Ong, Cheng Soon

36 publications

NeurIPS 2025 Amortized Active Generation of Pareto Sets Daniel M. Steinberg, Asiri Wijesinghe, Rafael Oliveira, Piotr Koniusz, Cheng Soon Ong, Edwin V. Bonilla

ICML 2025 Position: We Need Responsible, Application-Driven (RAD) AI Research Sarah Hartman, Cheng Soon Ong, Julia Powles, Petra Kuhnert

NeurIPS 2025 Squared Families Are Useful Conjugate Priors Russell Tsuchida, Jiawei Liu, Cheng Soon Ong, Dino Sejdinovic

ICLR 2025 Variational Search Distributions Daniel M. Steinberg, Rafael Oliveira, Cheng Soon Ong, Edwin V. Bonilla

AAAI 2024 Exact, Fast and Expressive Poisson Point Processes via Squared Neural Families Russell Tsuchida, Cheng Soon Ong, Dino Sejdinovic

NeurIPSW 2024 Variational Search Distributions Daniel M. Steinberg, Rafael Oliveira, Cheng Soon Ong, Edwin V. Bonilla

AISTATS 2023 Deep Equilibrium Models as Estimators for Continuous Latent Variables Russell Tsuchida, Cheng Soon Ong

ICLR 2023 Factorized Fourier Neural Operators Alasdair Tran, Alexander Mathews, Lexing Xie, Cheng Soon Ong

MLJ 2023 Guest Editorial: Special Issue on Robust Machine Learning Ransalu Senanayake, Daniel J. Fremont, Mykel J. Kochenderfer, Alessio R. Lomuscio, Dragos D. Margineantu, Cheng Soon Ong

NeurIPS 2023 Squared Neural Families: A New Class of Tractable Density Models Russell Tsuchida, Cheng Soon Ong, Dino Sejdinovic

TMLR 2023 Stochastic Gradient Updates Yield Deep Equilibrium Kernels Russell Tsuchida, Cheng Soon Ong

ICLR 2022 Declarative Nets That Are Equilibrium Models Russell Tsuchida, Suk Yee Yong, Mohammad Ali Armin, Lars Petersson, Cheng Soon Ong

AAAI 2022 Gaussian Process Bandits with Aggregated Feedback Mengyan Zhang, Russell Tsuchida, Cheng Soon Ong

NeurIPSW 2022 When Are Equilibrium Networks Scoring Algorithms? Russell Tsuchida, Cheng Soon Ong

ICML 2021 Quantile Bandits for Best Arms Identification Mengyan Zhang, Cheng Soon Ong

NeurIPS 2019 Disentangled Behavioural Representations Amir Dezfouli, Hassan Ashtiani, Omar Ghattas, Richard Nock, Peter Dayan, Cheng Soon Ong

ICML 2019 Monge Blunts Bayes: Hardness Results for Adversarial Training Zac Cranko, Aditya Menon, Richard Nock, Cheng Soon Ong, Zhan Shi, Christian Walder

NeurIPS 2018 Representation Learning of Compositional Data Marta Avalos, Richard Nock, Cheng Soon Ong, Julien Rouar, Ke Sun

NeurIPS 2016 A Scaled Bregman Theorem with Applications Richard Nock, Aditya Menon, Cheng Soon Ong

ICML 2016 Hawkes Processes with Stochastic Excitations Young Lee, Kar Wai Lim, Cheng Soon Ong

ICML 2016 Linking Losses for Density Ratio and Class-Probability Estimation Aditya Menon, Cheng Soon Ong

JMLR 2016 Multivariate Spearman's $\rho$ for Aggregating Ranks Using Copulas Justin Bedő, Cheng Soon Ong

MLJ 2015 Introduction: Special Issue of Selected Papers of ACML 2013 Cheng Soon Ong, Wray L. Buntine, Tu Bao Ho, Masashi Sugiyama, Geoffrey I. Webb

ICML 2015 Learning from Corrupted Binary Labels via Class-Probability Estimation Aditya Menon, Brendan Van Rooyen, Cheng Soon Ong, Bob Williamson

ACML 2013 Preface Cheng Soon Ong, Tu Bao Ho

JMLR 2012 Bayesian Mixed-Effects Inference on Classification Performance in Hierarchical Data Sets Kay H. Brodersen, Christoph Mathys, Justin R. Chumbley, Jean Daunizeau, Cheng Soon Ong, Joachim M. Buhmann, Klaas E. Stephan

AISTATS 2012 Part & Clamp: Efficient Structured Output Learning Patrick Pletscher, Cheng Soon Ong

ICML 2011 Learning Output Kernels with Block Coordinate Descent Francesco Dinuzzo, Cheng Soon Ong, Peter V. Gehler, Gianluigi Pillonetto

ECML-PKDD 2010 Entropy and Margin Maximization for Structured Output Learning Patrick Pletscher, Cheng Soon Ong, Joachim M. Buhmann

ICML 2009 Optimized Expected Information Gain for Nonlinear Dynamical Systems Alberto Giovanni Busetto, Cheng Soon Ong, Joachim M. Buhmann

AISTATS 2009 Spanning Tree Approximations for Conditional Random Fields Patrick Pletscher, Cheng Soon Ong, Joachim Buhmann

ICML 2007 Multiclass Multiple Kernel Learning Alexander Zien, Cheng Soon Ong

JMLR 2007 The Need for Open Source Software in Machine Learning Sören Sonnenburg, Mikio L. Braun, Cheng Soon Ong, Samy Bengio, Leon Bottou, Geoffrey Holmes, Yann LeCun, Klaus-Robert Müller, Fernando Pereira, Carl Edward Rasmussen, Gunnar Rätsch, Bernhard Schölkopf, Alexander Smola, Pascal Vincent, Jason Weston, Robert Williamson

JMLR 2005 Learning the Kernel with Hyperkernels Cheng Soon Ong, Alexander J. Smola, Robert C. Williamson

ICML 2004 Learning with Non-Positive Kernels Cheng Soon Ong, Xavier Mary, Stéphane Canu, Alexander J. Smola

ICML 2003 Machine Learning with Hyperkernels Cheng Soon Ong, Alexander J. Smola