Exploiting side information in distance dependent Chinese restaurant processes for data clustering. - Cheng Li 003; Dinh Q. Phung; Santu Rana; Svetha Venkatesh (ICME, 2013)

Regularizing Topic Discovery in EMRs with Side Information by Using Hierarchical Bayesian Models. - Cheng Li 003; Santu Rana; Dinh Q. Phung; Svetha Venkatesh (ICPR, 2014)

Small-Variance Asymptotics for Bayesian Nonparametric Models with Constraints. - Cheng Li 003; Santu Rana; Dinh Q. Phung; Svetha Venkatesh (PAKDD (2), 2015)

A Bayesian Nonparametric Approach for Multi-label Classification. - Vu Nguyen 001; Sunil Gupta 001; Santu Rana; Cheng Li 003; Svetha Venkatesh (ACML, 2016)

Budgeted Batch Bayesian Optimization. - Vu Nguyen 001; Santu Rana; Sunil Kumar Gupta 001; Cheng Li 003; Svetha Venkatesh (ICDM, 2016)

Stable clinical prediction using graph support vector machines. - Iman Kamkar; Sunil Gupta 001; Cheng Li 003; Dinh Q. Phung; Svetha Venkatesh (ICPR, 2016)

Multiple adverse effects prediction in longitudinal cancer treatment. - Cheng Li 003; Sunil Gupta 001; Santu Rana; Vu Nguyen 001; Svetha Venkatesh; David Ashely; Trish Livingston (ICPR, 2016)

Toxicity Prediction in Cancer Using Multiple Instance Learning in a Multi-task Framework. - Cheng Li 003; Sunil Gupta 001; Santu Rana; Wei Luo 001; Svetha Venkatesh; David Ashely; Dinh Q. Phung (PAKDD (1), 2016)

Data clustering using side information dependent Chinese restaurant processes. - Cheng Li 003; Santu Rana; Dinh Q. Phung; Svetha Venkatesh (Knowl. Inf. Syst., 2016)

Hierarchical Bayesian nonparametric models for knowledge discovery from electronic medical records. - Cheng Li 003; Santu Rana; Dinh Q. Phung; Svetha Venkatesh (Knowl. Based Syst., 2016)

Regret for Expected Improvement over the Best-Observed Value and Stopping Condition. - Vu Nguyen 001; Sunil Gupta 001; Santu Rana; Cheng Li 003; Svetha Venkatesh (ACML, 2017)

Bayesian Optimization in Weakly Specified Search Space. - Vu Nguyen 001; Sunil Gupta 001; Santu Rana; Cheng Li 003; Svetha Venkatesh (ICDM, 2017)

High Dimensional Bayesian Optimization with Elastic Gaussian Process. - Santu Rana; Cheng Li 003; Sunil Gupta 001; Vu Nguyen 001; Svetha Venkatesh (ICML, 2017)

High Dimensional Bayesian Optimization using Dropout. - Cheng Li 003; Sunil Gupta 001; Santu Rana; Vu Nguyen 001; Svetha Venkatesh; Alistair Shilton (IJCAI, 2017)

Budgeted Batch Bayesian Optimization With Unknown Batch Sizes. - Vu Nguyen 001; Santu Rana; Sunil Gupta 001; Cheng Li 003; Svetha Venkatesh (CoRR, 2017)

Sparse Approximation for Gaussian Process with Derivative Observations. - Ang Yang; Cheng Li 003; Santu Rana; Sunil Gupta 001; Svetha Venkatesh (Australasian Conference on Artificial Intelligence, 2018)

Accelerating Experimental Design by Incorporating Experimenter Hunches. - Cheng Li 003; Santu Rana; Sunil Gupta 001; Vu Nguyen 001; Svetha Venkatesh; Alessandra Sutti; David Rubin de Celis Leal; Teo Slezak; Murray Height; Mazher Mohammed; Ian Gibson (ICDM, 2018)

Efficient Bayesian Optimisation Using Derivative Meta-model. - Ang Yang; Cheng Li 003; Santu Rana; Sunil Gupta 001; Svetha Venkatesh (PRICAI, 2018)

Kernel Pre-Training in Feature Space via m-Kernels. - Alistair Shilton; Sunil Gupta 001; Santu Rana; Pratibha Vellanki; Cheng Li 003; Svetha Venkatesh; Laurence Park 001; Alessandra Sutti; David Rubin; Thomas Dorin; Alireza Vahid; Murray Height; et al. (CoRR, 2018)

Practical Batch Bayesian Optimization for Less Expensive Functions. - Vu Nguyen 001; Sunil Gupta 001; Santu Rana; Cheng Li 003; Svetha Venkatesh (CoRR, 2018)

Efficient Bayesian Optimization for Uncertainty Reduction Over Perceived Optima Locations. - Vu Nguyen 001; Sunil Gupta 001; Santu Rana; My T. Thai; Cheng Li 003; Svetha Venkatesh (ICDM, 2019)

Explaining Black-Box Models Using Interpretable Surrogates. - Deepthi Praveenlal Kuttichira; Sunil Gupta 001; Cheng Li 003; Santu Rana; Svetha Venkatesh (PRICAI (1), 2019)

Sparse Spectrum Gaussian Process for Bayesian Optimisation. - Ang Yang; Cheng Li 003; Santu Rana; Sunil Gupta 001; Svetha Venkatesh (CoRR, 2019)

Filtering Bayesian optimization approach in weakly specified search space. - Vu Nguyen 001; Sunil Gupta 001; Santu Rana; Cheng Li 003; Svetha Venkatesh (Knowl. Inf. Syst., 2019)

Accelerated Bayesian Optimisation through Weight-Prior Tuning. - Alistair Shilton; Sunil Gupta 001; Santu Rana; Pratibha Vellanki; Cheng Li 003; Svetha Venkatesh; Laurence Park 001; Alessandra Sutti; David Rubin; Thomas Dorin; Alireza Vahid; Murray Height; et al. (AISTATS, 2020)

Factor Screening using Bayesian Active Learning and Gaussian Process Meta-Modelling. - Cheng Li 003; Santu Rana; Andrew Gill; Dang Nguyen 002; Sunil Gupta 001; Svetha Venkatesh (ICPR, 2020)

Incorporating Expert Prior Knowledge into Experimental Design via Posterior Sampling. - Cheng Li 003; Sunil Gupta 001; Santu Rana; Vu Nguyen 001; Antonio Robles-Kelly; Svetha Venkatesh (CoRR, 2020)

Hierarchically Fair Federated Learning. - Jingfeng Zhang; Cheng Li 003; Antonio Robles-Kelly; Mohan S. Kankanhalli (CoRR, 2020)

Incorporating expert prior in Bayesian optimisation via space warping. - Anil Ramachandran; Sunil Gupta 001; Santu Rana; Cheng Li 003; Svetha Venkatesh (Knowl. Based Syst., 2020)

Sparse Spectrum Gaussian Process for Bayesian Optimization. - Ang Yang; Cheng Li 003; Santu Rana; Sunil Gupta 001; Svetha Venkatesh (PAKDD (2), 2021)