	A*	`conf`	Beyond the Known: Decision Making with Counterfactual Reasoning Decision Transformer. IJCAI Minh Hoang Nguyen, Linh Le Pham Van, Thommen George Karimpanal, Sunil Gupta, Hung Le
2025	J	`jnl`	Beyond the Known: Decision Making with Counterfactual Reasoning Decision Transformer. CoRR Minh Hoang Nguyen, Linh Le Pham Van, Thommen George Karimpanal, Sunil Gupta, Hung Le
2025	A	`conf`	Black-box Optimization with Unknown Constraints via Overparameterized Deep Neural Networks. UAI Dat Phan-Trong, Hung The Tran, Sunil Gupta
2025	J	`jnl`	CAAD: Context-Aware Adaptive Decoding for Truthful Text Generation. CoRR Manh Nguyen, Sunil Gupta, Hung Le
2025	A*	`conf`	Causal Discovery via Bayesian Optimization. ICLR Bao Duong, Sunil Gupta, Thin Nguyen
2025	J	`jnl`	Causal Discovery via Bayesian Optimization. CoRR Bao Duong, Sunil Gupta, Thin Nguyen
2025	J	`jnl`	Causal-Aware Generative Adversarial Networks with Reinforcement Learning. CoRR Tu Anh Hoang Nguyen, Dang Nguyen, Tri-Nhan Vo, Thuc Duy Le, Sunil Gupta
2025	—	`conf`	Defense Against Multi-target Multi-trigger Backdoor Attacks. PAKDD (6) Haripriya Harikumar, Santu Rana, Kien Do, Sunil Gupta, Wei Zong, Willy Susilo, Svetha Venkatesh
2025	—	`conf`	Designing Search Space for Unbounded Bayesian Optimization via Transfer Learning. ECML/PKDD (5) Quoc Anh Hoang Nguyen, Hung The Tran, Sunil Gupta, Dung D. Le
2025	J	`jnl`	Distance Is All You Need: Radial Dispersion for Uncertainty Estimation in Large Language Models. CoRR Manh Nguyen, Sunil Gupta, Hung Le
2025	A	`conf`	DmC: Nearest Neighbor Guidance Diffusion Model for Offline Cross-Domain Reinforcement Learning. ECAI Linh Le Pham Van, Minh Hoang Nguyen, Duc Kieu, Hung Le, Hung The Tran, Sunil Gupta
2025	J	`jnl`	DmC: Nearest Neighbor Guidance Diffusion Model for Offline Cross-domain Reinforcement Learning. CoRR Linh Le Pham Van, Minh Hoang Nguyen, Duc Kieu, Hung Le, Hung The Tran, Sunil Gupta
2025	A	`conf`	EvoCL: Continual Learning over Evolving Domains. WACV Vishnuprasadh Kumaravelu, P. K. Srijith, Sunil Gupta
2025	A	`conf`	Fair Domain Generalization with Heterogeneous Sensitive Attributes Across Domains. WACV Ragja Palakkadavath, Hung Le, Thanh Nguyen-Tang, Sunil Gupta, Svetha Venkatesh
2025	A*	`conf`	Federated Domain Generalization with Latent Space Inversion. ICDM Ragja Palakkadavath, Hung Le, Thanh Nguyen-Tang, Svetha Venkatesh, Sunil Gupta
2025	J	`jnl`	Federated Domain Generalization with Latent Space Inversion. CoRR Ragja Palakkadavath, Hung Le, Thanh Nguyen-Tang, Svetha Venkatesh, Sunil Gupta
2025	J	`jnl`	Finding the Trigger: Causal Abductive Reasoning on Video Events. CoRR Thao Minh Le, Vuong Le, Kien Do, Sunil Gupta, Svetha Venkatesh, Truyen Tran
2025	J	`jnl`	GRAD: Graph-Retrieved Adaptive Decoding for Hallucination Mitigation. CoRR Manh Nguyen, Sunil Gupta, Dai Do, Hung Le
2025	A	`conf`	High Dimensional Bayesian Optimization using Lasso Variable Selection. AISTATS Vu Viet Hoang, Hung The Tran, Sunil Gupta, Vu Nguyen
2025	J	`jnl`	High Dimensional Bayesian Optimization using Lasso Variable Selection. CoRR Vu Viet Hoang, Hung The Tran, Sunil Gupta, Vu Nguyen
2025	—	`conf`	Hybrid Cross-Domain Robust Reinforcement Learning. ECML/PKDD (6) Linh Le Pham Van, Minh Hoang Nguyen, Hung Le, Hung The Tran, Sunil Gupta
2025	J	`jnl`	Hybrid Cross-domain Robust Reinforcement Learning. CoRR Linh Le Pham Van, Minh Hoang Nguyen, Hung Le, Hung The Tran, Sunil Gupta
2025	J	`jnl`	LaGR-SEQ: Language-guided reinforcement learning with sample-efficient querying. Neural Comput. Appl. Thommen Karimpanal George, Buddhika Laknath Semage, Santu Rana, Hung Le, Truyen Tran, Sunil Gupta, Svetha Venkatesh
2025	J	`jnl`	Large Language Models for Imbalanced Classification: Diversity makes the difference. CoRR Dang Nguyen, Sunil Gupta, Kien Do, Binh T. Nguyen, Taylor A. Braund, Alexis E. Whitton, Svetha Venkatesh
2025	A	`conf`	Navigating Social Dilemmas with LLM-based Agents via Consideration of Future Consequences. AAMAS Dung Nguyen, Hung Le, Kien Do, Sunil Gupta, Svetha Venkatesh, Truyen Tran
2025	A*	`conf`	Navigating Social Dilemmas with LLM-based Agents via Consideration of Future Consequences. IJCAI Dung Nguyen, Hung Le, Kien Do, Sunil Gupta, Svetha Venkatesh, Truyen Tran
2025	J	`jnl`	Probabilities Are All You Need: A Probability-Only Approach to Uncertainty Estimation in Large Language Models. CoRR Manh Nguyen, Sunil Gupta, Hung Le
2025	A*	`conf`	Score-Based Integrated Gradient for Root Cause Explanations of Outliers. ICDM Phuoc Nguyen, Truyen Tran, Sunil Gupta, Svetha Venkatesh
2025	A*	`conf`	Stable Hadamard Memory: Revitalizing Memory-Augmented Agents for Reinforcement Learning. ICLR Hung Le, Dung Nguyen, Kien Do, Sunil Gupta, Svetha Venkatesh
