Santu Rana

发表

Logically Consistent Loss for Visual Question Answering pdf

Truyen Tran, Anh-Cat Le-Ngo, Santu Rana, 2020, ArXiv.

DeepCoDA: personalized interpretability for compositional health

Santu Rana, Sunil Gupta, Dang Nguyen, 2020, International Conference on Machine Learning.

Bayesian Optimization for Adaptive Experimental Design: A Review

Santu Rana, Sunil Gupta, Svetha Venkatesh, 2020, IEEE Access.

Information-Theoretic Transfer Learning Framework for Bayesian Optimisation

Svetha Venkatesh, Santu Rana, Sunil Gupta, 2018, ECML/PKDD.

Split-Merge Augmented Gibbs Sampling for Hierarchical Dirichlet Processes

Svetha Venkatesh, Dinh Q. Phung, Santu Rana, 2013, PAKDD.

Multiple adverse effects prediction in longitudinal cancer treatment

Santu Rana, Sunil Gupta, Svetha Venkatesh, 2016, 2016 23rd International Conference on Pattern Recognition (ICPR).

Explaining Black-Box Models Using Interpretable Surrogates

Santu Rana, Svetha Venkatesh, Cheng Li, 2019, PRICAI.

A flexible transfer learning framework for Bayesian optimization with convergence guarantee

Svetha Venkatesh, Santu Rana, Sunil Gupta, 2019, Expert Syst. Appl..

A new transfer learning framework with application to model-agnostic multi-task learning

Svetha Venkatesh, Dinh Q. Phung, Santu Rana, 2016, Knowledge and Information Systems.

Guidelines for Developing and Reporting Machine Learning Predictive Models in Biomedical Research: A Multidisciplinary View

Wei Luo, John Yearwood, Tu Bao Ho, 2016, Journal of medical Internet research.

Hyperparameter tuning for big data using Bayesian optimisation

Svetha Venkatesh, Santu Rana, Sunil Gupta, 2016, 2016 23rd International Conference on Pattern Recognition (ICPR).

Prescriptive Analytics Through Constrained Bayesian Optimization

Svetha Venkatesh, Santu Rana, Sunil Gupta, 2018, PAKDD.

Exploiting Strategy-Space Diversity for Batch Bayesian Optimization

Svetha Venkatesh, Alistair Shilton, Santu Rana, 2018, AISTATS.

Intervention-Driven Predictive Framework for Modeling Healthcare Data

Svetha Venkatesh, Dinh Q. Phung, Santu Rana, 2014, PAKDD.

High Dimensional Bayesian Optimization using Dropout

Cheng Li, Svetha Venkatesh, Alistair Shilton, 2018, IJCAI.

Bayesian Optimization with Discrete Variables

Santu Rana, Sunil Gupta, Svetha Venkatesh, 2019, Australasian Conference on Artificial Intelligence.

Batch Bayesian optimization using multi-scale search

Svetha Venkatesh, Santu Rana, Tinu Theckel Joy, 2020, Knowl. Based Syst..

Accelerating Experimental Design by Incorporating Experimenter Hunches

Ian Gibson, Santu Rana, Sunil Gupta, 2018, 2018 IEEE International Conference on Data Mining (ICDM).

Regret Bounds for Transfer Learning in Bayesian Optimisation

Svetha Venkatesh, Alistair Shilton, Santu Rana, 2017, AISTATS.

Incorporating Expert Prior in Bayesian Optimisation via Space Warping pdf

Cheng Li, Santu Rana, Sunil Gupta, 2020, Knowl. Based Syst..

Hierarchical Bayesian nonparametric models for knowledge discovery from electronic medical records

Cheng Li, Svetha Venkatesh, Dinh Q. Phung, 2016, Knowl. Based Syst..

Filtering Bayesian optimization approach in weakly specified search space

Cheng Li, Santu Rana, Vu Nguyen, 2018, Knowledge and Information Systems.

Flexible Transfer Learning Framework for Bayesian Optimisation

Svetha Venkatesh, Santu Rana, Sunil Kumar Gupta, 2016, PAKDD.

Detection of Compromised Models Using Bayesian Optimization

Santu Rana, Sunil Gupta, Svetha Venkatesh, 2019, Australasian Conference on Artificial Intelligence.

