Cheng Soon Ong

103 papers A* 20A 6B 4C 3Journal 56Unranked 13
YearRankTypeTitle / Venue / Authors
2026 J jnl
Active Flow Matching.
CoRR
Yashvir S. Grewal, Daniel M. Steinberg, Thang D. Bui, Cheng Soon Ong, Edwin V. Bonilla
2026 J jnl
Flowette: Flow Matching with Graphette Priors for Graph Generation.
CoRR
Asiri Wijesinghe, Sevvandi Kandanaarachchi, Daniel M. Steinberg, Cheng Soon Ong
2025 J jnl
A pseudo-inverse of a line graph.
CoRR
Sevvandi Kandanaarachchi, Philip Kilby, Cheng Soon Ong
2025 J jnl
Amortized Active Generation of Pareto Sets.
CoRR
Daniel M. Steinberg, Asiri Wijesinghe, Rafael Oliveira, Piotr Koniusz, Cheng Soon Ong, Edwin V. Bonilla
2025 A* conf
Fairness Evaluation with Item Response Theory.
WWW
Ziqi Xu, Sevvandi Kandanaarachchi, Cheng Soon Ong, Eirini Ntoutsi
2025 J jnl
Generalization Certificates for Adversarially Robust Bayesian Linear Regression.
CoRR
Mahalakshmi Sabanayagam, Russell Tsuchida, Cheng Soon Ong, Debarghya Ghoshdastidar
2025 J jnl
Graphon Mixtures.
CoRR
Sevvandi Kandanaarachchi, Cheng Soon Ong
2025 — conf
Position: We Need Responsible, Application-Driven (RAD) AI Research.
ICML (Position Papers)
Sarah Hartman, Cheng Soon Ong, Julia Powles, Petra Kuhnert
2025 J jnl
Position: We need responsible, application-driven (RAD) AI research.
CoRR
Sarah Hartman, Cheng Soon Ong, Julia Powles, Petra Kuhnert
2025 J jnl
Squared families: Searching beyond regular probability models.
CoRR
Russell Tsuchida, Jiawei Liu, Cheng Soon Ong, Dino Sejdinovic
2025 A* conf
Variational Search Distributions.
ICLR
Daniel M. Steinberg, Rafael Oliveira, Cheng Soon Ong, Edwin V. Bonilla
2024 A* conf
Exact, Fast and Expressive Poisson Point Processes via Squared Neural Families.
AAAI
Russell Tsuchida, Cheng Soon Ong, Dino Sejdinovic
2024 J jnl
Exact, Fast and Expressive Poisson Point Processes via Squared Neural Families.
CoRR
Russell Tsuchida, Cheng Soon Ong, Dino Sejdinovic
2024 J jnl
Fairness Evaluation with Item Response Theory.
CoRR
Ziqi Xu, Sevvandi Kandanaarachchi, Cheng Soon Ong, Eirini Ntoutsi
2024 J jnl
Graphons of Line Graphs.
CoRR
Sevvandi Kandanaarachchi, Cheng Soon Ong
2024 J jnl
Indirect Query Bayesian Optimization with Integrated Feedback.
CoRR
Mengyan Zhang, Shahine Bouabid, Cheng Soon Ong, Seth R. Flaxman, Dino Sejdinovic
2024 J jnl
Variational Search Distributions.
CoRR
Daniel M. Steinberg, Rafael Oliveira, Cheng Soon Ong, Edwin V. Bonilla
2023 A conf
Deep equilibrium models as estimators for continuous latent variables.
AISTATS
Russell Tsuchida, Cheng Soon Ong
2023 A* conf
Factorized Fourier Neural Operators.
ICLR
Alasdair Tran, Alexander Patrick Mathews, Lexing Xie, Cheng Soon Ong
2023 J jnl
Guest Editorial: Special issue on robust machine learning.
Mach. Learn.
Ransalu Senanayake, Daniel J. Fremont, Mykel J. Kochenderfer, Alessio R. Lomuscio, Dragos D. Margineantu, Cheng Soon Ong
2023 A* conf
Squared Neural Families: A New Class of Tractable Density Models.