2025	J	`jnl`	Unpaired recurrent learning for real-world video de-hazing. Pattern Recognit. Prashant W. Patil, Santosh Nagnath Randive, Sunil Gupta, Santu Rana, Svetha Venkatesh, Subrahmanyam Murala
2024	J	`jnl`	Active Level Set Estimation for Continuous Search Space with Theoretical Guarantee. CoRR Giang Ngo, Dang Nguyen, Dat Phan-Trong, Sunil Gupta
2024	A*	`conf`	Active Set Ordering. NeurIPS Quoc Phong Nguyen, Sunil Gupta, Svetha Venkatesh, Bryan Kian Hsiang Low, Patrick Jaillet
2024	A*	`conf`	Diversifying Training Pool Predictability for Zero-shot Coordination: A Theory of Mind Approach. IJCAI Dung Nguyen, Hung Le, Kien Do, Sunil Gupta, Svetha Venkatesh, Truyen Tran
2024	A*	`conf`	EMOTE: An Explainable Architecture for Modelling the Other through Empathy. IJCAI Manisha Senadeera, Thommen Karimpanal George, Stephan Jacobs, Sunil Gupta, Santu Rana
2024	J	`jnl`	Efficient Symmetry-Aware Materials Generation via Hierarchical Generative Flow Networks. CoRR Tri Minh Nguyen, Sherif Abdulkader Tawfik, Truyen Tran, Sunil Gupta, Santu Rana, Svetha Venkatesh
2024	—	`conf`	Enhanced Bayesian Optimization via Preferential Modeling of Abstract Properties. ECML/PKDD (6) A. V. Arun Kumar, Alistair Shilton, Sunil Gupta, Santu Rana, Stewart Greenhill, Svetha Venkatesh
2024	J	`jnl`	Enhanced Bayesian Optimization via Preferential Modeling of Abstract Properties. CoRR A. V. Arun Kumar, Alistair Shilton, Sunil Gupta, Santu Rana, Stewart Greenhill, Svetha Venkatesh
2024	J	`jnl`	Few-shot Algorithm Assurance. CoRR Dang Nguyen, Sunil Gupta
2024	A*	`conf`	Generating Realistic Tabular Data with Large Language Models. ICDM Dang Nguyen, Sunil Gupta, Kien Do, Thin Nguyen, Svetha Venkatesh
2024	J	`jnl`	Generating Realistic Tabular Data with Large Language Models. CoRR Dang Nguyen, Sunil Gupta, Kien Do, Thin Nguyen, Svetha Venkatesh
2024	—	`conf`	Improving Diversity in Black-Box Few-Shot Knowledge Distillation. ECML/PKDD (2) Tri-Nhan Vo, Dang Nguyen, Kien Do, Sunil Gupta
2024	A	`conf`	Learn to Unlearn for Deep Neural Networks: Minimizing Unlearning Interference with Gradient Projection. WACV Tuan Hoang, Santu Rana, Sunil Gupta, Svetha Venkatesh
2024	J	`jnl`	Novel Kernel Models and Exact Representor Theory for Neural Networks Beyond the Over-Parameterized Regime. CoRR Alistair Shilton, Sunil Gupta, Santu Rana, Svetha Venkatesh
2024	—	`conf`	PINN-BO: A Black-Box Optimization Algorithm Using Physics-Informed Neural Networks. ECML/PKDD (2) Dat Phan-Trong, Hung The Tran, Alistair Shilton, Sunil Gupta
2024	J	`jnl`	PINN-BO: A Black-box Optimization Algorithm using Physics-Informed Neural Networks. CoRR Dat Phan-Trong, Hung The Tran, Alistair Shilton, Sunil Gupta
2024	A	`conf`	Policy Learning for Off-Dynamics RL with Deficient Support. AAMAS Linh Le Pham Van, Hung The Tran, Sunil Gupta
2024	J	`jnl`	Policy Learning for Off-Dynamics RL with Deficient Support. CoRR Linh Le Pham Van, Hung The Tran, Sunil Gupta
2024	J	`jnl`	Predicting the Reliability of an Image Classifier under Image Distortion. CoRR Dang Nguyen, Sunil Gupta, Kien Do, Svetha Venkatesh
2024	—	`conf`	Revisiting Sample Weights Based Method for Noisy-Label Detection and Classification. ACCV (1) Tuan Hoang, Hung Tran, Santu Rana, Sunil Gupta, Svetha Venkatesh
2024	J	`jnl`	Robust Transfer Learning for Active Level Set Estimation with Locally Adaptive Gaussian Process Prior. CoRR Giang Ngo, Dang Nguyen, Sunil Gupta
2024	A*	`conf`	Root Cause Explanation of Outliers under Noisy Mechanisms. AAAI Phuoc Nguyen, Truyen Tran, Sunil Gupta, Thin Nguyen, Svetha Venkatesh
2024	J	`jnl`	Stable Hadamard Memory: Revitalizing Memory-Augmented Agents for Reinforcement Learning. CoRR Hung Le, Kien Do, Dung Nguyen, Sunil Gupta, Svetha Venkatesh
2023	C	`conf`	Active Level Set Estimation for Continuous Search Space with Theoretical Guarantee. ACML Giang Ngo, Dang Nguyen, Dat Phan-Trong, Sunil Gupta
2023	J	`jnl`	BO-Muse: A human expert and AI teaming framework for accelerated experimental design. CoRR Sunil Gupta, Alistair Shilton, Arun Kumar A. V., Shannon Ryan, Majid Abdolshah, Hung Le, Santu Rana, Julian Berk, Mahad Rashid, Svetha Venkatesh
2023	J	`jnl`	Balanced Q-learning: Combining the influence of optimistic and pessimistic targets. Artif. Intell. Thommen George Karimpanal, Hung Le, Majid Abdolshah, Santu Rana, Sunil Gupta, Truyen Tran, Svetha Venkatesh
2023	A	`conf`	Continual Learning with Dependency Preserving Hypernetworks. WACV Dupati Srikar Chandra, Sakshi Varshney, P. K. Srijith, Sunil Gupta