Exploiting side information in distance dependent Chinese restaurant processes for data clustering

Cheng Li, Svetha Venkatesh, Dinh Q. Phung, 2013, 2013 IEEE International Conference on Multimedia and Expo (ICME).

Toxicity Prediction in Cancer Using Multiple Instance Learning in a Multi-task Framework

Wei Luo, Cheng Li, Svetha Venkatesh, 2016, PAKDD.

Small-Variance Asymptotics for Bayesian Nonparametric Models with Constraints

Cheng Li, Svetha Venkatesh, Dinh Q. Phung, 2015, PAKDD.

Accelerated Bayesian Optimization throughWeight-Prior Tuning

Cheng Li, Alireza Vahid, Santu Rana, 2018 .

Stable Bayesian Optimization

Svetha Venkatesh, Santu Rana, Sunil Gupta, 2017, PAKDD.

Cascade Bayesian Optimization

Svetha Venkatesh, Santu Rana, Vu Nguyen, 2016, Australasian Conference on Artificial Intelligence.

Bayesian optimisation in unknown bounded search domains

Santu Rana, Sunil Gupta, Vu Nguyen, 2020, Knowl. Based Syst..

Understanding Behavioral Differences Between Short and Long-Term Drinking Abstainers from Social Media

Svetha Venkatesh, Santu Rana, Thin Nguyen, 2016, ADMA.

Learning Transferable Domain Priors for Safe Exploration in Reinforcement Learning

Thommen George Karimpanal, Truyen Tran, Santu Rana, 2020, 2020 International Joint Conference on Neural Networks (IJCNN).

Randomised Gaussian Process Upper Confidence Bound for Bayesian Optimisation pdf

Santu Rana, Sunil Gupta, Svetha Venkatesh, 2020, IJCAI.

Kernel Pre-Training in Feature Space via m-Kernels pdf

Cheng Li, Svetha Venkatesh, Alistair Shilton, 2018, ArXiv.

Incomplete Conditional Density Estimation for Fast Materials Discovery

Truyen Tran, Santu Rana, Sunil Gupta, 2019, SDM.

Budgeted Batch Bayesian Optimization

Cheng Li, Svetha Venkatesh, Santu Rana, 2016, 2016 IEEE 16th International Conference on Data Mining (ICDM).

HyperVAE: A Minimum Description Length Variational Hyper-Encoding Network pdf

Truyen Tran, Phuoc Nguyen, Santu Rana, 2020, ArXiv.

Data clustering using side information dependent Chinese restaurant processes

Cheng Li, Svetha Venkatesh, Dinh Q. Phung, 2015, Knowledge and Information Systems.

A Privacy Preserving Bayesian Optimization with High Efficiency

Svetha Venkatesh, Santu Rana, Sunil Gupta, 2018, PAKDD.

Differentially Private Prescriptive Analytics

Svetha Venkatesh, Santu Rana, Sunil Gupta, 2018, 2018 IEEE International Conference on Data Mining (ICDM).

A random walk down personalized single-cell networks: predicting the response of any gene to any drug for any patient

Santu Rana, Sunil Gupta, Svetha Venkatesh, 2019, bioRxiv.

Exploration Enhanced Expected Improvement for Bayesian Optimization

Svetha Venkatesh, Santu Rana, Vu Nguyen, 2018, ECML/PKDD.

High Dimensional Bayesian Optimization with Elastic Gaussian Process

Cheng Li, Svetha Venkatesh, Santu Rana, 2017, ICML.

Recognising faces in unseen modes: A tensor based approach

Svetha Venkatesh, Wanquan Liu, Mihai Lazarescu, 2008, 2008 IEEE Conference on Computer Vision and Pattern Recognition.

Regularizing Topic Discovery in EMRs with Side Information by Using Hierarchical Bayesian Models

Cheng Li, Svetha Venkatesh, Dinh Q. Phung, 2014, 2014 22nd International Conference on Pattern Recognition.

Bayesian Optimization with Missing Inputs pdf

Santu Rana, Sunil Gupta, Svetha Venkatesh, 2020, ECML/PKDD.

