Cheng Soon Ong
22 papers · 2005–2025 · 6 conferences · across top CS/AI conferences
Achievements
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🏃 Academic Marathon (20) 🌍 Conference Polyglot (6) 🧭 Keyword Pioneer 🌉 Interdisciplinary Bridge 🐣 Hot Topic Early Bird
🐣
Hot Topic Early Bird
🌍
Conference Polyglot
(6)
🏃
Academic Marathon
(20)
🏆
Grand Slam
🗃️
Keyword Collector
(86)
📈
Trend Setter
💎
Century Club
(22)
🔥
Unstoppable
(5)
🚀
Conference Pioneer
Conferences
ICML (7)
JMLR (4)
NIPS (4)
ICLR (3)
AAAI (2)
AISTATS (2)
Top co-authors
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