← Authors

Cheng Soon Ong

22 papers · 2005–2025 · 6 conferences · across top CS/AI conferences

Achievements

🧭 Keyword Pioneer 🐝 Cross-Pollinator (14) 🌈 Renaissance Researcher (7) πŸ—ΊοΈ Taxonomy Completionist (41) πŸŒ‰ Interdisciplinary Bridge 🐣 Hot Topic Early Bird 🌍 Conference Polyglot (6) πŸƒ Academic Marathon (20) πŸ† Grand Slam πŸ—ƒοΈ Keyword Collector (86) πŸ“ˆ Trend Setter πŸ’Ž Century Club (22) πŸ”₯ Unstoppable (5) πŸš€ Conference Pioneer

Conferences

ICML (7) JMLR (4) NIPS (4) ICLR (3) AAAI (2) AISTATS (2)

Top co-authors

Russell Tsuchida (5) Aditya Menon (4) Richard Nock (4) Mengyan Zhang (2) Dino Sejdinovic (2) Lars Petersson (1) Carl Edward Rasmussen (1) Edwin V. Bonilla (1) Ke Sun (1) Joachim M. Buhmann (1)

Keywords

gaussian process (3) convex optimization (2) neural network (2) bregman divergence (2) support vector machine (2) class-probability estimation (2) multi-armed bandit (2) kernel methods (2) principal component analysis (1) supervised learning (1) robust optimization (1) expectation maximization (1) adversarial training (1) positive unlabeled learning (1) optimal transport (1) density estimation (1) semidefinite programming (1) multiple instance learning (1) partition function (1) bayesian inference (1)

Papers

Position: We Need Responsible, Application-Driven (RAD) AI Research ICML 2025
Variational Search Distributions ICLR 2025
Exact, Fast and Expressive Poisson Point Processes via Squared Neural Families AAAI 2024
Deep equilibrium models as estimators for continuous latent variables AISTATS 2023
Factorized Fourier Neural Operators ICLR 2023
Squared Neural Families: A New Class of Tractable Density Models NIPS 2023
Gaussian Process Bandits with Aggregated Feedback AAAI 2022
Declarative nets that are equilibrium models ICLR 2022
Quantile Bandits for Best Arms Identification ICML 2021
Disentangled behavioural representations NIPS 2019
Monge blunts Bayes: Hardness Results for Adversarial Training ICML 2019
Representation Learning of Compositional Data NIPS 2018
A scaled Bregman theorem with applications NIPS 2016
Hawkes Processes with Stochastic Excitations ICML 2016
Linking losses for density ratio and class-probability estimation ICML 2016
Multivariate Spearman's $\rho$ for Aggregating Ranks Using Copulas JMLR 2016
Learning from Corrupted Binary Labels via Class-Probability Estimation ICML 2015
Ellipsoidal Multiple Instance Learning ICML 2013
Part & Clamp: Efficient Structured Output Learning AISTATS 2012
Bayesian Mixed-Effects Inference on Classification Performance in Hierarchical Data Sets JMLR 2012
The Need for Open Source Software in Machine Learning JMLR 2007
Learning the Kernel with Hyperkernels JMLR 2005