Sequential Subspace Search for Functional Bayesian Optimization Incorporating Experimenter Intuition pdf

Santu Rana, Sunil Gupta, Svetha Venkatesh, 2020, ArXiv.

Stable Bayesian optimization

Svetha Venkatesh, Santu Rana, Sunil Gupta, 2018, International Journal of Data Science and Analytics.

A Bayesian Nonparametric Approach for Multi-label Classification

Cheng Li, Svetha Venkatesh, Santu Rana, 2016, ACML.

Extracting Key Challenges in Achieving Sobriety Through Shared Subspace Learning

Svetha Venkatesh, Santu Rana, Thin Nguyen, 2016, ADMA.

Practical Batch Bayesian Optimization for Less Expensive Functions pdf

Cheng Li, Svetha Venkatesh, Santu Rana, 2018, ArXiv.

Randomised Gaussian Process Upper Confidence Bound for Bayesian Optimisation

Santu Rana, Svetha Venkatesh, Julian Berk, 2020, International Joint Conference on Artificial Intelligence.

Collaborating Differently on Different Topics: A Multi-Relational Approach to Multi-Task Learning

Svetha Venkatesh, Dinh Q. Phung, Santu Rana, 2015, PAKDD.

Bayesian Optimisation for Objective Functions with Varying Smoothness

Cheng Li, Santu Rana, Sunil Gupta, 2019, Australasian Conference on Artificial Intelligence.

Information-Theoretic Multi-task Learning Framework for Bayesian Optimisation

Santu Rana, Sunil Gupta, Svetha Venkatesh, 2019, Australasian Conference on Artificial Intelligence.

Expected Hypervolume Improvement with Constraints

Svetha Venkatesh, Alistair Shilton, Majid Abdolshah, 2018, 2018 24th International Conference on Pattern Recognition (ICPR).

Level Set Estimation with Search Space Warping

Santu Rana, Sunil Gupta, Svetha Venkatesh, 2020, PAKDD.

Sub-linear Regret Bounds for Bayesian Optimisation in Unknown Search Spaces pdf

Santu Rana, Hung Tran-The, Svetha Venkatesh, 2020, NeurIPS.

Sparse Approximation for Gaussian Process with Derivative Observations

Cheng Li, Svetha Venkatesh, Santu Rana, 2018, Australasian Conference on Artificial Intelligence.

Bayesian functional optimisation with shape prior pdf

Svetha Venkatesh, Santu Rana, Pratibha Vellanki, 2018, AAAI.

Cost-aware Multi-objective Bayesian optimisation pdf

Majid Abdolshah, Santu Rana, Sunil Gupta, 2019, ArXiv.

Process-constrained batch Bayesian optimisation

Svetha Venkatesh, Santu Rana, Paul G. Sanders, 2017, NIPS.

A unified tensor framework for face recognition

Svetha Venkatesh, Wanquan Liu, Mihai Lazarescu, 2009, Pattern Recognit..

Efficient Bayesian Optimisation Using Derivative Meta-model

Cheng Li, Svetha Venkatesh, Santu Rana, 2018, PRICAI.

Accelerated Bayesian Optimisation through Weight-Prior Tuning

Alireza Vahid, Santu Rana, Sunil Gupta, 2020, AISTATS.

Distributionally Robust Bayesian Quadrature Optimization

Santu Rana, Sunil Gupta, Svetha Venkatesh, 2020, AISTATS.

Bayesian Optimization in Weakly Specified Search Space

Cheng Li, Svetha Venkatesh, Santu Rana, 2017, 2017 IEEE International Conference on Data Mining (ICDM).

Bayesian nonparametric Multiple Instance Regression

Svetha Venkatesh, C. Shunmuga Velayutham, Santu Rana, 2016, 2016 23rd International Conference on Pattern Recognition (ICPR).

Efficient tensor based face recognition

Svetha Venkatesh, Wanquan Liu, Mihai Lazarescu, 2008, 2008 19th International Conference on Pattern Recognition.

Bayesian Optimization with Unknown Search Space

Santu Rana, Sunil Gupta, Svetha Venkatesh, 2019, NeurIPS.

Sparse Spectrum Gaussian Process for Bayesian Optimisation pdf

Santu Rana, Svetha Venkatesh, Cheng Li, 2019, ArXiv.