2023	C	`conf`	Domain Generalization with Interpolation Robustness. ACML Ragja Palakkadavath, Thanh Nguyen-Tang, Hung Le, Svetha Venkatesh, Sunil Gupta
2023	J	`jnl`	EMOTE: An Explainable architecture for Modelling the Other Through Empathy. CoRR Manisha Senadeera, Thommen Karimpanal George, Sunil Gupta, Stephan Jacobs, Santu Rana
2023	J	`jnl`	Gradient Descent in Neural Networks as Sequential Learning in RKBS. CoRR Alistair Shilton, Sunil Gupta, Santu Rana, Svetha Venkatesh
2023	A*	`conf`	Gradient Descent in Neural Networks as Sequential Learning in Reproducing Kernel Banach Space. ICML Alistair Shilton, Sunil Gupta, Santu Rana, Svetha Venkatesh
2023	A	`conf`	Guiding Visual Question Answering with Attention Priors. WACV Thao Minh Le, Vuong Le, Sunil Gupta, Svetha Venkatesh, Truyen Tran
2023	J	`jnl`	LaGR-SEQ: Language-Guided Reinforcement Learning with Sample-Efficient Querying. CoRR Thommen George Karimpanal, Buddhika Laknath Semage, Santu Rana, Hung Le, Truyen Tran, Sunil Gupta, Svetha Venkatesh
2023	J	`jnl`	Learn to Unlearn for Deep Neural Networks: Minimizing Unlearning Interference with Gradient Projection. CoRR Tuan Hoang, Santu Rana, Sunil Gupta, Svetha Venkatesh
2023	A*	`conf`	Multi-weather Image Restoration via Domain Translation. ICCV Prashant W. Patil, Sunil Gupta, Santu Rana, Svetha Venkatesh, Subrahmanyam Murala
2023	J	`jnl`	Neural-BO: A Black-box Optimization Algorithm using Deep Neural Networks. CoRR Dat Phan-Trong, Hung Tran-The, Sunil Gupta
2023	J	`jnl`	NeuralBO: A black-box optimization algorithm using deep neural networks. Neurocomputing Dat Phan-Trong, Hung Tran-The, Sunil Gupta
2023	A*	`conf`	On Instance-Dependent Bounds for Offline Reinforcement Learning with Linear Function Approximation. AAAI Thanh Nguyen-Tang, Ming Yin, Sunil Gupta, Svetha Venkatesh, Raman Arora
2023	J	`jnl`	Predictive Modeling through Hyper-Bayesian Optimization. CoRR Manisha Senadeera, Santu Rana, Sunil Gupta, Svetha Venkatesh
2023	J	`jnl`	Root Cause Explanation of Outliers under Noisy Mechanisms. CoRR Phuoc Nguyen, Truyen Tran, Sunil Gupta, Thin Nguyen, Svetha Venkatesh
2023	J	`jnl`	Unified Multi-Weather Visibility Restoration. IEEE Trans. Multim. Ashutosh Kulkarni, Prashant W. Patil, Subrahmanyam Murala, Sunil Gupta
2022	—	`conf`	Black-Box Few-Shot Knowledge Distillation. ECCV (21) Dang Nguyen, Sunil Gupta, Kien Do, Svetha Venkatesh
2022	J	`jnl`	Black-box Few-shot Knowledge Distillation. CoRR Dang Nguyen, Sunil Gupta, Kien Do, Svetha Venkatesh
2022	J	`jnl`	Continual Learning with Dependency Preserving Hypernetworks. CoRR Dupati Srikar Chandra, Sakshi Varshney, P. K. Srijith, Sunil Gupta
2022	J	`jnl`	Defense Against Multi-target Trojan Attacks. CoRR Haripriya Harikumar, Santu Rana, Kien Do, Sunil Gupta, Wei Zong, Willy Susilo, Svetha Venkatesh
2022	J	`jnl`	Dual-frame spatio-temporal feature modulation for video enhancement. Pattern Recognit. Prashant W. Patil, Sunil Gupta, Santu Rana, Svetha Venkatesh
2022	A*	`conf`	Expected Improvement for Contextual Bandits. NeurIPS Hung Tran-The, Sunil Gupta, Santu Rana, Tuan Truong, Long Tran-Thanh, Svetha Venkatesh
2022	J	`jnl`	Fast Conditional Network Compression Using Bayesian HyperNetworks. CoRR Phuoc Nguyen, Truyen Tran, Ky Le, Sunil Gupta, Santu Rana, Dang Nguyen, Trong Nguyen, Shannon Ryan, Svetha Venkatesh
2022	J	`jnl`	Guiding Visual Question Answering with Attention Priors. CoRR Thao Minh Le, Vuong Le, Sunil Gupta, Svetha Venkatesh, Truyen Tran
2022	A*	`conf`	Learning to Constrain Policy Optimization with Virtual Trust Region. NeurIPS Hung Le, Thommen Karimpanal George, Majid Abdolshah, Dung Nguyen, Kien Do, Sunil Gupta, Svetha Venkatesh
2022	J	`jnl`	Memory-Constrained Policy Optimization. CoRR Hung Le, Thommen George Karimpanal, Majid Abdolshah, Dung Nguyen, Kien Do, Sunil Gupta, Svetha Venkatesh
2022	A*	`conf`	Offline Neural Contextual Bandits: Pessimism, Optimization and Generalization. ICLR Thanh Nguyen-Tang, Sunil Gupta, A. Tuan Nguyen, Svetha Venkatesh
2022	J	`jnl`	On Instance-Dependent Bounds for Offline Reinforcement Learning with Linear Function Approximation. CoRR Thanh Nguyen-Tang, Ming Yin, Sunil Gupta, Svetha Venkatesh, Raman Arora
2022	J	`jnl`	On Sample Complexity of Offline Reinforcement Learning with Deep ReLU Networks in Besov Spaces. Trans. Mach. Learn. Res. Thanh Nguyen-Tang, Sunil Gupta, Hung Tran-The, Svetha Venkatesh
2022	J	`jnl`	Prescriptive analytics with differential privacy. Int. J. Data Sci. Anal. Haripriya Harikumar, Santu Rana, Sunil Gupta, Thin Nguyen, Ramachandra Kaimal, Svetha Venkatesh
2022	—	`conf`	Real-Time Skill Discovery in Intelligent Virtual Assistants. PAKDD (1) Preeti Gopal, Sunil Gupta, Santu Rana, Vuong Le, Trong Nguyen, Svetha Venkatesh
