Cheng Soon Ong

Orcid: 0000-0002-2302-9733

According to our database1, Cheng Soon Ong authored at least 78 papers between 1999 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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On csauthors.net:

Bibliography

2024
Variational Search Distributions.
CoRR, 2024

Graphons of Line Graphs.
CoRR, 2024

Exact, Fast and Expressive Poisson Point Processes via Squared Neural Families.
Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023
Stochastic gradient updates yield deep equilibrium kernels.
Trans. Mach. Learn. Res., 2023

Guest Editorial: Special issue on robust machine learning.
Mach. Learn., 2023

Uncertainty Quantification of the Virial Black Hole Mass with Conformal Prediction.
CoRR, 2023

Squared Neural Families: A New Class of Tractable Density Models.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Factorized Fourier Neural Operators.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

Deep equilibrium models as estimators for continuous latent variables.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

2022
Discriminative Concept Learning Network: Sample Source Code and Supplement (Project Archive).
Dataset, July, 2022

Two-Stage Neural Contextual Bandits for Personalised News Recommendation.
CoRR, 2022

Declarative nets that are equilibrium models.
Proceedings of the Tenth International Conference on Learning Representations, 2022

Gaussian Process Bandits with Aggregated Feedback.
Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021
eQTLHap: a tool for comprehensive eQTL analysis considering haplotypic and genotypic effects.
Briefings Bioinform., 2021

Radflow: A Recurrent, Aggregated, and Decomposable Model for Networks of Time Series.
Proceedings of the WWW '21: The Web Conference 2021, 2021

Quantile Bandits for Best Arms Identification.
Proceedings of the 38th International Conference on Machine Learning, 2021

2020
Quantile Bandits for Best Arms Identification with Concentration Inequalities.
CoRR, 2020

2019
New Tricks for Estimating Gradients of Expectations.
CoRR, 2019

Disentangled behavioural representations.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Monge blunts Bayes: Hardness Results for Adversarial Training.
Proceedings of the 36th International Conference on Machine Learning, 2019

Costs and Benefits of Fair Representation Learning.
Proceedings of the 2019 AAAI/ACM Conference on AI, Ethics, and Society, 2019

2018
Wheel Defect Detection With Machine Learning.
IEEE Trans. Intell. Transp. Syst., 2018

Cold-start playlist recommendation with multitask learning.
PeerJ Prepr., 2018

Combining active learning suggestions.
PeerJ Comput. Sci., 2018

Monge beats Bayes: Hardness Results for Adversarial Training.
CoRR, 2018

A Primer on Causal Analysis.
CoRR, 2018

Representation Learning of Compositional Data.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

2017
kWIP: The k-mer weighted inner product, a de novo estimator of genetic similarity.
PLoS Comput. Biol., 2017

Provably Fair Representations.
CoRR, 2017

Structured Recommendation.
CoRR, 2017

Revisiting revisits in trajectory recommendation.
Proceedings of International Workshop on Citizens for Recommender Systems, 2017

PathRec: Visual Analysis of Travel Route Recommendations.
Proceedings of the Eleventh ACM Conference on Recommender Systems, 2017

2016
Learning SVM in Kreĭn Spaces.
IEEE Trans. Pattern Anal. Mach. Intell., 2016

Multivariate Spearman's rho for Aggregating Ranks Using Copulas.
J. Mach. Learn. Res., 2016

A Modular Theory of Feature Learning.
CoRR, 2016

<i>SplAdder</i>: identification, quantification and testing of alternative splicing events from RNA-Seq data.
Bioinform., 2016

A scaled Bregman theorem with applications.
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Linking losses for density ratio and class-probability estimation.
Proceedings of the 33nd International Conference on Machine Learning, 2016

Hawkes Processes with Stochastic Excitations.
Proceedings of the 33nd International Conference on Machine Learning, 2016

Probabilistic Knowledge Graph Construction: Compositional and Incremental Approaches.
Proceedings of the 25th ACM International Conference on Information and Knowledge Management, 2016

Learning Points and Routes to Recommend Trajectories.
Proceedings of the 25th ACM International Conference on Information and Knowledge Management, 2016

2015
Introduction: special issue of selected papers of ACML 2013.
Mach. Learn., 2015

Discriminative concept learning network: Reveal high-level differential concepts from shallow architecture.
Proceedings of the 2015 International Joint Conference on Neural Networks, 2015