NeurIPS
Russell Tsuchida, Cheng Soon Ong, Dino Sejdinovic
2023 J jnl
Squared Neural Families: A New Class of Tractable Density Models.
CoRR
Russell Tsuchida, Cheng Soon Ong, Dino Sejdinovic
2023 J jnl
Stochastic gradient updates yield deep equilibrium kernels.
Trans. Mach. Learn. Res.
Russell Tsuchida, Cheng Soon Ong
2023 J jnl
Uncertainty Quantification of the Virial Black Hole Mass with Conformal Prediction.
CoRR
Suk Yee Yong, Cheng Soon Ong
2022 A* conf
Declarative nets that are equilibrium models.
ICLR
Russell Tsuchida, Suk Yee Yong, Mohammad Ali Armin, Lars Petersson, Cheng Soon Ong
2022 J jnl
Deep equilibrium models as estimators for continuous latent variables.
CoRR
Russell Tsuchida, Cheng Soon Ong
2022 A* conf
Gaussian Process Bandits with Aggregated Feedback.
AAAI
Mengyan Zhang, Russell Tsuchida, Cheng Soon Ong
2022 J jnl
Two-Stage Neural Contextual Bandits for Personalised News Recommendation.
CoRR
Mengyan Zhang, Thanh Nguyen-Tang, Fangzhao Wu, Zhenyu He, Xing Xie, Cheng Soon Ong
2021 J jnl
Factorized Fourier Neural Operators.
CoRR
Alasdair Tran, Alexander Patrick Mathews, Lexing Xie, Cheng Soon Ong
2021 J jnl
Gaussian Process Bandits with Aggregated Feedback.
CoRR
Mengyan Zhang, Russell Tsuchida, Cheng Soon Ong
2021 A* conf
Quantile Bandits for Best Arms Identification.
ICML
Mengyan Zhang, Cheng Soon Ong
2021 A* conf
Radflow: A Recurrent, Aggregated, and Decomposable Model for Networks of Time Series.
WWW
Alasdair Tran, Alexander Patrick Mathews, Cheng Soon Ong, Lexing Xie
2021 J jnl
Radflow: A Recurrent, Aggregated, and Decomposable Model for Networks of Time Series.
CoRR
Alasdair Tran, Alexander Patrick Mathews, Cheng Soon Ong, Lexing Xie
2021 J jnl
eQTLHap: a tool for comprehensive eQTL analysis considering haplotypic and genotypic effects.
Briefings Bioinform.
Ziad Al Bkhetan, Gursharan Chana, Cheng Soon Ong, Benjamin Goudey, Kotagiri Ramamohanarao
2020 J jnl
Quantile Bandits for Best Arms Identification with Concentration Inequalities.
CoRR
Mengyan Zhang, Cheng Soon Ong
2019 J jnl
Cold-start Playlist Recommendation with Multitask Learning.
CoRR
Dawei Chen, Cheng Soon Ong, Aditya Krishna Menon
2019 C conf
Costs and Benefits of Fair Representation Learning.
AIES
Daniel McNamara, Cheng Soon Ong, Robert C. Williamson
2019 A* conf
Disentangled behavioural representations.
NeurIPS
Amir Dezfouli, Hassan Ashtiani, Omar Ghattas, Richard Nock, Peter Dayan, Cheng Soon Ong
2019 A* conf
Monge blunts Bayes: Hardness Results for Adversarial Training.
ICML
Zac Cranko, Aditya Krishna Menon, Richard Nock, Cheng Soon Ong, Zhan Shi, Christian J. Walder
2019 J jnl
New Tricks for Estimating Gradients of Expectations.
CoRR
Christian J. Walder, Richard Nock, Cheng Soon Ong, Masashi Sugiyama
2018 J jnl
A Primer on Causal Analysis.
CoRR
Finnian Lattimore, Cheng Soon Ong
2018 J jnl
Cold-start playlist recommendation with multitask learning.
PeerJ Prepr.
Dawei Chen, Cheng Soon Ong, Aditya Krishna Menon
2018 J jnl
Combining active learning suggestions.
