1 citations · 1 across the 6 of their papers we have counts for
7 papers
Elicitation and Decision Geometry in Single-Index Bandits
Sakshi Arya, Cheng Soon Ong
We study two-arm contextual bandits with arm-specific single indices and a shared unknown monotone link. Monotonicity makes the optimal action depend only on the contrast between t…
Position: We Need Responsible, Application-Driven (RAD) AI Research
Sarah Hartman, Cheng Soon Ong, Julia Powles +1
This position paper argues that achieving meaningful scientific and societal advances with artificial intelligence (AI) requires a responsible, application-driven approach (RAD) to…
Squared families: Searching beyond regular probability models
Russell Tsuchida, Jiawei Liu, Cheng Soon Ong +1
We introduce squared families, which are families of probability densities obtained by squaring a linear transformation of a statistic. Squared families are singular, however their…
Generalization Certificates for Adversarially Robust Bayesian Linear Regression
Mahalakshmi Sabanayagam, Russell Tsuchida, Cheng Soon Ong +1
Adversarial robustness of machine learning models is critical to ensuring reliable performance under data perturbations. Recent progress has been on point estimators, and this pape…
Indirect Query Bayesian Optimization with Integrated Feedback
Mengyan Zhang, Shahine Bouabid, Cheng Soon Ong +2
We develop the framework of Indirect Query Bayesian Optimization (IQBO), a new class of Bayesian optimization problems where the integrated feedback is given via a conditional expe…
TPCNet: Representation learning for HI mapping
Hiep Nguyen, Haiyang Tang, Matthew Alger +4
We introduce TPCNet, a neural network predictor that combines Convolutional and Transformer architectures with Positional encodings, for neutral atomic hydrogen (HI) spectral analy…
Exact, Fast and Expressive Poisson Point Processes via Squared Neural Families
Russell Tsuchida, Cheng Soon Ong, Dino Sejdinovic
We introduce squared neural Poisson point processes (SNEPPPs) by parameterising the intensity function by the squared norm of a two layer neural network. When the hidden layer is f…