Learning from Corrupted Binary Labels via Class-Probability Estimation.
Proceedings of the 32nd International Conference on Machine Learning, 2015

2014
Open science in machine learning.
CoRR, 2014

Cell density in prostate histopathology images as a measure of tumor distribution.
Proceedings of the Medical Imaging 2014: Digital Pathology, 2014

2013
Automated Analysis of Tissue Micro-Array Images on the Example of Renal Cell Carcinoma.
Proceedings of the Similarity-Based Pattern Analysis and Recognition, 2013

Learning sparse classifiers with difference of convex functions algorithms.
Optim. Methods Softw., 2013

Near-optimal experimental design for model selection in systems biology.
Bioinform., 2013

Analytic center cutting plane method for multiple kernel learning.
Ann. Math. Artif. Intell., 2013

Applications of Class-Conditional Conformal Predictor in Multi-class Classification.
Proceedings of the 12th International Conference on Machine Learning and Applications, 2013

Ellipsoidal Multiple Instance Learning.
Proceedings of the 30th International Conference on Machine Learning, 2013

2012
Part & Clamp: Efficient Structured Output Learning.
Proceedings of the Fifteenth International Conference on Artificial Intelligence and Statistics, 2012

Bayesian mixed-effects inference on classification performance in hierarchical data sets.
J. Mach. Learn. Res., 2012

2011
Generative Embedding for Model-Based Classification of fMRI Data.
PLoS Comput. Biol., 2011

Model-based feature construction for multivariate decoding.
NeuroImage, 2011

Contextual Gaussian Process Bandit Optimization.
Proceedings of the Advances in Neural Information Processing Systems 24: 25th Annual Conference on Neural Information Processing Systems 2011. Proceedings of a meeting held 12-14 December 2011, 2011

Learning Output Kernels with Block Coordinate Descent.
Proceedings of the 28th International Conference on Machine Learning, 2011

2010
Entropy and Margin Maximization for Structured Output Learning.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2010

The Binormal Assumption on Precision-Recall Curves.
Proceedings of the 20th International Conference on Pattern Recognition, 2010

The Balanced Accuracy and Its Posterior Distribution.
Proceedings of the 20th International Conference on Pattern Recognition, 2010

Computational TMA Analysis and Cell Nucleus Classification of Renal Cell Carcinoma.
Proceedings of the Pattern Recognition, 2010

2009
<i>mGene.web</i>: a web service for accurate computational gene finding.
Nucleic Acids Res., 2009

Spanning Tree Approximations for Conditional Random Fields.
Proceedings of the Twelfth International Conference on Artificial Intelligence and Statistics, 2009

Optimized expected information gain for nonlinear dynamical systems.
Proceedings of the 26th Annual International Conference on Machine Learning, 2009

2008
Support Vector Machines and Kernels for Computational Biology.
PLoS Comput. Biol., 2008

An Automated Combination of Kernels for Predicting Protein Subcellular Localization.
Proceedings of the Algorithms in Bioinformatics, 8th International Workshop, 2008

2007
The Need for Open Source Software in Machine Learning.
J. Mach. Learn. Res., 2007

PALMA: mRNA to genome alignments using large margin algorithms.
Bioinform., 2007

Multiclass multiple kernel learning.
Proceedings of the Machine Learning, 2007

2006
PALMA: Perfect Alignments using Large Margin Algorithms.
Proceedings of the German Conference on Bioinformatics GCB 2006, 19.09. 2006, 2006

2005
Learning the Kernel with Hyperkernels.
J. Mach. Learn. Res., 2005

Protein function prediction via graph kernels.
Proceedings of the Proceedings Thirteenth International Conference on Intelligent Systems for Molecular Biology 2005, 2005

2004
Learning with non-positive kernels.
Proceedings of the Machine Learning, 2004

2003
Machine Learning with Hyperkernels.
Proceedings of the Machine Learning, 2003

2002
Hyperkernels.
Proceedings of the Advances in Neural Information Processing Systems 15 [Neural Information Processing Systems, 2002

2000
On designing an automated Malaysian stemmer for the Malay language (poster session).
Proceedings of the Fifth International Workshop on Information Retrieval with Asian Languages, 2000, Hong Kong, China, September 30, 2000

1999
A comparison of artificial neural networks and cluster analysis for typing biometrics authentication.
Proceedings of the International Joint Conference Neural Networks, 1999


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