PeerJ Comput. Sci.
Alasdair Tran, Cheng Soon Ong, Christian Wolf
2018 J jnl
Monge beats Bayes: Hardness Results for Adversarial Training.
CoRR
Zac Cranko, Aditya Krishna Menon, Richard Nock, Cheng Soon Ong, Zhan Shi, Christian J. Walder
2018 A* conf
Representation Learning of Compositional Data.
NeurIPS
Marta Avalos, Richard Nock, Cheng Soon Ong, Julien Rouar, Ke Sun
2018 J jnl
Wheel Defect Detection With Machine Learning.
IEEE Trans. Intell. Transp. Syst.
Gabriel Krummenacher, Cheng Soon Ong, Stefan Koller, Seijin Kobayashi, Joachim M. Buhmann
2017 A conf
PathRec: Visual Analysis of Travel Route Recommendations.
RecSys
Dawei Chen, Dongwoo Kim, Lexing Xie, Minjeong Shin, Aditya Krishna Menon, Cheng Soon Ong, Iman Avazpour, John Grundy
2017 J jnl
PathRec: Visual Analysis of Travel Route Recommendations.
CoRR
Dawei Chen, Dongwoo Kim, Lexing Xie, Minjeong Shin, Aditya Krishna Menon, Cheng Soon Ong, Iman Avazpour, John Grundy
2017 J jnl
Provably Fair Representations.
CoRR
Daniel McNamara, Cheng Soon Ong, Robert C. Williamson
2017 — conf
Revisiting revisits in trajectory recommendation.
CitRec@RecSys
Aditya Krishna Menon, Dawei Chen, Lexing Xie, Cheng Soon Ong
2017 J jnl
Revisiting revisits in trajectory recommendation.
CoRR
Aditya Krishna Menon, Dawei Chen, Lexing Xie, Cheng Soon Ong
2017 J jnl
Structured Recommendation.
CoRR
Dawei Chen, Lexing Xie, Aditya Krishna Menon, Cheng Soon Ong
2017 J jnl
kWIP: The k-mer weighted inner product, a de novo estimator of genetic similarity.
PLoS Comput. Biol.
Kevin D. Murray, Christfried Webers, Cheng Soon Ong, Justin O. Borevitz, Norman Warthmann
2016 J jnl
A Modular Theory of Feature Learning.
CoRR
Daniel McNamara, Cheng Soon Ong, Robert C. Williamson
2016 — conf
A scaled Bregman theorem with applications.
NIPS
Richard Nock, Aditya Krishna Menon, Cheng Soon Ong
2016 J jnl
A scaled Bregman theorem with applications.
CoRR
Richard Nock, Aditya Krishna Menon, Cheng Soon Ong
2016 A* conf
Hawkes Processes with Stochastic Excitations.
ICML
Young Lee, Kar Wai Lim, Cheng Soon Ong
2016 J jnl
Hawkes Processes with Stochastic Excitations.
CoRR
Young Lee, Kar Wai Lim, Cheng Soon Ong
2016 A conf
Learning Points and Routes to Recommend Trajectories.
CIKM
Dawei Chen, Cheng Soon Ong, Lexing Xie
2016 J jnl
Learning Points and Routes to Recommend Trajectories.
CoRR
Dawei Chen, Cheng Soon Ong, Lexing Xie
2016 J jnl
Learning SVM in Kreĭn Spaces.
IEEE Trans. Pattern Anal. Mach. Intell.
Gaëlle Loosli, Stéphane Canu, Cheng Soon Ong
2016 A* conf
Linking losses for density ratio and class-probability estimation.
ICML
Aditya Krishna Menon, Cheng Soon Ong
2016 J jnl
Multivariate Spearman's rho for Aggregating Ranks Using Copulas.
J. Mach. Learn. Res.
Justin Bedo, Cheng Soon Ong
2016 A conf
Probabilistic Knowledge Graph Construction: Compositional and Incremental Approaches.
CIKM
Dongwoo Kim, Lexing Xie, Cheng Soon Ong
2016 J jnl
Probabilistic Knowledge Graph Construction: Compositional and Incremental Approaches.