2022	A	`conf`	Regret Bounds for Expected Improvement Algorithms in Gaussian Process Bandit Optimization. AISTATS Hung Tran-The, Sunil Gupta, Santu Rana, Svetha Venkatesh
2022	J	`jnl`	Regret Bounds for Expected Improvement Algorithms in Gaussian Process Bandit Optimization. CoRR Hung Tran-The, Sunil Gupta, Santu Rana, Svetha Venkatesh
2022	—	`conf`	Semantic Control of Generative Musical Attributes. ISMIR Stewart Greenhill, Majid Abdolshah, Vuong Le, Sunil Gupta, Svetha Venkatesh
2022	A	`conf`	Sympathy-based Reinforcement Learning Agents. AAMAS Manisha Senadeera, Thommen George Karimpanal, Sunil Gupta, Santu Rana
2022	A*	`conf`	TRF: Learning Kernels with Tuned Random Features. AAAI Alistair Shilton, Sunil Gupta, Santu Rana, Arun Kumar Anjanapura Venkatesh, Svetha Venkatesh
2022	J	`jnl`	Verification of integrity of deployed deep learning models using Bayesian Optimization. Knowl. Based Syst. Deepthi Praveenlal Kuttichira, Sunil Gupta, Dang Nguyen, Santu Rana, Svetha Venkatesh
2022	—	`conf`	Video Restoration Framework and Its Meta-adaptations to Data-Poor Conditions. ECCV (28) Prashant W. Patil, Sunil Gupta, Santu Rana, Svetha Venkatesh
2021	J	`jnl`	A Field Guide to Scientific XAI: Transparent and Interpretable Deep Learning for Bioinformatics Research. CoRR Thomas P. Quinn, Sunil Gupta, Svetha Venkatesh, Vuong Le
2021	A*	`conf`	A New Representation of Successor Features for Transfer across Dissimilar Environments. ICML Majid Abdolshah, Hung Le, Thommen George Karimpanal, Sunil Gupta, Santu Rana, Svetha Venkatesh
2021	J	`jnl`	A New Representation of Successor Features for Transfer across Dissimilar Environments. CoRR Majid Abdolshah, Hung Le, Thommen George Karimpanal, Sunil Gupta, Santu Rana, Svetha Venkatesh
2021	J	`jnl`	ALT-MAS: A Data-Efficient Framework for Active Testing of Machine Learning Algorithms. CoRR Huong Ha, Sunil Gupta, Santu Rana, Svetha Venkatesh
2021	J	`jnl`	Adaptive cost-aware Bayesian optimization. Knowl. Based Syst. Phuc Luong, Dang Nguyen, Sunil Gupta, Santu Rana, Svetha Venkatesh
2021	J	`jnl`	An Unified Recurrent Video Object Segmentation Framework for Various Surveillance Environments. IEEE Trans. Image Process. Prashant W. Patil, Akshay Dudhane, Ashutosh Kulkarni, Subrahmanyam Murala, Anil Balaji Gonde, Sunil Gupta
2021	J	`jnl`	Balanced Q-learning: Combining the Influence of Optimistic and Pessimistic Targets. CoRR Thommen George Karimpanal, Hung Le, Majid Abdolshah, Santu Rana, Sunil Gupta, Truyen Tran, Svetha Venkatesh
2021	A*	`conf`	Bayesian Optimistic Optimisation with Exponentially Decaying Regret. ICML Hung Tran-The, Sunil Gupta, Santu Rana, Svetha Venkatesh
2021	J	`jnl`	Bayesian Optimistic Optimisation with Exponentially Decaying Regret. CoRR Hung Tran-The, Sunil Gupta, Santu Rana, Svetha Venkatesh
2021	J	`jnl`	Combining Online Learning and Offline Learning for Contextual Bandits with Deficient Support. CoRR Hung Tran-The, Sunil Gupta, Thanh Nguyen-Tang, Santu Rana, Svetha Venkatesh
2021	A*	`conf`	Distributional Reinforcement Learning via Moment Matching. AAAI Thanh Nguyen-Tang, Sunil Gupta, Svetha Venkatesh
2021	J	`jnl`	Fairness improvement for black-box classifiers with Gaussian process. Inf. Sci. Dang Nguyen, Sunil Gupta, Santu Rana, Alistair Shilton, Svetha Venkatesh
2021	—	`conf`	Fast Conditional Network Compression Using Bayesian HyperNetworks. ECML/PKDD (3) Phuoc Nguyen, Truyen Tran, Ky Le, Sunil Gupta, Santu Rana, Dang Nguyen, Trong Nguyen, Shannon Ryan, Svetha Venkatesh
2021	A*	`conf`	High Dimensional Level Set Estimation with Bayesian Neural Network. AAAI Huong Ha, Sunil Gupta, Santu Rana, Svetha Venkatesh
2021	A*	`conf`	Kernel Functional Optimisation. NeurIPS Arun Kumar Anjanapura Venkatesh, Alistair Shilton, Santu Rana, Sunil Gupta, Svetha Venkatesh
2021	—	`conf`	Knowledge Distillation with Distribution Mismatch. ECML/PKDD (2) Dang Nguyen, Sunil Gupta, Trong Nguyen, Santu Rana, Phuoc Nguyen, Truyen Tran, Ky Le, Shannon Ryan, Svetha Venkatesh
2021	J	`jnl`	Offline Neural Contextual Bandits: Pessimism, Optimization and Generalization. CoRR Thanh Nguyen-Tang, Sunil Gupta, A. Tuan Nguyen, Svetha Venkatesh
2021	J	`jnl`	On Finite-Sample Analysis of Offline Reinforcement Learning with Deep ReLU Networks. CoRR Thanh Nguyen-Tang, Sunil Gupta, Hung Tran-The, Svetha Venkatesh
2021	J	`jnl`	Personalized single-cell networks: a framework to predict the response of any gene to any drug for any patient. BioData Min. Haripriya Harikumar, Thomas P. Quinn, Santu Rana, Sunil Gupta, Svetha Venkatesh
2021	J	`jnl`	Plug and Play, Model-Based Reinforcement Learning. CoRR Majid Abdolshah, Hung Le, Thommen George Karimpanal, Sunil Gupta, Santu Rana, Svetha Venkatesh