Differentially Private Random Forest with High Utility

Svetha Venkatesh, Santu Rana, Sunil Kumar Gupta, 2015, 2015 IEEE International Conference on Data Mining.

Scalable Backdoor Detection in Neural Networks pdf

Santu Rana, Sunil Gupta, Svetha Venkatesh, 2020, ECML/PKDD.

Rapid Bayesian optimisation for synthesis of short polymer fiber materials

Cheng Li, Sunil Gupta, Stewart Greenhill, 2017, Scientific Reports.

Trading Convergence Rate with Computational Budget in High Dimensional Bayesian Optimization

Santu Rana, Sunil Gupta, Hung Tran-The, 2020, AAAI.

Hybrid Generative-Discriminative Models for Inverse Materials Design pdf

Svetha Venkatesh, Truyen Tran, Phuoc Nguyen, 2018, ArXiv.

Stable Bayesian Optimisation via Direct Stability Quantification pdf

Svetha Venkatesh, Alistair Shilton, Majid Abdolshah, 2019, ArXiv.

Regret for Expected Improvement over the Best-Observed Value and Stopping Condition

Cheng Li, Svetha Venkatesh, Santu Rana, 2017, ACML.

Multi-objective Bayesian optimisation with preferences over objectives

Svetha Venkatesh, Alistair Shilton, Majid Abdolshah, 2019, NeurIPS.

Privacy Aware K-Means Clustering with High Utility

Svetha Venkatesh, Santu Rana, Sunil Gupta, 2016, PAKDD.

Selecting Optimal Source for Transfer Learning in Bayesian Optimisation

Svetha Venkatesh, Santu Rana, Anil Ramachandran, 2018, PRICAI.

Unsupervised Anomaly Detection on Temporal Multiway Data

Truyen Tran, Kien Do, Phuoc Nguyen, 2020, 2020 IEEE Symposium Series on Computational Intelligence (SSCI).

Multi-Target Optimisation via Bayesian Optimisation and Linear Programming

Svetha Venkatesh, Alistair Shilton, Santu Rana, 2018, UAI.

Fast Hyperparameter Tuning using Bayesian Optimization with Directional Derivatives pdf

Svetha Venkatesh, Santu Rana, Sunil Gupta, 2019, Knowl. Based Syst..

Efficient Bayesian Optimization for Uncertainty Reduction Over Perceived Optima Locations

Cheng Li, Santu Rana, Sunil Gupta, 2019, 2019 IEEE International Conference on Data Mining (ICDM).

Multi-modal abnormality detection in video with unknown data segmentation

Svetha Venkatesh, Duc-Son Pham, Dinh Q. Phung, 2012, Proceedings of the 21st International Conference on Pattern Recognition (ICPR2012).

What shall I share and with Whom? - A Multi-Task Learning Formulation using Multi-Faceted Task Relationships

Svetha Venkatesh, Dinh Q. Phung, Santu Rana, 2015, SDM.

Incorporating Expert Prior Knowledge into Experimental Design via Posterior Sampling pdf

Antonio Robles-Kelly, Cheng Li, Santu Rana, 2020, ArXiv.

Bayesian Optimization for Categorical and Category-Specific Continuous Inputs

Santu Rana, Sunil Gupta, Dang Nguyen, 2019, AAAI.

A predictive framework for modeling healthcare data with evolving clinical interventions

Svetha Venkatesh, Dinh Q. Phung, Santu Rana, 2015, Stat. Anal. Data Min..

Budgeted Batch Bayesian Optimization With Unknown Batch Sizes pdf

Cheng Li, Svetha Venkatesh, Santu Rana, 2017, ArXiv.

Keeping up with Innovation: A Predictive Framework for Modeling Healthcare Data with Evolving Clinical Interventions

Svetha Venkatesh, Dinh Q. Phung, Santu Rana, 2014, SDM.

Large-scale statistical modeling of motion patterns: a Bayesian nonparametric approach

Svetha Venkatesh, Dinh Q. Phung, Santu Rana, 2012, ICVGIP '12.

Algorithmic Assurance: An Active Approach to Algorithmic Testing using Bayesian Optimisation

Svetha Venkatesh, Santu Rana, Vu Nguyen, 2018, NeurIPS.