CoRR
Dongwoo Kim, Lexing Xie, Cheng Soon Ong
2015 B conf
Discriminative concept learning network: Reveal high-level differential concepts from shallow architecture.
IJCNN
Qiao Wang, Sylvia Young, Aaron Harwood, Cheng Soon Ong
2015 J jnl
Introduction: special issue of selected papers of ACML 2013.
Mach. Learn.
Cheng Soon Ong, Wray L. Buntine, Tu Bao Ho, Masashi Sugiyama, Geoffrey I. Webb
2015 A* conf
Learning from Corrupted Binary Labels via Class-Probability Estimation.
ICML
Aditya Krishna Menon, Brendan van Rooyen, Cheng Soon Ong, Bob Williamson
2014 — conf
Cell density in prostate histopathology images as a measure of tumor distribution.
Digital Pathology
Hayley M. Reynolds, Scott Williams, Alan M. Zhang, Cheng Soon Ong, David Rawlinson, Rajib Chakravorty, Catherine Mitchell, Annette Haworth
2014 J jnl
Multivariate Spearman's rho for aggregating ranks using copulas.
CoRR
Justin Bedo, Cheng Soon Ong
2014 J jnl
Open science in machine learning.
CoRR
Joaquin Vanschoren, Mikio L. Braun, Cheng Soon Ong
2013 J jnl
Analytic center cutting plane method for multiple kernel learning.
Ann. Math. Artif. Intell.
Sharon Wulff, Cheng Soon Ong
2013 — conf
Applications of Class-Conditional Conformal Predictor in Multi-class Classification.
ICMLA (1)
Fan Shi, Cheng Soon Ong, Christopher Leckie
2013 C ed.
Asian Conference on Machine Learning, ACML 2013, Canberra, ACT, Australia, November 13-15, 2013
ACML
Cheng Soon Ong, Tu Bao Ho
2013 — ch.
Automated Analysis of Tissue Micro-Array Images on the Example of Renal Cell Carcinoma.
Similarity-Based Pattern Analysis and Recognition
Peter J. Schüffler, Thomas J. Fuchs, Cheng Soon Ong, Volker Roth, Joachim M. Buhmann
2013 — conf
Ellipsoidal Multiple Instance Learning.
ICML (2)
Gabriel Krummenacher, Cheng Soon Ong, Joachim M. Buhmann
2013 J jnl
Learning sparse classifiers with difference of convex functions algorithms.
Optim. Methods Softw.
Cheng Soon Ong, Le Thi Hoai An
2013 J jnl
Near-optimal experimental design for model selection in systems biology.
Bioinform.
Alberto Giovanni Busetto, Alain Hauser, Gabriel Krummenacher, Mikael Sunnåker, Sotiris Dimopoulos, Cheng Soon Ong, Jörg Stelling, Joachim M. Buhmann
2012 J jnl
Bayesian mixed-effects inference on classification performance in hierarchical data sets.
J. Mach. Learn. Res.
Kay Henning Brodersen, Christoph Mathys, Justin R. Chumbley, Jean Daunizeau, Cheng Soon Ong, Joachim M. Buhmann, Klaas E. Stephan
2012 A conf
Part & Clamp: Efficient Structured Output Learning.
AISTATS
Patrick Pletscher, Cheng Soon Ong
2011 — conf
Contextual Gaussian Process Bandit Optimization.
NIPS
Andreas Krause, Cheng Soon Ong
2011 J jnl
Generative Embedding for Model-Based Classification of fMRI Data.
PLoS Comput. Biol.
Kay Henning Brodersen, Thomas M. Schofield, Alexander P. Leff, Cheng Soon Ong, Ekaterina I. Lomakina, Joachim M. Buhmann, Klaas E. Stephan
2011 A* conf
Learning Output Kernels with Block Coordinate Descent.
ICML
Francesco Dinuzzo, Cheng Soon Ong, Peter V. Gehler, Gianluigi Pillonetto
2011 J jnl
Model-based feature construction for multivariate decoding.