2021	J	`jnl`	Semantic Host-free Trojan Attack. CoRR Haripriya Harikumar, Kien Do, Santu Rana, Sunil Gupta, Svetha Venkatesh
2021	—	`conf`	Sparse Spectrum Gaussian Process for Bayesian Optimization. PAKDD (2) Ang Yang, Cheng Li, Santu Rana, Sunil Gupta, Svetha Venkatesh
2021	—	`conf`	Variational Hyper-encoding Networks. ECML/PKDD (2) Phuoc Nguyen, Truyen Tran, Sunil Gupta, Santu Rana, Hieu-Chi Dam, Svetha Venkatesh
2020	A	`conf`	Accelerated Bayesian Optimisation through Weight-Prior Tuning. AISTATS 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	J	`jnl`	Batch Bayesian optimization using multi-scale search. Knowl. Based Syst. Tinu Theckel Joy, Santu Rana, Sunil Gupta, Svetha Venkatesh
2020	J	`jnl`	Bayesian Optimization for Adaptive Experimental Design: A Review. IEEE Access Stewart Greenhill, Santu Rana, Sunil Gupta, Pratibha Vellanki, Svetha Venkatesh
2020	A*	`conf`	Bayesian Optimization for Categorical and Category-Specific Continuous Inputs. AAAI Dang Nguyen, Sunil Gupta, Santu Rana, Alistair Shilton, Svetha Venkatesh
2020	—	`conf`	Bayesian Optimization with Missing Inputs. ECML/PKDD (2) Phuc Luong, Dang Nguyen, Sunil Gupta, Santu Rana, Svetha Venkatesh
2020	J	`jnl`	Bayesian Optimization with Missing Inputs. CoRR Phuc Luong, Dang Nguyen, Sunil Gupta, Santu Rana, Svetha Venkatesh
2020	J	`jnl`	Bayesian optimisation in unknown bounded search domains. Knowl. Based Syst. Julian Berk, Sunil Gupta, Santu Rana, Vu Nguyen, Svetha Venkatesh
2020	J	`jnl`	Bayesian strategy selection identifies optimal solutions to complex problems using an example from GP prescribing. npj Digit. Medicine Steven Allender, Joshua Hayward, Sunil Gupta, A. Sanigorski, Santu Rana, Hugh Seward, Stephan Jacobs, Svetha Venkatesh
2020	A*	`conf`	DeepCoDA: personalized interpretability for compositional health data. ICML Thomas P. Quinn, Dang Nguyen, Santu Rana, Sunil Gupta, Svetha Venkatesh
2020	J	`jnl`	DeepCoDA: personalized interpretability for compositional health data. CoRR Thomas P. Quinn, Dang Nguyen, Santu Rana, Sunil Gupta, Svetha Venkatesh
2020	J	`jnl`	Distributional Reinforcement Learning with Maximum Mean Discrepancy. CoRR Thanh Tang Nguyen, Sunil Gupta, Svetha Venkatesh
2020	A	`conf`	Distributionally Robust Bayesian Quadrature Optimization. AISTATS Thanh Tang Nguyen, Sunil Gupta, Huong Ha, Santu Rana, Svetha Venkatesh
2020	J	`jnl`	Distributionally Robust Bayesian Quadrature Optimization. CoRR Thanh Tang Nguyen, Sunil Gupta, Huong Ha, Santu Rana, Svetha Venkatesh
2020	B	`conf`	Factor Screening using Bayesian Active Learning and Gaussian Process Meta-Modelling. ICPR Cheng Li, Santu Rana, Andrew Gill, Dang Nguyen, Sunil Gupta, Svetha Venkatesh
2020	J	`jnl`	Fast hyperparameter tuning using Bayesian optimization with directional derivatives. Knowl. Based Syst. Tinu Theckel Joy, Santu Rana, Sunil Gupta, Svetha Venkatesh
2020	J	`jnl`	High Dimensional Level Set Estimation with Bayesian Neural Network. CoRR Huong Ha, Sunil Gupta, Santu Rana, Svetha Venkatesh
2020	J	`jnl`	HyperVAE: A Minimum Description Length Variational Hyper-Encoding Network. CoRR Phuoc Nguyen, Truyen Tran, Sunil Gupta, Santu Rana, Hieu-Chi Dam, Svetha Venkatesh
2020	J	`jnl`	Incorporating Expert Prior Knowledge into Experimental Design via Posterior Sampling. CoRR Cheng Li, Sunil Gupta, Santu Rana, Vu Nguyen, Antonio Robles-Kelly, Svetha Venkatesh
2020	J	`jnl`	Incorporating Expert Prior in Bayesian Optimisation via Space Warping. CoRR Anil Ramachandran, Sunil Gupta, Santu Rana, Cheng Li, Svetha Venkatesh
2020	J	`jnl`	Incorporating expert prior in Bayesian optimisation via space warping. Knowl. Based Syst. Anil Ramachandran, Sunil Gupta, Santu Rana, Cheng Li, Svetha Venkatesh
2020	B	`conf`	Learning Transferable Domain Priors for Safe Exploration in Reinforcement Learning. IJCNN Thommen George Karimpanal, Santu Rana, Sunil Gupta, Truyen Tran, Svetha Venkatesh
2020	—	`conf`	Level Set Estimation with Search Space Warping. PAKDD (2) Manisha Senadeera, Santu Rana, Sunil Gupta, Svetha Venkatesh
2020	J	`jnl`	Logically Consistent Loss for Visual Question Answering. CoRR Anh-Cat Le-Ngo, Truyen Tran, Santu Rana, Sunil Gupta, Svetha Venkatesh
2020	A*	`conf`	Randomised Gaussian Process Upper Confidence Bound for Bayesian Optimisation. IJCAI Julian Berk, Sunil Gupta, Santu Rana, Svetha Venkatesh
2020	J	`jnl`	Randomised Gaussian Process Upper Confidence Bound for Bayesian Optimisation. CoRR Julian Berk, Sunil Gupta, Santu Rana, Svetha Venkatesh