A framework for feature extraction from hospital medical data with applications in risk prediction

Wei Luo, Svetha Venkatesh, Truyen Tran, 2014, BMC Bioinformatics.

Differentially Private Multi-task Learning

Svetha Venkatesh, Santu Rana, Sunil Kumar Gupta, 2016, PAISI.

DeepCoDA: personalized interpretability for compositional health data

Santu Rana, Sunil Gupta, Dang Nguyen, 2020, ICML.

High Dimensional Level Set Estimation with Bayesian Neural Network pdf

Santu Rana, Sunil Gupta, Svetha Venkatesh, 2020, AAAI.

Variational Hyper-encoding Networks

Svetha Venkatesh, Santu Rana, Sunil Gupta, 2021, ECML/PKDD.

Fairness improvement for black-box classifiers with Gaussian process

Svetha Venkatesh, Santu Rana, Sunil Gupta, 2021, Inf. Sci..

Combining Online Learning and Offline Learning for Contextual Bandits with Deficient Support pdf

Svetha Venkatesh, Santu Rana, Sunil Gupta, 2021, ArXiv.

Plug and Play, Model-Based Reinforcement Learning pdf

Thommen George Karimpanal, Svetha Venkatesh, Majid Abdolshah, 2021, ArXiv.

Prescriptive analytics with differential privacy

Santu Rana, Thin Nguyen, Ramachandra Kaimal, 2021, Int. J. Data Sci. Anal..

A New Representation of Successor Features for Transfer across Dissimilar Environments pdf

Thommen George Karimpanal, Svetha Venkatesh, Majid Abdolshah, 2021, ICML.

Intuitive Physics Guided Exploration for Sample Efficient Sim2real Transfer pdf

Thommen George Karimpanal, Svetha Venkatesh, Santu Rana, 2021, ArXiv.

Bayesian Optimistic Optimisation with Exponentially Decaying Regret

Svetha Venkatesh, Santu Rana, Sunil Gupta, 2021, ICML.

Fast Conditional Network Compression Using Bayesian HyperNetworks

Santu Rana, Sunil Gupta, Dang Nguyen, 2022, ECML/PKDD.

Adaptive cost-aware Bayesian optimization

Santu Rana, Dang Nguyen, Sunil Gupta, 2021, Knowl. Based Syst..

Factor Screening using Bayesian Active Learning and Gaussian Process Meta-Modelling

Svetha Venkatesh, Santu Rana, Sunil Gupta, 2021, 2020 25th International Conference on Pattern Recognition (ICPR).

ALT-MAS: A Data-Efficient Framework for Active Testing of Machine Learning Algorithms pdf

Svetha Venkatesh, Santu Rana, Sunil Gupta, 2021, ArXiv.

Semantic Host-free Trojan Attack pdf

Svetha Venkatesh, Kien Do, Santu Rana, 2021, ArXiv.

Knowledge Distillation with Distribution Mismatch

Santu Rana, Sunil Gupta, Dang Nguyen, 2021, ECML/PKDD.

Balanced Q-learning: Combining the Influence of Optimistic and Pessimistic Targets pdf

Thommen George Karimpanal, Majid Abdolshah, Santu Rana, 2021, Artif. Intell..

HealthMap: A visual platform for patient suicide risk review

Svetha Venkatesh, Truyen Tran, Santu Rana, 2014 .

Learning Transferable Domain Priors for Safe Exploration in Reinforcement Learning

Thommen George Karimpanal, Svetha Venkatesh, Truyen Tran, 2020, 2020 International Joint Conference on Neural Networks (IJCNN).

Web search activity data accurately predict population chronic disease risk in the USA

Wei Luo, Svetha Venkatesh, Truyen Tran, 2015, Journal of Epidemiology & Community Health.

New Bayesian-Optimization-Based Design of High-Strength 7xxx-Series Alloys from Recycled Aluminum

Svetha Venkatesh, Santu Rana, Sunil Gupta, 2018, JOM.

Is Demography Destiny? Application of Machine Learning Techniques to Accurately Predict Population Health Outcomes from a Minimal Demographic Dataset

Svetha Venkatesh, Truyen Tran, Wei Luo, 2015, PloS one.