NeuroImage
Kay Henning Brodersen, Florent Haiss, Cheng Soon Ong, Fabienne Jung, Marc Tittgemeyer, Joachim M. Buhmann, Bruno Weber, Klaas E. Stephan
2010 — conf
Computational TMA Analysis and Cell Nucleus Classification of Renal Cell Carcinoma.
DAGM-Symposium
Peter J. Schüffler, Thomas J. Fuchs, Cheng Soon Ong, Volker Roth, Joachim M. Buhmann
2010 — conf
Entropy and Margin Maximization for Structured Output Learning.
ECML/PKDD (3)
Patrick Pletscher, Cheng Soon Ong, Joachim M. Buhmann
2010 B conf
The Balanced Accuracy and Its Posterior Distribution.
ICPR
Kay Henning Brodersen, Cheng Soon Ong, Klaas Enno Stephan, Joachim M. Buhmann
2010 B conf
The Binormal Assumption on Precision-Recall Curves.
ICPR
Kay Henning Brodersen, Cheng Soon Ong, Klaas Enno Stephan, Joachim M. Buhmann
2009 A* conf
Optimized expected information gain for nonlinear dynamical systems.
ICML
Alberto Giovanni Busetto, Cheng Soon Ong, Joachim M. Buhmann
2009 A conf
Spanning Tree Approximations for Conditional Random Fields.
AISTATS
Patrick Pletscher, Cheng Soon Ong, Joachim M. Buhmann
2008 C conf
An Automated Combination of Kernels for Predicting Protein Subcellular Localization.
WABI
Cheng Soon Ong, Alexander Zien
2008 J jnl
Support Vector Machines and Kernels for Computational Biology.
PLoS Comput. Biol.
Asa Ben-Hur, Cheng Soon Ong, Sören Sonnenburg, Bernhard Schölkopf, Gunnar Rätsch
2007 A* conf
Multiclass multiple kernel learning.
ICML
Alexander Zien, Cheng Soon Ong
2007 J jnl
PALMA: mRNA to genome alignments using large margin algorithms.
Bioinform.
Uta Schulze, Bettina Hepp, Cheng Soon Ong, Gunnar Rätsch
2007 J jnl
The Need for Open Source Software in Machine Learning.
J. Mach. Learn. Res.
Sören Sonnenburg, Mikio L. Braun, Cheng Soon Ong, Samy Bengio, Léon Bottou, Geoffrey Holmes, Yann LeCun, Klaus-Robert Müller, Fernando Pereira, Carl Edward Rasmussen, Gunnar Rätsch, Bernhard Schölkopf, Alexander J. Smola, Pascal Vincent, Jason Weston, Robert C. Williamson
2006 — conf
PALMA: Perfect Alignments using Large Margin Algorithms.
German Conference on Bioinformatics
Gunnar Rätsch, Bettina Hepp, Uta Schulze, Cheng Soon Ong
2005 J jnl
Learning the Kernel with Hyperkernels.
J. Mach. Learn. Res.
Cheng Soon Ong, Alexander J. Smola, Robert C. Williamson
2005 — conf
Protein function prediction via graph kernels.
ISMB (Supplement of Bioinformatics)
Karsten M. Borgwardt, Cheng Soon Ong, Stefan Schönauer, S. V. N. Vishwanathan, Alexander J. Smola, Hans-Peter Kriegel
2004 A* conf
Learning with non-positive kernels.
ICML
Cheng Soon Ong, Xavier Mary, Stéphane Canu, Alexander J. Smola
2003 A* conf
Machine Learning with Hyperkernels.
ICML
Cheng Soon Ong, Alexander J. Smola
2002 — conf
Hyperkernels.
NIPS
Cheng Soon Ong, Alexander J. Smola, Robert C. Williamson
2000 — conf
On designing an automated Malaysian stemmer for the Malay language (poster session).
IRAL
Sock Yin Tai, Cheng Soon Ong, Noor Aida Abdullah
1999 B conf
A comparison of artificial neural networks and cluster analysis for typing biometrics authentication.
IJCNN
Leenesh Kumar Maisuria, Cheng Soon Ong, Wen Kin Lai