2020	—	`conf`	Scalable Backdoor Detection in Neural Networks. ECML/PKDD (2) Haripriya Harikumar, Vuong Le, Santu Rana, Sourangshu Bhattacharya, Sunil Gupta, Svetha Venkatesh
2020	J	`jnl`	Scalable Backdoor Detection in Neural Networks. CoRR Haripriya Harikumar, Vuong Le, Santu Rana, Sourangshu Bhattacharya, Sunil Gupta, Svetha Venkatesh
2020	J	`jnl`	Sequential Subspace Search for Functional Bayesian Optimization Incorporating Experimenter Intuition. CoRR Alistair Shilton, Sunil Gupta, Santu Rana, Svetha Venkatesh
2020	A*	`conf`	Sub-linear Regret Bounds for Bayesian Optimisation in Unknown Search Spaces. NeurIPS Hung Tran-The, Sunil Gupta, Santu Rana, Huong Ha, Svetha Venkatesh
2020	J	`jnl`	Sub-linear Regret Bounds for Bayesian Optimisation in Unknown Search Spaces. CoRR Hung Tran-The, Sunil Gupta, Santu Rana, Huong Ha, Svetha Venkatesh
2020	A*	`conf`	Trading Convergence Rate with Computational Budget in High Dimensional Bayesian Optimization. AAAI Hung Tran-The, Sunil Gupta, Santu Rana, Svetha Venkatesh
2020	—	`conf`	Unsupervised Anomaly Detection on Temporal Multiway Data. SSCI Duc Nguyen, Phuoc Nguyen, Kien Do, Santu Rana, Sunil Gupta, Truyen Tran
2020	J	`jnl`	Unsupervised Anomaly Detection on Temporal Multiway Data. CoRR Duc Nguyen, Phuoc Nguyen, Kien Do, Santu Rana, Sunil Gupta, Truyen Tran
2019	J	`jnl`	A flexible transfer learning framework for Bayesian optimization with convergence guarantee. Expert Syst. Appl. Tinu Theckel Joy, Santu Rana, Sunil Gupta, Svetha Venkatesh
2019	J	`jnl`	Accelerating Experimental Design by Incorporating Experimenter Hunches. CoRR 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
2019	A*	`conf`	Bayesian Functional Optimisation with Shape Prior. AAAI Pratibha Vellanki, Santu Rana, Sunil Gupta, David Rubin de Celis Leal, Alessandra Sutti, Murray Height, Svetha Venkatesh
2019	—	`conf`	Bayesian Optimisation for Objective Functions with Varying Smoothness. Australasian Conference on Artificial Intelligence A. V. Arun Kumar, Santu Rana, Cheng Li, Sunil Gupta, Alistair Shilton, Svetha Venkatesh
2019	J	`jnl`	Bayesian Optimization for Categorical and Category-Specific Continuous Inputs. CoRR Dang Nguyen, Sunil Gupta, Santu Rana, Alistair Shilton, Svetha Venkatesh
2019	—	`conf`	Bayesian Optimization with Discrete Variables. Australasian Conference on Artificial Intelligence Phuc Luong, Sunil Gupta, Dang Nguyen, Santu Rana, Svetha Venkatesh
2019	A*	`conf`	Bayesian Optimization with Unknown Search Space. NeurIPS Huong Ha, Santu Rana, Sunil Gupta, Thanh Tang Nguyen, Hung Tran-The, Svetha Venkatesh
2019	J	`jnl`	Bayesian Optimization with Unknown Search Space. CoRR Huong Ha, Santu Rana, Sunil Gupta, Thanh Tang Nguyen, Hung Tran-The, Svetha Venkatesh
2019	J	`jnl`	Cost-aware Multi-objective Bayesian optimisation. CoRR Majid Abdolshah, Alistair Shilton, Santu Rana, Sunil Gupta, Svetha Venkatesh
2019	—	`conf`	Detection of Compromised Models Using Bayesian Optimization. Australasian Conference on Artificial Intelligence Deepthi Praveenlal Kuttichira, Sunil Gupta, Dang Nguyen, Santu Rana, Svetha Venkatesh
2019	A*	`conf`	Efficient Bayesian Optimization for Uncertainty Reduction Over Perceived Optima Locations. ICDM Vu Nguyen, Sunil Gupta, Santu Rana, My T. Thai, Cheng Li, Svetha Venkatesh
2019	—	`conf`	Explaining Black-Box Models Using Interpretable Surrogates. PRICAI (1) Deepthi Praveenlal Kuttichira, Sunil Gupta, Cheng Li, Santu Rana, Svetha Venkatesh
2019	J	`jnl`	Fast Hyperparameter Tuning using Bayesian Optimization with Directional Derivatives. CoRR Tinu Theckel Joy, Santu Rana, Sunil Gupta, Svetha Venkatesh
2019	J	`jnl`	Filtering Bayesian optimization approach in weakly specified search space. Knowl. Inf. Syst. Vu Nguyen, Sunil Gupta, Santu Rana, Cheng Li, Svetha Venkatesh
2019	A	`conf`	Incomplete Conditional Density Estimation for Fast Materials Discovery. SDM Phuoc Nguyen, Truyen Tran, Sunil Gupta, Santu Rana, Matthew Barnett, Svetha Venkatesh
2019	—	`conf`	Information-Theoretic Multi-task Learning Framework for Bayesian Optimisation. Australasian Conference on Artificial Intelligence Anil Ramachandran, Sunil Gupta, Santu Rana, Svetha Venkatesh
2019	J	`jnl`	Learning Transferable Domain Priors for Safe Exploration in Reinforcement Learning. CoRR Thommen George Karimpanal, Santu Rana, Sunil Gupta, Truyen Tran, Svetha Venkatesh
2019	A*	`conf`	Multi-objective Bayesian optimisation with preferences over objectives. NeurIPS Majid Abdolshah, Alistair Shilton, Santu Rana, Sunil Gupta, Svetha Venkatesh
2019	J	`jnl`	Multi-objective Bayesian optimisation with preferences over objectives. CoRR Majid Abdolshah, Alistair Shilton, Santu Rana, Sunil Gupta, Svetha Venkatesh
