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2020 – today
- 2024
[c101]Tuan Hoang, Hung Tran, Santu Rana, Sunil Gupta, Svetha Venkatesh:
Revisiting Sample Weights Based Method for Noisy-Label Detection and Classification. ACCV (1) 2024: 95-110- [c100]Kishan R. Nagiredla, Buddhika Laknath Semage, Arun Kumar Anjanapura Venkatesh, Thommen George Karimpanal, Santu Rana:
ECoDe: A Sample-Efficient Method for Co-design of Robotic Agents. AI (2) 2024: 3-15 - [c99]Kiran Purohit, Soumi Das, Sourangshu Bhattacharya, Santu Rana:
A Data-Driven Defense Against Edge-Case Model Poisoning Attacks on Federated Learning. ECAI 2024: 2162-2169 - [c98]Kien Do
, Dung Nguyen, Hung Le, Thao Le, Dang Nguyen, Haripriya Harikumar, Truyen Tran, Santu Rana, Svetha Venkatesh:
Revisiting the Dataset Bias Problem from a Statistical Perspective. ECAI 2024: 3120-3127 - [c97]Ajsal Shereef Palattuparambil, Thommen Karimpanal George, Santu Rana:
Personalisation via Dynamic Policy Fusion. HAI 2024: 459-461 - [c96]Banibrata Ghosh, Haripriya Harikumar, Khoa D. Doan, Svetha Venkatesh, Santu Rana:
Composite Concept Extraction Through Backdooring. ICPR (29) 2024: 276-290 - [c95]Manisha Senadeera, Thommen Karimpanal George, Stephan Jacobs, Sunil Gupta, Santu Rana:
EMOTE: An Explainable Architecture for Modelling the Other through Empathy. IJCAI 2024: 4876-4884 - [c94]A. V. Arun Kumar, Alistair Shilton, Sunil Gupta, Santu Rana, Stewart Greenhill, Svetha Venkatesh:
Enhanced Bayesian Optimization via Preferential Modeling of Abstract Properties. ECML/PKDD (6) 2024: 234-250 - [c93]Tuan Hoang, Santu Rana, Sunil Gupta, Svetha Venkatesh:
Learn to Unlearn for Deep Neural Networks: Minimizing Unlearning Interference with Gradient Projection. WACV 2024: 4807-4816 - [i60]Kien Do, Dung Nguyen, Hung Le, Thao Le, Dang Nguyen, Haripriya Harikumar, Truyen Tran, Santu Rana, Svetha Venkatesh:
Revisiting the Dataset Bias Problem from a Statistical Perspective. CoRR abs/2402.03577 (2024) - [i59]A. V. Arun Kumar, Alistair Shilton, Sunil Gupta, Santu Rana, Stewart Greenhill, Svetha Venkatesh:
Enhanced Bayesian Optimization via Preferential Modeling of Abstract Properties. CoRR abs/2402.17343 (2024) - [i58]Aly M. Kassem, Omar Mahmoud, Niloofar Mireshghallah, Hyunwoo Kim, Yulia Tsvetkov, Yejin Choi, Sherif Saad, Santu Rana:
Alpaca against Vicuna: Using LLMs to Uncover Memorization of LLMs. CoRR abs/2403.04801 (2024) - [i57]Alistair Shilton, Sunil Gupta, Santu Rana, Svetha Venkatesh:
Novel Kernel Models and Exact Representor Theory for Neural Networks Beyond the Over-Parameterized Regime. CoRR abs/2405.15254 (2024) - [i56]Banibrata Ghosh, Haripriya Harikumar, Khoa D. Doan, Svetha Venkatesh, Santu Rana:
Composite Concept Extraction through Backdooring. CoRR abs/2406.13411 (2024) - [i55]Ajsal Shereef Palattuparambil, Thommen George Karimpanal, Santu Rana:
Personalisation via Dynamic Policy Fusion. CoRR abs/2409.20016 (2024) - [i54]Tri Minh Nguyen, Sherif Abdulkader Tawfik, Truyen Tran, Sunil Gupta, Santu Rana, Svetha Venkatesh:
Efficient Symmetry-Aware Materials Generation via Hierarchical Generative Flow Networks. CoRR abs/2411.04323 (2024) - 2023
- [j22]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: 104021 (2023) - [c92]Maxence Hussonnois, Thommen George Karimpanal, Santu Rana:
Controlled Diversity with Preference : Towards Learning a Diverse Set of Desired Skills. AAMAS 2023: 1135-1143 - [c91]Prashant W. Patil, Sunil Gupta, Santu Rana, Svetha Venkatesh, Subrahmanyam Murala:
Multi-weather Image Restoration via Domain Translation. ICCV 2023: 21639-21648 - [c90]Alistair Shilton, Sunil Gupta, Santu Rana, Svetha Venkatesh:
Gradient Descent in Neural Networks as Sequential Learning in Reproducing Kernel Banach Space. ICML 2023: 31435-31488 - [i53]Alistair Shilton, Sunil Gupta, Santu Rana, Svetha Venkatesh:
Gradient Descent in Neural Networks as Sequential Learning in RKBS. CoRR abs/2302.00205 (2023) - [i52]Buddhika Laknath Semage, Thommen George Karimpanal, Santu Rana, Svetha Venkatesh:
Zero-shot Sim2Real Adaptation Across Environments. CoRR abs/2302.04013 (2023) - [i51]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 abs/2303.01684 (2023) - [i50]Maxence Hussonnois, Thommen George Karimpanal, Santu Rana:
Controlled Diversity with Preference : Towards Learning a Diverse Set of Desired Skills. CoRR abs/2303.04592 (2023) - [i49]Kiran Purohit, Soumi Das, Sourangshu Bhattacharya, Santu Rana:
LearnDefend: Learning to Defend against Targeted Model-Poisoning Attacks on Federated Learning. CoRR abs/2305.02022 (2023) - [i48]Manisha Senadeera, Thommen Karimpanal George, Sunil Gupta, Stephan Jacobs, Santu Rana:
EMOTE: An Explainable architecture for Modelling the Other Through Empathy. CoRR abs/2306.00295 (2023) - [i47]Manisha Senadeera, Santu Rana, Sunil Gupta, Svetha Venkatesh:
Predictive Modeling through Hyper-Bayesian Optimization. CoRR abs/2308.00285 (2023) - [i46]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 abs/2308.13542 (2023) - [i45]Kishan R. Nagiredla, Buddhika Laknath Semage, Thommen George Karimpanal, Arun Kumar A. V., Santu Rana:
Sample-Efficient Co-Design of Robotic Agents Using Multi-fidelity Training on Universal Policy Network. CoRR abs/2309.04085 (2023) - [i44]Tuan Hoang, Santu Rana, Sunil Gupta, Svetha Venkatesh:
Learn to Unlearn for Deep Neural Networks: Minimizing Unlearning Interference with Gradient Projection. CoRR abs/2312.04095 (2023) - 2022
- [j21]Haripriya Harikumar, Santu Rana, Sunil Gupta, Thin Nguyen, Ramachandra Kaimal, Svetha Venkatesh:
Prescriptive analytics with differential privacy. Int. J. Data Sci. Anal. 13(2): 123-138 (2022) - [j20]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: 108238 (2022) - [j19]Prashant W. Patil, Sunil Gupta, Santu Rana, Svetha Venkatesh:
Dual-frame spatio-temporal feature modulation for video enhancement. Pattern Recognit. 130: 108822 (2022) - [c89]Alistair Shilton, Sunil Gupta, Santu Rana, Arun Kumar Anjanapura Venkatesh, Svetha Venkatesh:
TRF: Learning Kernels with Tuned Random Features. AAAI 2022: 8286-8294 - [c88]Hung Tran-The, Sunil Gupta, Santu Rana, Svetha Venkatesh:
Regret Bounds for Expected Improvement Algorithms in Gaussian Process Bandit Optimization. AISTATS 2022: 8715-8737 - [c87]Manisha Senadeera, Thommen George Karimpanal, Sunil Gupta, Santu Rana:
Sympathy-based Reinforcement Learning Agents. AAMAS 2022: 1164-1172 - [c86]Prashant W. Patil, Sunil Gupta, Santu Rana, Svetha Venkatesh:
Video Restoration Framework and Its Meta-adaptations to Data-Poor Conditions. ECCV (28) 2022: 143-160 - [c85]Kien Do, Haripriya Harikumar, Hung Le, Dung Nguyen, Truyen Tran, Santu Rana, Dang Nguyen, Willy Susilo, Svetha Venkatesh:
Towards Effective and Robust Neural Trojan Defenses via Input Filtering. ECCV (5) 2022: 283-300 - [c84]Buddhika Laknath Semage, Thommen George Karimpanal, Santu Rana, Svetha Venkatesh:
Intuitive Physics Guided Exploration for Sample Efficient Sim2real Transfer. ICPR Workshops (2) 2022: 674-686 - [c83]Buddhika Laknath Semage, Thommen George Karimpanal, Santu Rana, Svetha Venkatesh:
Fast Model-based Policy Search for Universal Policy Networks. ICPR 2022: 2314-2320 - [c82]Buddhika Laknath Semage, Thommen George Karimpanal, Santu Rana, Svetha Venkatesh:
Uncertainty Aware System Identification with Universal Policies. ICPR 2022: 2321-2327 - [c81]Kien Do, Hung Le, Dung Nguyen, Dang Nguyen, Haripriya Harikumar, Truyen Tran, Santu Rana, Svetha Venkatesh:
Momentum Adversarial Distillation: Handling Large Distribution Shifts in Data-Free Knowledge Distillation. NeurIPS 2022 - [c80]Hung Tran-The, Sunil Gupta, Santu Rana, Tuan Truong, Long Tran-Thanh, Svetha Venkatesh:
Expected Improvement for Contextual Bandits. NeurIPS 2022 - [c79]Arun Kumar A. V., Santu Rana, Alistair Shilton, Svetha Venkatesh:
Human-AI Collaborative Bayesian Optimisation. NeurIPS 2022 - [c78]Preeti Gopal, Sunil Gupta, Santu Rana, Vuong Le, Trong Nguyen, Svetha Venkatesh:
Real-Time Skill Discovery in Intelligent Virtual Assistants. PAKDD (1) 2022: 315-327 - [i43]Buddhika Laknath Semage, Thommen George Karimpanal, Santu Rana, Svetha Venkatesh:
Fast Model-based Policy Search for Universal Policy Networks. CoRR abs/2202.05843 (2022) - [i42]Buddhika Laknath Semage, Thommen George Karimpanal, Santu Rana, Svetha Venkatesh:
Uncertainty Aware System Identification with Universal Policies. CoRR abs/2202.05844 (2022) - [i41]Kien Do, Haripriya Harikumar, Hung Le, Dung Nguyen, Truyen Tran, Santu Rana, Dang Nguyen, Willy Susilo, Svetha Venkatesh:
Towards Effective and Robust Neural Trojan Defenses via Input Filtering. CoRR abs/2202.12154 (2022) - [i40]Hung Tran-The, Sunil Gupta, Santu Rana, Svetha Venkatesh:
Regret Bounds for Expected Improvement Algorithms in Gaussian Process Bandit Optimization. CoRR abs/2203.07875 (2022) - [i39]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 abs/2205.06404 (2022) - [i38]Haripriya Harikumar, Santu Rana, Kien Do, Sunil Gupta, Wei Zong, Willy Susilo, Svetha Venkatesh:
Defense Against Multi-target Trojan Attacks. CoRR abs/2207.03895 (2022) - [i37]Kien Do, Hung Le, Dung Nguyen, Dang Nguyen, Haripriya Harikumar, Truyen Tran, Santu Rana, Svetha Venkatesh:
Momentum Adversarial Distillation: Handling Large Distribution Shifts in Data-Free Knowledge Distillation. CoRR abs/2209.10359 (2022) - 2021
- [j18]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) - [j17]Dang Nguyen, Sunil Gupta, Santu Rana, Alistair Shilton, Svetha Venkatesh:
Fairness improvement for black-box classifiers with Gaussian process. Inf. Sci. 576: 542-556 (2021) - [j16]Phuc Luong, Dang Nguyen, Sunil Gupta, Santu Rana, Svetha Venkatesh:
Adaptive cost-aware Bayesian optimization. Knowl. Based Syst. 232: 107481 (2021) - [c77]Huong Ha, Sunil Gupta, Santu Rana, Svetha Venkatesh:
High Dimensional Level Set Estimation with Bayesian Neural Network. AAAI 2021: 12095-12103 - [c76]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: 1-9 - [c75]Hung Tran-The, Sunil Gupta, Santu Rana, Svetha Venkatesh:
Bayesian Optimistic Optimisation with Exponentially Decaying Regret. ICML 2021: 10390-10400 - [c74]Wei Zong, Yang-Wai Chow, Willy Susilo, Santu Rana, Svetha Venkatesh:
Targeted Universal Adversarial Perturbations for Automatic Speech Recognition. ISC 2021: 358-373 - [c73]Arun Kumar Anjanapura Venkatesh, Alistair Shilton, Santu Rana, Sunil Gupta, Svetha Venkatesh:
Kernel Functional Optimisation. NeurIPS 2021: 4725-4737 - [c72]Ang Yang, Cheng Li, Santu Rana, Sunil Gupta, Svetha Venkatesh:
Sparse Spectrum Gaussian Process for Bayesian Optimization. PAKDD (2) 2021: 257-268 - [c71]Phuoc Nguyen, Truyen Tran, Sunil Gupta, Santu Rana, Hieu-Chi Dam, Svetha Venkatesh:
Variational Hyper-encoding Networks. ECML/PKDD (2) 2021: 100-115 - [c70]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: 250-265 - [c69]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: 330-345 - [i36]Huong Ha, Sunil Gupta, Santu Rana, Svetha Venkatesh:
ALT-MAS: A Data-Efficient Framework for Active Testing of Machine Learning Algorithms. CoRR abs/2104.04999 (2021) - [i35]Buddhika Laknath Semage, Thommen George Karimpanal, Santu Rana, Svetha Venkatesh:
Intuitive Physics Guided Exploration for Sample Efficient Sim2real Transfer. CoRR abs/2104.08795 (2021) - [i34]Hung Tran-The, Sunil Gupta, Santu Rana, Svetha Venkatesh:
Bayesian Optimistic Optimisation with Exponentially Decaying Regret. CoRR abs/2105.04332 (2021) - [i33]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 abs/2107.08426 (2021) - [i32]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 abs/2107.11533 (2021) - [i31]Majid Abdolshah, Hung Le, Thommen George Karimpanal, Sunil Gupta, Santu Rana, Svetha Venkatesh:
Plug and Play, Model-Based Reinforcement Learning. CoRR abs/2108.08960 (2021) - [i30]Haripriya Harikumar, Kien Do, Santu Rana, Sunil Gupta, Svetha Venkatesh:
Semantic Host-free Trojan Attack. CoRR abs/2110.13414 (2021) - [i29]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 abs/2111.02787 (2021) - 2020
- [j15]Stewart Greenhill, Santu Rana, Sunil Gupta, Pratibha Vellanki, Svetha Venkatesh:
Bayesian Optimization for Adaptive Experimental Design: A Review. IEEE Access 8: 13937-13948 (2020) - [j14]Tinu Theckel Joy, Santu Rana, Sunil Gupta, Svetha Venkatesh:
Batch Bayesian optimization using multi-scale search. Knowl. Based Syst. 187 (2020) - [j13]Julian Berk, Sunil Gupta, Santu Rana, Vu Nguyen, Svetha Venkatesh:
Bayesian optimisation in unknown bounded search domains. Knowl. Based Syst. 195: 105645 (2020) - [j12]Anil Ramachandran, Sunil Gupta, Santu Rana, Cheng Li, Svetha Venkatesh:
Incorporating expert prior in Bayesian optimisation via space warping. Knowl. Based Syst. 195: 105663 (2020) - [j11]Tinu Theckel Joy, Santu Rana, Sunil Gupta, Svetha Venkatesh:
Fast hyperparameter tuning using Bayesian optimization with directional derivatives. Knowl. Based Syst. 205: 106247 (2020) - [j10]Steven Allender, Joshua Hayward, Sunil Gupta, A. Sanigorski, Santu Rana, Hugh Seward, Stephan Jacobs, Svetha Venkatesh:
Bayesian strategy selection identifies optimal solutions to complex problems using an example from GP prescribing. npj Digit. Medicine 3 (2020) - [c68]Hung Tran-The, Sunil Gupta, Santu Rana, Svetha Venkatesh:
Trading Convergence Rate with Computational Budget in High Dimensional Bayesian Optimization. AAAI 2020: 2425-2432 - [c67]Dang Nguyen, Sunil Gupta, Santu Rana, Alistair Shilton, Svetha Venkatesh:
Bayesian Optimization for Categorical and Category-Specific Continuous Inputs. AAAI 2020: 5256-5263 - [c66]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: 635-645 - [c65]Thanh Tang Nguyen, Sunil Gupta, Huong Ha, Santu Rana, Svetha Venkatesh:
Distributionally Robust Bayesian Quadrature Optimization. AISTATS 2020: 1921-1931 - [c64]Thomas P. Quinn, Dang Nguyen, Santu Rana, Sunil Gupta, Svetha Venkatesh:
DeepCoDA: personalized interpretability for compositional health data. ICML 2020: 7877-7886 - [c63]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: 3288-3295 - [c62]Julian Berk, Sunil Gupta, Santu Rana, Svetha Venkatesh:
Randomised Gaussian Process Upper Confidence Bound for Bayesian Optimisation. IJCAI 2020: 2284-2290 - [c61]Thommen George Karimpanal, Santu Rana, Sunil Gupta, Truyen Tran, Svetha Venkatesh:
Learning Transferable Domain Priors for Safe Exploration in Reinforcement Learning. IJCNN 2020: 1-10 - [c60]Hung Tran-The, Sunil Gupta, Santu Rana, Huong Ha, Svetha Venkatesh:
Sub-linear Regret Bounds for Bayesian Optimisation in Unknown Search Spaces. NeurIPS 2020 - [c59]Manisha Senadeera, Santu Rana, Sunil Gupta, Svetha Venkatesh:
Level Set Estimation with Search Space Warping. PAKDD (2) 2020: 827-839 - [c58]Haripriya Harikumar, Vuong Le, Santu Rana, Sourangshu Bhattacharya, Sunil Gupta, Svetha Venkatesh:
Scalable Backdoor Detection in Neural Networks. ECML/PKDD (2) 2020: 289-304 - [c57]Phuc Luong, Dang Nguyen, Sunil Gupta, Santu Rana, Svetha Venkatesh:
Bayesian Optimization with Missing Inputs. ECML/PKDD (2) 2020: 691-706 - [c56]Duc Nguyen, Phuoc Nguyen, Kien Do, Santu Rana, Sunil Gupta, Truyen Tran:
Unsupervised Anomaly Detection on Temporal Multiway Data. SSCI 2020: 1059-1066 - [i28]Thanh Tang Nguyen, Sunil Gupta, Huong Ha, Santu Rana, Svetha Venkatesh:
Distributionally Robust Bayesian Quadrature Optimization. CoRR abs/2001.06814 (2020) - [i27]Cheng Li, Sunil Gupta, Santu Rana, Vu Nguyen, Antonio Robles-Kelly, Svetha Venkatesh:
Incorporating Expert Prior Knowledge into Experimental Design via Posterior Sampling. CoRR abs/2002.11256 (2020) - [i26]Anil Ramachandran, Sunil Gupta, Santu Rana, Cheng Li, Svetha Venkatesh:
Incorporating Expert Prior in Bayesian Optimisation via Space Warping. CoRR abs/2003.12250 (2020) - [i25]Phuoc Nguyen, Truyen Tran, Sunil Gupta, Santu Rana, Hieu-Chi Dam, Svetha Venkatesh:
HyperVAE: A Minimum Description Length Variational Hyper-Encoding Network. CoRR abs/2005.08482 (2020) - [i24]Thomas P. Quinn, Dang Nguyen, Santu Rana, Sunil Gupta, Svetha Venkatesh:
DeepCoDA: personalized interpretability for compositional health data. CoRR abs/2006.01392 (2020) - [i23]Julian Berk, Sunil Gupta, Santu Rana, Svetha Venkatesh:
Randomised Gaussian Process Upper Confidence Bound for Bayesian Optimisation. CoRR abs/2006.04296 (2020) - [i22]Haripriya Harikumar, Vuong Le, Santu Rana, Sourangshu Bhattacharya, Sunil Gupta, Svetha Venkatesh:
Scalable Backdoor Detection in Neural Networks. CoRR abs/2006.05646 (2020) - [i21]Phuc Luong, Dang Nguyen, Sunil Gupta, Santu Rana, Svetha Venkatesh:
Bayesian Optimization with Missing Inputs. CoRR abs/2006.10948 (2020) - [i20]Hung Tran-The, Sunil Gupta, Santu Rana, Huong Ha, Svetha Venkatesh:
Sub-linear Regret Bounds for Bayesian Optimisation in Unknown Search Spaces. CoRR abs/2009.02539 (2020) - [i19]Alistair Shilton, Sunil Gupta, Santu Rana, Svetha Venkatesh:
Sequential Subspace Search for Functional Bayesian Optimization Incorporating Experimenter Intuition. CoRR abs/2009.03543 (2020) - [i18]Duc Nguyen, Phuoc Nguyen, Kien Do, Santu Rana, Sunil Gupta, Truyen Tran:
Unsupervised Anomaly Detection on Temporal Multiway Data. CoRR abs/2009.09443 (2020) - [i17]Anh-Cat Le-Ngo, Truyen Tran, Santu Rana, Sunil Gupta, Svetha Venkatesh:
Logically Consistent Loss for Visual Question Answering. CoRR abs/2011.10094 (2020) - [i16]Huong Ha, Sunil Gupta, Santu Rana, Svetha Venkatesh:
High Dimensional Level Set Estimation with Bayesian Neural Network. CoRR abs/2012.09973 (2020)
2010 – 2019
- 2019
- [j9]Tinu Theckel Joy, Santu Rana, Sunil Gupta, Svetha Venkatesh:
A flexible transfer learning framework for Bayesian optimization with convergence guarantee. Expert Syst. Appl. 115: 656-672 (2019) - [j8]Vu Nguyen, Sunil Gupta, Santu Rana, Cheng Li, Svetha Venkatesh:
Filtering Bayesian optimization approach in weakly specified search space. Knowl. Inf. Syst. 60(1): 385-413 (2019) - [c55]Pratibha Vellanki, Santu Rana, Sunil Gupta, David Rubin de Celis Leal, Alessandra Sutti, Murray Height, Svetha Venkatesh:
Bayesian Functional Optimisation with Shape Prior. AAAI 2019: 1617-1624 - [c54]A. V. Arun Kumar, Santu Rana, Cheng Li, Sunil Gupta, Alistair Shilton, Svetha Venkatesh:
Bayesian Optimisation for Objective Functions with Varying Smoothness. Australasian Conference on Artificial Intelligence 2019: 460-472 - [c53]Phuc Luong, Sunil Gupta, Dang Nguyen, Santu Rana, Svetha Venkatesh:
Bayesian Optimization with Discrete Variables. Australasian Conference on Artificial Intelligence 2019: 473-484 - [c52]Deepthi Praveenlal Kuttichira, Sunil Gupta, Dang Nguyen, Santu Rana, Svetha Venkatesh:
Detection of Compromised Models Using Bayesian Optimization. Australasian Conference on Artificial Intelligence 2019: 485-496 - [c51]Anil Ramachandran, Sunil Gupta, Santu Rana, Svetha Venkatesh:
Information-Theoretic Multi-task Learning Framework for Bayesian Optimisation. Australasian Conference on Artificial Intelligence 2019: 497-509 - [c50]Vu Nguyen, Sunil Gupta, Santu Rana, My T. Thai, Cheng Li, Svetha Venkatesh:
Efficient Bayesian Optimization for Uncertainty Reduction Over Perceived Optima Locations. ICDM 2019: 1270-1275 - [c49]Huong Ha, Santu Rana, Sunil Gupta, Thanh Tang Nguyen, Hung Tran-The, Svetha Venkatesh:
Bayesian Optimization with Unknown Search Space. NeurIPS 2019: 11772-11781 - [c48]Majid Abdolshah, Alistair Shilton, Santu Rana, Sunil Gupta, Svetha Venkatesh:
Multi-objective Bayesian optimisation with preferences over objectives. NeurIPS 2019: 12214-12224 - [c47]Deepthi Praveenlal Kuttichira, Sunil Gupta, Cheng Li, Santu Rana, Svetha Venkatesh:
Explaining Black-Box Models Using Interpretable Surrogates. PRICAI (1) 2019: 3-15 - [c46]Phuoc Nguyen, Truyen Tran, Sunil Gupta, Santu Rana, Matthew Barnett, Svetha Venkatesh:
Incomplete Conditional Density Estimation for Fast Materials Discovery. SDM 2019: 549-557 - [i15]Tinu Theckel Joy, Santu Rana, Sunil Gupta, Svetha Venkatesh:
Fast Hyperparameter Tuning using Bayesian Optimization with Directional Derivatives. CoRR abs/1902.02416 (2019) - [i14]Majid Abdolshah, Alistair Shilton, Santu Rana, Sunil Gupta, Svetha Venkatesh:
Multi-objective Bayesian optimisation with preferences over objectives. CoRR abs/1902.04228 (2019) - [i13]Alistair Shilton, Sunil Gupta, Santu Rana, Svetha Venkatesh, Majid Abdolshah, Dang Nguyen:
Stable Bayesian Optimisation via Direct Stability Quantification. CoRR abs/1902.07846 (2019) - [i12]Ang Yang, Cheng Li, Santu Rana, Sunil Gupta, Svetha Venkatesh:
Sparse Spectrum Gaussian Process for Bayesian Optimisation. CoRR abs/1906.08898 (2019) - [i11]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:
Accelerating Experimental Design by Incorporating Experimenter Hunches. CoRR abs/1907.09065 (2019) - [i10]Majid Abdolshah, Alistair Shilton, Santu Rana, Sunil Gupta, Svetha Venkatesh:
Cost-aware Multi-objective Bayesian optimisation. CoRR abs/1909.03600 (2019) - [i9]Thommen George Karimpanal, Santu Rana, Sunil Gupta, Truyen Tran, Svetha Venkatesh:
Learning Transferable Domain Priors for Safe Exploration in Reinforcement Learning. CoRR abs/1909.04307 (2019) - [i8]Huong Ha, Santu Rana, Sunil Gupta, Thanh Tang Nguyen, Hung Tran-The, Svetha Venkatesh:
Bayesian Optimization with Unknown Search Space. CoRR abs/1910.13092 (2019) - [i7]Hung Tran-The, Sunil Gupta, Santu Rana, Svetha Venkatesh:
Trading Convergence Rate with Computational Budget in High Dimensional Bayesian Optimization. CoRR abs/1911.11950 (2019) - [i6]Dang Nguyen, Sunil Gupta, Santu Rana, Alistair Shilton, Svetha Venkatesh:
Bayesian Optimization for Categorical and Category-Specific Continuous Inputs. CoRR abs/1911.12473 (2019) - 2018
- [j7]Thanh Dai Nguyen, Sunil Gupta, Santu Rana, Svetha Venkatesh:
Stable Bayesian optimization. Int. J. Data Sci. Anal. 6(4): 327-339 (2018) - [c45]Sunil Gupta, Alistair Shilton, Santu Rana, Svetha Venkatesh:
Exploiting Strategy-Space Diversity for Batch Bayesian Optimization. AISTATS 2018: 538-547 - [c44]Ang Yang, Cheng Li, Santu Rana, Sunil Gupta, Svetha Venkatesh:
Sparse Approximation for Gaussian Process with Derivative Observations. Australasian Conference on Artificial Intelligence 2018: 507-518 - [c43]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:
Accelerating Experimental Design by Incorporating Experimenter Hunches. ICDM 2018: 257-266 - [c42]Haripriya Harikumar, Santu Rana, Sunil Gupta, Thin Nguyen, Ramachandra Kaimal, Svetha Venkatesh:
Differentially Private Prescriptive Analytics. ICDM 2018: 995-1000 - [c41]Majid Abdolshah, Alistair Shilton, Santu Rana, Sunil Gupta, Svetha Venkatesh:
Expected Hypervolume Improvement with Constraints. ICPR 2018: 3238-3243 - [c40]Shivapratap Gopakumar, Sunil Gupta, Santu Rana, Vu Nguyen, Svetha Venkatesh:
Algorithmic Assurance: An Active Approach to Algorithmic Testing using Bayesian Optimisation. NeurIPS 2018: 5470-5478 - [c39]Haripriya Harikumar, Santu Rana, Sunil Gupta, Thin Nguyen, Ramachandra Kaimal, Svetha Venkatesh:
Prescriptive Analytics Through Constrained Bayesian Optimization. PAKDD (1) 2018: 335-347 - [c38]Thanh Dai Nguyen, Sunil Gupta, Santu Rana, Svetha Venkatesh:
A Privacy Preserving Bayesian Optimization with High Efficiency. PAKDD (3) 2018: 543-555 - [c37]Julian Berk, Vu Nguyen, Sunil Gupta, Santu Rana, Svetha Venkatesh:
Exploration Enhanced Expected Improvement for Bayesian Optimization. ECML/PKDD (2) 2018: 621-637 - [c36]Anil Ramachandran, Sunil Gupta, Santu Rana, Svetha Venkatesh:
Information-Theoretic Transfer Learning Framework for Bayesian Optimisation. ECML/PKDD (2) 2018: 827-842 - [c35]Anil Ramachandran, Sunil Gupta, Santu Rana, Svetha Venkatesh:
Selecting Optimal Source for Transfer Learning in Bayesian Optimisation. PRICAI (1) 2018: 42-56 - [c34]Ang Yang, Cheng Li, Santu Rana, Sunil Gupta, Svetha Venkatesh:
Efficient Bayesian Optimisation Using Derivative Meta-model. PRICAI 2018: 256-264 - [c33]Alistair Shilton, Santu Rana, Sunil Gupta, Svetha Venkatesh:
Multi-Target Optimisation via Bayesian Optimisation and Linear Programming. UAI 2018: 145-155 - [i5]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:
Kernel Pre-Training in Feature Space via m-Kernels. CoRR abs/1805.07852 (2018) - [i4]Pratibha Vellanki, Santu Rana, Sunil Gupta, David Rubin de Celis Leal, Alessandra Sutti, Murray Height, Svetha Venkatesh:
Bayesian functional optimisation with shape prior. CoRR abs/1809.07260 (2018) - [i3]Vu Nguyen, Sunil Gupta, Santu Rana, Cheng Li, Svetha Venkatesh:
Practical Batch Bayesian Optimization for Less Expensive Functions. CoRR abs/1811.01466 (2018) - [i2]Phuoc Nguyen, Truyen Tran, Sunil Gupta, Santu Rana, Svetha Venkatesh:
Hybrid Generative-Discriminative Models for Inverse Materials Design. CoRR abs/1811.06060 (2018) - 2017
- [c32]Vu Nguyen, Sunil Gupta, Santu Rana, Cheng Li, Svetha Venkatesh:
Regret for Expected Improvement over the Best-Observed Value and Stopping Condition. ACML 2017: 279-294 - [c31]Alistair Shilton, Sunil Gupta, Santu Rana, Svetha Venkatesh:
Regret Bounds for Transfer Learning in Bayesian Optimisation. AISTATS 2017: 307-315 - [c30]Vu Nguyen, Sunil Gupta, Santu Rana, Cheng Li, Svetha Venkatesh:
Bayesian Optimization in Weakly Specified Search Space. ICDM 2017: 347-356 - [c29]Santu Rana, Cheng Li, Sunil Gupta, Vu Nguyen, Svetha Venkatesh:
High Dimensional Bayesian Optimization with Elastic Gaussian Process. ICML 2017: 2883-2891 - [c28]Cheng Li, Sunil Gupta, Santu Rana, Vu Nguyen, Svetha Venkatesh, Alistair Shilton:
High Dimensional Bayesian Optimization using Dropout. IJCAI 2017: 2096-2102 - [c27]Pratibha Vellanki, Santu Rana, Sunil Gupta, David Rubin, Alessandra Sutti, Thomas Dorin, Murray Height, Paul G. Sanders, Svetha Venkatesh:
Process-constrained batch Bayesian optimisation. NIPS 2017: 3414-3423 - [c26]Thanh Dai Nguyen, Sunil Gupta, Santu Rana, Svetha Venkatesh:
Stable Bayesian Optimization. PAKDD (2) 2017: 578-591 - [i1]Vu Nguyen, Santu Rana, Sunil Gupta, Cheng Li, Svetha Venkatesh:
Budgeted Batch Bayesian Optimization With Unknown Batch Sizes. CoRR abs/1703.04842 (2017) - 2016
- [j6]Cheng Li, Santu Rana, Dinh Q. Phung, Svetha Venkatesh:
Data clustering using side information dependent Chinese restaurant processes. Knowl. Inf. Syst. 47(2): 463-488 (2016) - [j5]Sunil Gupta, Santu Rana, Budhaditya Saha, Dinh Q. Phung, Svetha Venkatesh:
A new transfer learning framework with application to model-agnostic multi-task learning. Knowl. Inf. Syst. 49(3): 933-973 (2016) - [j4]Cheng Li, Santu Rana, Dinh Q. Phung, Svetha Venkatesh:
Hierarchical Bayesian nonparametric models for knowledge discovery from electronic medical records. Knowl. Based Syst. 99: 168-182 (2016) - [c25]Vu Nguyen, Sunil Gupta, Santu Rana, Cheng Li, Svetha Venkatesh:
A Bayesian Nonparametric Approach for Multi-label Classification. ACML 2016: 254-269 - [c24]Haripriya Harikumar, Thin Nguyen, Santu Rana, Sunil Gupta, Ramachandra Kaimal, Svetha Venkatesh:
Extracting Key Challenges in Achieving Sobriety Through Shared Subspace Learning. ADMA 2016: 420-433 - [c23]Haripriya Harikumar, Thin Nguyen, Sunil Gupta, Santu Rana, Ramachandra Kaimal, Svetha Venkatesh:
Understanding Behavioral Differences Between Short and Long-Term Drinking Abstainers from Social Media. ADMA 2016: 520-533 - [c22]Thanh Dai Nguyen, Sunil Gupta, Santu Rana, Vu Nguyen, Svetha Venkatesh, Kyle J. Deane, Paul G. Sanders:
Cascade Bayesian Optimization. Australasian Conference on Artificial Intelligence 2016: 268-280 - [c21]Vu Nguyen, Santu Rana, Sunil Kumar Gupta, Cheng Li, Svetha Venkatesh:
Budgeted Batch Bayesian Optimization. ICDM 2016: 1107-1112 - [c20]Tinu Theckel Joy, Santu Rana, Sunil Gupta, Svetha Venkatesh:
Hyperparameter tuning for big data using Bayesian optimisation. ICPR 2016: 2574-2579 - [c19]Cheng Li, Sunil Gupta, Santu Rana, Vu Nguyen, Svetha Venkatesh, David Ashely, Trish Livingston:
Multiple adverse effects prediction in longitudinal cancer treatment. ICPR 2016: 3156-3161 - [c18]Saravanan Subramanian, Santu Rana, Sunil Gupta, Palaniappan Bagavathi Sivakumar, C. Shunmuga Velayutham, Svetha Venkatesh:
Bayesian nonparametric Multiple Instance Regression. ICPR 2016: 3661-3666 - [c17]Sunil Kumar Gupta, Santu Rana, Svetha Venkatesh:
Differentially Private Multi-task Learning. PAISI 2016: 101-113 - [c16]Tinu Theckel Joy, Santu Rana, Sunil Kumar Gupta, Svetha Venkatesh:
Flexible Transfer Learning Framework for Bayesian Optimisation. PAKDD (1) 2016: 102-114 - [c15]Cheng Li, Sunil Gupta, Santu Rana, Wei Luo, Svetha Venkatesh, David Ashely, Dinh Q. Phung:
Toxicity Prediction in Cancer Using Multiple Instance Learning in a Multi-task Framework. PAKDD (1) 2016: 152-164 - [c14]Thanh Dai Nguyen, Sunil Gupta, Santu Rana, Svetha Venkatesh:
Privacy Aware K-Means Clustering with High Utility. PAKDD (2) 2016: 388-400 - 2015
- [j3]Santu Rana, Sunil Gupta, Dinh Q. Phung, Svetha Venkatesh:
A predictive framework for modeling healthcare data with evolving clinical interventions. Stat. Anal. Data Min. 8(3): 162-182 (2015) - [c13]Santu Rana, Sunil Kumar Gupta, Svetha Venkatesh:
Differentially Private Random Forest with High Utility. ICDM 2015: 955-960 - [c12]Cheng Li, Santu Rana, Dinh Q. Phung, Svetha Venkatesh:
Small-Variance Asymptotics for Bayesian Nonparametric Models with Constraints. PAKDD (2) 2015: 92-105 - [c11]Sunil Kumar Gupta, Santu Rana, Dinh Q. Phung, Svetha Venkatesh:
Collaborating Differently on Different Topics: A Multi-Relational Approach to Multi-Task Learning. PAKDD (1) 2015: 303-316 - [c10]Sunil Gupta, Santu Rana, Dinh Q. Phung, Svetha Venkatesh:
What shall I share and with Whom? - A Multi-Task Learning Formulation using Multi-Faceted Task Relationships. SDM 2015: 703-711 - 2014
- [j2]Truyen Tran, Wei Luo, Dinh Q. Phung, Sunil Gupta, Santu Rana, Richard Kennedy, Ann Larkins, Svetha Venkatesh:
A framework for feature extraction from hospital medical data with applications in risk prediction. BMC Bioinform. 15: 6596 (2014) - [c9]Cheng Li, Santu Rana, Dinh Q. Phung, Svetha Venkatesh:
Regularizing Topic Discovery in EMRs with Side Information by Using Hierarchical Bayesian Models. ICPR 2014: 1307-1312 - [c8]Santu Rana, Sunil Kumar Gupta, Dinh Q. Phung, Svetha Venkatesh:
Intervention-Driven Predictive Framework for Modeling Healthcare Data. PAKDD (1) 2014: 497-508 - [c7]Sunil Kumar Gupta, Santu Rana, Dinh Q. Phung, Svetha Venkatesh:
Keeping up with Innovation: A Predictive Framework for Modeling Healthcare Data with Evolving Clinical Interventions. SDM 2014: 235-243 - 2013
- [c6]Cheng Li, Dinh Q. Phung, Santu Rana, Svetha Venkatesh:
Exploiting side information in distance dependent Chinese restaurant processes for data clustering. ICME 2013: 1-6 - [c5]Santu Rana, Dinh Q. Phung, Svetha Venkatesh:
Split-Merge Augmented Gibbs Sampling for Hierarchical Dirichlet Processes. PAKDD (2) 2013: 546-557 - 2012
- [c4]Tien-Vu Nguyen, Dinh Q. Phung, Santu Rana, Duc-Son Pham, Svetha Venkatesh:
Multi-modal abnormality detection in video with unknown data segmentation. ICPR 2012: 1322-1325 - [c3]Santu Rana, Dinh Q. Phung, Sonny Pham, Svetha Venkatesh:
Large-scale statistical modeling of motion patterns: a Bayesian nonparametric approach. ICVGIP 2012: 7
2000 – 2009
- 2009
- [j1]Santu Rana, Wanquan Liu, Mihai M. Lazarescu, Svetha Venkatesh:
A unified tensor framework for face recognition. Pattern Recognit. 42(11): 2850-2862 (2009) - 2008
- [c2]Santu Rana, Wanquan Liu, Mihai M. Lazarescu, Svetha Venkatesh:
Recognising faces in unseen modes: A tensor based approach. CVPR 2008 - [c1]Santu Rana, Wanquan Liu, Mihai M. Lazarescu, Svetha Venkatesh:
Efficient tensor based face recognition. ICPR 2008: 1-4
Coauthor Index
[c101] [c95] [c94] [c93] [i59] [i57] [i54] [j22] [c91] [c90] [i53] [i51] [i48] [i47] [i46] [i44] [j21] [j20] [j19] [c89] [c88] [c87] [c86] [c80] [c78] [i40] [i39] [i38] [j18] [j17] [j16] [c77] [c76] [c75] [c73] [c72] [c71] [c70] [c69] [i36] [i34] [i33] [i32] [i31] [i30] [i29] [j15] [j14] [j13] [j12] [j11] [j10] [c68] [c67] [c66] [c65] [c64] [c63] [c62] [c61] [c60] [c59] [c58] [c57] [c56] [i28] [i27] [i26] [i25] [i24] [i23] [i22] [i21] [i20] [i19] [i18] [i17] [i16] [j9] [j8] [c55] [c54] [c53] [c52] [c51] [c50] [c49] [c48] [c47] [c46] [i15] [i14] [i13] [i12] [i11] [i10] [i9] [i8] [i7] [i6] [j7] [c45] [c44] [c43] [c42] [c41] [c40] [c39] [c38] [c37] [c36] [c35] [c34] [c33] [i5] [i4] [i3] [i2] [c32] [c31] [c30] [c29] [c28] [c27] [c26] [i1] [j5] [c25] [c24] [c23] [c22] [c21] [c20] [c19] [c18] [c17] [c16] [c15] [c14] [j3] [c13] [c11] [c10] [j2] [c8] [c7]
Thommen George Karimpanal
aka: Thommen Karimpanal George
aka: Thommen Karimpanal George
Vu Nguyen 0001
aka: Tien-Vu Nguyen
aka: Tien-Vu Nguyen
[c101] [c98] [c96] [c94] [c93] [i60] [i59] [i57] [i56] [i54] [j22] [c91] [c90] [i53] [i52] [i51] [i47] [i46] [i44] [j21] [j20] [j19] [c89] [c88] [c86] [c85] [c84] [c83] [c82] [c81] [c80] [c79] [c78] [i43] [i42] [i41] [i40] [i39] [i38] [i37] [j18] [j17] [j16] [c77] [c76] [c75] [c74] [c73] [c72] [c71] [c70] [c69] [i36] [i35] [i34] [i33] [i32] [i31] [i30] [i29] [j15] [j14] [j13] [j12] [j11] [j10] [c68] [c67] [c66] [c65] [c64] [c63] [c62] [c61] [c60] [c59] [c58] [c57] [i28] [i27] [i26] [i25] [i24] [i23] [i22] [i21] [i20] [i19] [i17] [i16] [j9] [j8] [c55] [c54] [c53] [c52] [c51] [c50] [c49] [c48] [c47] [c46] [i15] [i14] [i13] [i12] [i11] [i10] [i9] [i8] [i7] [i6] [j7] [c45] [c44] [c43] [c42] [c41] [c40] [c39] [c38] [c37] [c36] [c35] [c34] [c33] [i5] [i4] [i3] [i2] [c32] [c31] [c30] [c29] [c28] [c27] [c26] [i1] [j6] [j5] [j4] [c25] [c24] [c23] [c22] [c21] [c20] [c19] [c18] [c17] [c16] [c15] [c14] [j3] [c13] [c12] [c11] [c10] [j2] [c9] [c8] [c7] [c6] [c5] [c4] [c3] [j1] [c2] [c1]
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