Cheng Li

Publication Activity (10 Years)

Years Active: 2013-2021
Publications (10 Years): 28

Top Topics

Multiple Instance

Top Venues

Knowl. Inf. Syst.

Publications

Ang Yang, Cheng Li, Santu Rana, Sunil Gupta, Svetha Venkatesh
Sparse Spectrum Gaussian Process for Bayesian Optimization. PAKDD (2) (2021)
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)
Anil Ramachandran, Sunil Gupta, Santu Rana, Cheng Li, Svetha Venkatesh
Incorporating Expert Prior in Bayesian Optimisation via Space Warping. CoRR (2020)
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)
Cheng Li, Sunil Gupta, Santu Rana, Vu Nguyen, Antonio Robles-Kelly, Svetha Venkatesh
Incorporating Expert Prior Knowledge into Experimental Design via Posterior Sampling. CoRR (2020)
Anil Ramachandran, Sunil Gupta, Santu Rana, Cheng Li, Svetha Venkatesh
Incorporating expert prior in Bayesian optimisation via space warping. Knowl. Based Syst. 195 (2020)
Ang Yang, Cheng Li, Santu Rana, Sunil Gupta, Svetha Venkatesh
Sparse Spectrum Gaussian Process for Bayesian Optimisation. CoRR (2019)
Vu Nguyen, Sunil Gupta, Santu Rana, My Thai, Cheng Li, Svetha Venkatesh
Efficient Bayesian Optimization for Uncertainty Reduction Over Perceived Optima Locations. ICDM (2019)
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 (2019)
Vu Nguyen, Sunil Gupta, Santu Rana, Cheng Li, Svetha Venkatesh
Filtering Bayesian optimization approach in weakly specified search space. Knowl. Inf. Syst. 60 (1) (2019)
Deepthi Praveenlal Kuttichira, Sunil Gupta, Cheng Li, Santu Rana, Svetha Venkatesh
Explaining Black-Box Models Using Interpretable Surrogates. PRICAI (1) (2019)
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 (2018)
Ang Yang, Cheng Li, Santu Rana, Sunil Gupta, Svetha Venkatesh
Efficient Bayesian Optimisation Using Derivative Meta-model. PRICAI (2018)
Vu Nguyen, Sunil Gupta, Santu Rana, Cheng Li, Svetha Venkatesh
Practical Batch Bayesian Optimization for Less Expensive Functions. CoRR (2018)
Ang Yang, Cheng Li, Santu Rana, Sunil Gupta, Svetha Venkatesh
Sparse Approximation for Gaussian Process with Derivative Observations. Australasian Conference on Artificial Intelligence (2018)
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)
Vu Nguyen, Sunil Gupta, Santu Rana, Cheng Li, Svetha Venkatesh
Bayesian Optimization in Weakly Specified Search Space. ICDM (2017)
Cheng Li, Sunil Gupta, Santu Rana, Vu Nguyen, Svetha Venkatesh, Alistair Shilton
High Dimensional Bayesian Optimization using Dropout. IJCAI (2017)
Vu Nguyen, Sunil Gupta, Santu Rana, Cheng Li, Svetha Venkatesh
Regret for Expected Improvement over the Best-Observed Value and Stopping Condition. ACML (2017)
Vu Nguyen, Santu Rana, Sunil Gupta, Cheng Li, Svetha Venkatesh
Budgeted Batch Bayesian Optimization With Unknown Batch Sizes. CoRR (2017)
Santu Rana, Cheng Li, Sunil Gupta, Vu Nguyen, Svetha Venkatesh
High Dimensional Bayesian Optimization with Elastic Gaussian Process. ICML (2017)
Vu Nguyen, Santu Rana, Sunil Kumar Gupta, Cheng Li, Svetha Venkatesh
Budgeted Batch Bayesian Optimization. ICDM (2016)
Iman Kamkar, Sunil Gupta, Cheng Li, Dinh Q. Phung, Svetha Venkatesh
Stable clinical prediction using graph support vector machines. ICPR (2016)
Cheng Li, Sunil Gupta, Santu Rana, Vu Nguyen, Svetha Venkatesh, David Ashely, Trish Livingston
Multiple adverse effects prediction in longitudinal cancer treatment. ICPR (2016)
Cheng Li, Santu Rana, Dinh Q. Phung, Svetha Venkatesh
Hierarchical Bayesian nonparametric models for knowledge discovery from electronic medical records. Knowl. Based Syst. 99 (2016)
Cheng Li, Santu Rana, Dinh Q. Phung, Svetha Venkatesh
Data clustering using side information dependent Chinese restaurant processes. Knowl. Inf. Syst. 47 (2) (2016)
Vu Nguyen, Sunil Gupta, Santu Rana, Cheng Li, Svetha Venkatesh
A Bayesian Nonparametric Approach for Multi-label Classification. ACML (2016)
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)
Cheng Li, Santu Rana, Dinh Q. Phung, Svetha Venkatesh
Small-Variance Asymptotics for Bayesian Nonparametric Models with Constraints. PAKDD (2) (2015)
Cheng Li, Santu Rana, Dinh Q. Phung, Svetha Venkatesh
Regularizing Topic Discovery in EMRs with Side Information by Using Hierarchical Bayesian Models. ICPR (2014)
Cheng Li, Dinh Q. Phung, Santu Rana, Svetha Venkatesh
Exploiting side information in distance dependent Chinese restaurant processes for data clustering. ICME (2013)