2019	J	`jnl`	Sparse Spectrum Gaussian Process for Bayesian Optimisation. CoRR Ang Yang, Cheng Li, Santu Rana, Sunil Gupta, Svetha Venkatesh
2019	J	`jnl`	Stable Bayesian Optimisation via Direct Stability Quantification. CoRR Alistair Shilton, Sunil Gupta, Santu Rana, Svetha Venkatesh, Majid Abdolshah, Dang Nguyen
2019	J	`jnl`	Trading Convergence Rate with Computational Budget in High Dimensional Bayesian Optimization. CoRR Hung Tran-The, Sunil Gupta, Santu Rana, Svetha Venkatesh
2018	—	`conf`	A Privacy Preserving Bayesian Optimization with High Efficiency. PAKDD (3) Thanh Dai Nguyen, Sunil Gupta, Santu Rana, Svetha Venkatesh
2018	A*	`conf`	Accelerating Experimental Design by Incorporating Experimenter Hunches. ICDM 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	A*	`conf`	Algorithmic Assurance: An Active Approach to Algorithmic Testing using Bayesian Optimisation. NeurIPS Shivapratap Gopakumar, Sunil Gupta, Santu Rana, Vu Nguyen, Svetha Venkatesh
2018	J	`jnl`	Bayesian functional optimisation with shape prior. CoRR Pratibha Vellanki, Santu Rana, Sunil Gupta, David Rubin de Celis Leal, Alessandra Sutti, Murray Height, Svetha Venkatesh
2018	A*	`conf`	Differentially Private Prescriptive Analytics. ICDM Haripriya Harikumar, Santu Rana, Sunil Gupta, Thin Nguyen, Ramachandra Kaimal, Svetha Venkatesh
2018	B	`conf`	Efficient Bayesian Optimisation Using Derivative Meta-model. PRICAI Ang Yang, Cheng Li, Santu Rana, Sunil Gupta, Svetha Venkatesh
2018	B	`conf`	Expected Hypervolume Improvement with Constraints. ICPR Majid Abdolshah, Alistair Shilton, Santu Rana, Sunil Gupta, Svetha Venkatesh
2018	A	`conf`	Exploiting Strategy-Space Diversity for Batch Bayesian Optimization. AISTATS Sunil Gupta, Alistair Shilton, Santu Rana, Svetha Venkatesh
2018	—	`conf`	Exploration Enhanced Expected Improvement for Bayesian Optimization. ECML/PKDD (2) Julian Berk, Vu Nguyen, Sunil Gupta, Santu Rana, Svetha Venkatesh
2018	J	`jnl`	Hybrid Generative-Discriminative Models for Inverse Materials Design. CoRR Phuoc Nguyen, Truyen Tran, Sunil Gupta, Santu Rana, Svetha Venkatesh
2018	—	`conf`	Information-Theoretic Transfer Learning Framework for Bayesian Optimisation. ECML/PKDD (2) Anil Ramachandran, Sunil Gupta, Santu Rana, Svetha Venkatesh
2018	J	`jnl`	Kernel Pre-Training in Feature Space via m-Kernels. CoRR 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
2018	A	`conf`	Multi-Target Optimisation via Bayesian Optimisation and Linear Programming. UAI Alistair Shilton, Santu Rana, Sunil Gupta, Svetha Venkatesh
2018	J	`jnl`	Practical Batch Bayesian Optimization for Less Expensive Functions. CoRR Vu Nguyen, Sunil Gupta, Santu Rana, Cheng Li, Svetha Venkatesh
2018	—	`conf`	Prescriptive Analytics Through Constrained Bayesian Optimization. PAKDD (1) Haripriya Harikumar, Santu Rana, Sunil Gupta, Thin Nguyen, Ramachandra Kaimal, Svetha Venkatesh
2018	—	`conf`	Selecting Optimal Source for Transfer Learning in Bayesian Optimisation. PRICAI (1) Anil Ramachandran, Sunil Gupta, Santu Rana, Svetha Venkatesh
2018	—	`conf`	Sparse Approximation for Gaussian Process with Derivative Observations. Australasian Conference on Artificial Intelligence Ang Yang, Cheng Li, Santu Rana, Sunil Gupta, Svetha Venkatesh
2018	J	`jnl`	Stable Bayesian optimization. Int. J. Data Sci. Anal. Thanh Dai Nguyen, Sunil Gupta, Santu Rana, Svetha Venkatesh
2017	J	`jnl`	A Framework for Mixed-Type Multioutcome Prediction With Applications in Healthcare. IEEE J. Biomed. Health Informatics Budhaditya Saha, Sunil Gupta, Dinh Q. Phung, Svetha Venkatesh
2017	A*	`conf`	Bayesian Optimization in Weakly Specified Search Space. ICDM Vu Nguyen, Sunil Gupta, Santu Rana, Cheng Li, Svetha Venkatesh
2017	J	`jnl`	Budgeted Batch Bayesian Optimization With Unknown Batch Sizes. CoRR Vu Nguyen, Santu Rana, Sunil Gupta, Cheng Li, Svetha Venkatesh
2017	J	`jnl`	Effective sparse imputation of patient conditions in electronic medical records for emergency risk predictions. Knowl. Inf. Syst. Budhaditya Saha, Sunil Gupta, Dinh Q. Phung, Svetha Venkatesh
2017	A*	`conf`	High Dimensional Bayesian Optimization using Dropout. IJCAI Cheng Li, Sunil Gupta, Santu Rana, Vu Nguyen, Svetha Venkatesh, Alistair Shilton
2017	A*	`conf`	High Dimensional Bayesian Optimization with Elastic Gaussian Process. ICML Santu Rana, Cheng Li, Sunil Gupta, Vu Nguyen, Svetha Venkatesh
2017	J	`jnl`	Nonparametric discovery and analysis of learning patterns and autism subgroups from therapeutic data. Knowl. Inf. Syst. Pratibha Vellanki, Thi V. Duong, Sunil Gupta, Svetha Venkatesh, Dinh Q. Phung
2017	—	`conf`	Process-constrained batch Bayesian optimisation. NIPS Pratibha Vellanki, Santu Rana, Sunil Gupta, David Rubin, Alessandra Sutti, Thomas Dorin, Murray Height, Paul G. Sanders, Svetha Venkatesh
2017	A	`conf`	Regret Bounds for Transfer Learning in Bayesian Optimisation. AISTATS Alistair Shilton, Sunil Gupta, Santu Rana, Svetha Venkatesh
2017	C	`conf`	Regret for Expected Improvement over the Best-Observed Value and Stopping Condition. ACML Vu Nguyen, Sunil Gupta, Santu Rana, Cheng Li, Svetha Venkatesh
2017	—	`conf`	Stable Bayesian Optimization. PAKDD (2) Thanh Dai Nguyen, Sunil Gupta, Santu Rana, Svetha Venkatesh
2016	C	`conf`	A Bayesian Nonparametric Approach for Multi-label Classification. ACML Vu Nguyen, Sunil Gupta, Santu Rana, Cheng Li, Svetha Venkatesh
2016	J	`jnl`	A new transfer learning framework with application to model-agnostic multi-task learning. Knowl. Inf. Syst. Sunil Gupta, Santu Rana, Budhaditya Saha, Dinh Q. Phung, Svetha Venkatesh
2016	B	`conf`	Bayesian nonparametric Multiple Instance Regression. ICPR Saravanan Subramanian, Santu Rana, Sunil Gupta, Palaniappan Bagavathi Sivakumar, C. Shunmuga Velayutham, Svetha Venkatesh
2016	—	`conf`	Cascade Bayesian Optimization. Australasian Conference on Artificial Intelligence Thanh Dai Nguyen, Sunil Gupta, Santu Rana, Vu Nguyen, Svetha Venkatesh, Kyle J. Deane, Paul G. Sanders
2016	C	`conf`	Extracting Key Challenges in Achieving Sobriety Through Shared Subspace Learning. ADMA Haripriya Harikumar, Thin Nguyen, Santu Rana, Sunil Gupta, Ramachandra Kaimal, Svetha Venkatesh
2016	B	`conf`	Hyperparameter tuning for big data using Bayesian optimisation. ICPR Tinu Theckel Joy, Santu Rana, Sunil Gupta, Svetha Venkatesh
2016	J	`jnl`	Modelling multilevel data in multimedia: A hierarchical factor analysis approach. Multim. Tools Appl. Sunil Gupta, Dinh Q. Phung, Svetha Venkatesh
2016	B	`conf`	Multiple adverse effects prediction in longitudinal cancer treatment. ICPR Cheng Li, Sunil Gupta, Santu Rana, Vu Nguyen, Svetha Venkatesh, David Ashely, Trish Livingston
2016	J	`jnl`	Multiple task transfer learning with small sample sizes. Knowl. Inf. Syst. Budhaditya Saha, Sunil Gupta, Dinh Q. Phung, Svetha Venkatesh
2016	J	`jnl`	Nonparametric discovery of movement patterns from accelerometer signals. Pattern Recognit. Lett. Nguyen Cong Thuong, Sunil Gupta, Svetha Venkatesh, Dinh Q. Phung
2016	—	`conf`	Privacy Aware K-Means Clustering with High Utility. PAKDD (2) Thanh Dai Nguyen, Sunil Gupta, Santu Rana, Svetha Venkatesh
2016	B	`conf`	Stable clinical prediction using graph support vector machines. ICPR Iman Kamkar, Sunil Gupta, Cheng Li, Dinh Q. Phung, Svetha Venkatesh
2016	—	`conf`	Toxicity Prediction in Cancer Using Multiple Instance Learning in a Multi-task Framework. PAKDD (1) Cheng Li, Sunil Gupta, Santu Rana, Wei Luo, Svetha Venkatesh, David Ashely, Dinh Q. Phung
2016	B	`conf`	Transfer learning for rare cancer problems via Discriminative Sparse Gaussian Graphical model. ICPR Budhaditya Saha, Sunil Gupta, Dinh Q. Phung, Svetha Venkatesh
2016	C	`conf`	Understanding Behavioral Differences Between Short and Long-Term Drinking Abstainers from Social Media. ADMA Haripriya Harikumar, Thin Nguyen, Sunil Gupta, Santu Rana, Ramachandra Kaimal, Svetha Venkatesh
2015	J	`jnl`	A predictive framework for modeling healthcare data with evolving clinical interventions. Stat. Anal. Data Min. Santu Rana, Sunil Gupta, Dinh Q. Phung, Svetha Venkatesh
2015	B	`conf`	Improved risk predictions via sparse imputation of patient conditions in electronic medical records. DSAA Budhaditya Saha, Sunil Gupta, Svetha Venkatesh
2015	A	`conf`	What shall I share and with Whom? - A Multi-Task Learning Formulation using Multi-Faceted Task Relationships. SDM Sunil Gupta, Santu Rana, Dinh Q. Phung, Svetha Venkatesh
2014	B	`conf`	A Bayesian Nonparametric Framework for Activity Recognition Using Accelerometer Data. ICPR Nguyen Cong Thuong, Sunil Gupta, Svetha Venkatesh, Dinh Q. Phung
2014	J	`jnl`	A framework for feature extraction from hospital medical data with applications in risk prediction. BMC Bioinform. Truyen Tran, Wei Luo, Dinh Q. Phung, Sunil Gupta, Santu Rana, Richard Kennedy, Ann Larkins, Svetha Venkatesh
2014	A*	`conf`	Fixed-lag particle filter for continuous context discovery using Indian Buffet Process. PerCom Nguyen Cong Thuong, Sunil Gupta, Svetha Venkatesh, Dinh Q. Phung
2013	A*	`conf`	Extraction of latent patterns and contexts from social honest signals using hierarchical Dirichlet processes. PerCom Nguyen Cong Thuong, Dinh Q. Phung, Sunil Gupta, Svetha Venkatesh
2013	—	`conf`	Interactive browsing system for anomaly video surveillance. ISSNIP Tien-Vu Nguyen, Dinh Q. Phung, Sunil Gupta, Svetha Venkatesh