Cédric Archambeau

According to our database1, Cédric Archambeau authored at least 69 papers between 2002 and 2021.

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Bibliography

2021
Multi-objective Asynchronous Successive Halving.
CoRR, 2021

A multi-objective perspective on jointly tuning hardware and hyperparameters.
CoRR, 2021

Overfitting in Bayesian Optimization: an empirical study and early-stopping solution.
CoRR, 2021

A resource-efficient method for repeated HPO and NAS problems.
CoRR, 2021

Amazon SageMaker Automatic Model Tuning: Scalable Gradient-Free Optimization.
Proceedings of the KDD '21: The 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2021

BORE: Bayesian Optimization by Density-Ratio Estimation.
Proceedings of the 38th International Conference on Machine Learning, 2021

Hyperparameter Transfer Learning with Adaptive Complexity.
Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

Fair Bayesian Optimization.
Proceedings of the AIES '21: AAAI/ACM Conference on AI, 2021

On the Lack of Robust Interpretability of Neural Text Classifiers.
Proceedings of the Findings of the Association for Computational Linguistics: ACL/IJCNLP 2021, 2021

2020
Amazon SageMaker Automatic Model Tuning: Scalable Black-box Optimization.
CoRR, 2020

Amazon SageMaker Autopilot: a white box AutoML solution at scale.
CoRR, 2020

Pareto-efficient Acquisition Functions for Cost-Aware Bayesian Optimization.
CoRR, 2020

Fair Bayesian Optimization.
CoRR, 2020

Cost-aware Bayesian Optimization.
CoRR, 2020

Model-based Asynchronous Hyperparameter Optimization.
CoRR, 2020

LEEP: A New Measure to Evaluate Transferability of Learned Representations.
CoRR, 2020

Amazon SageMaker Autopilot: a white box AutoML solution at scale.
Proceedings of the Fourth Workshop on Data Management for End-To-End Machine Learning, 2020

LEEP: A New Measure to Evaluate Transferability of Learned Representations.
Proceedings of the 37th International Conference on Machine Learning, 2020

2019
Constrained Bayesian Optimization with Max-Value Entropy Search.
CoRR, 2019

Learning search spaces for Bayesian optimization: Another view of hyperparameter transfer learning.
CoRR, 2019

2018
Scalable Hyperparameter Transfer Learning.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

2017
An interpretable latent variable model for attribute applicability in the Amazon catalogue.
CoRR, 2017

Bayesian Optimization with Tree-structured Dependencies.
Proceedings of the 34th International Conference on Machine Learning, 2017

2016
Online optimization and regret guarantees for non-additive long-term constraints.
CoRR, 2016

Online Dual Decomposition for Performance and Delivery-Based Distributed Ad Allocation.
Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2016

Adaptive Algorithms for Online Convex Optimization with Long-term Constraints.
Proceedings of the 33nd International Conference on Machine Learning, 2016

2015
Latent IBP Compound Dirichlet Allocation.
IEEE Trans. Pattern Anal. Mach. Intell., 2015

Online Inference for Relation Extraction with a Reduced Feature Set.
CoRR, 2015

One-Pass Ranking Models for Low-Latency Product Recommendations.
Proceedings of the 21th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2015

2014
Overlapping Trace Norms in Multi-View Learning.
CoRR, 2014

Towards crowd-based customer service: a mixed-initiative tool for managing Q&A sites.
Proceedings of the CHI Conference on Human Factors in Computing Systems, 2014

2013
Connecting comments and tags: improved modeling of social tagging systems.
Proceedings of the Sixth ACM International Conference on Web Search and Data Mining, 2013

Error Prediction with Partial Feedback.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2013

Bringing Representativeness into Social Media Monitoring and Analysis.
Proceedings of the 46th Hawaii International Conference on System Sciences, 2013

Structured Penalties for Log-Linear Language Models.
Proceedings of the 2013 Conference on Empirical Methods in Natural Language Processing, 2013

2012
Variational Markov chain Monte Carlo for Bayesian smoothing of non-linear diffusions.
Comput. Stat., 2012

Plackett-Luce regression: A new Bayesian model for polychotomous data.
Proceedings of the Twenty-Eighth Conference on Uncertainty in Artificial Intelligence, 2012

2011
Robust Bayesian Matrix Factorisation.
Proceedings of the Fourteenth International Conference on Artificial Intelligence and Statistics, 2011

The sequence memoizer.
Commun. ACM, 2011

Sparse Bayesian Multi-Task Learning.
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

Mail2Wiki: posting and curating Wiki content from email.
Proceedings of the 16th International Conference on Intelligent User Interfaces, 2011

Mail2Wiki: low-cost sharing and early curation from email to wikis.
Proceedings of the Fifth International Conference on Communities and Technologies, 2011

2010
A Comparison of Variational and Markov Chain Monte Carlo Methods for Inference in Partially Observed Stochastic Dynamic Systems.
J. Signal Process. Syst., 2010

2009
The Variational Gaussian Approximation Revisited.
Neural Comput., 2009

Prediction of hot spot residues at protein-protein interfaces by combining machine learning and energy-based methods.
BMC Bioinform., 2009

Switching regulatory models of cellular stress response.
Bioinform., 2009

A stochastic memoizer for sequence data.
Proceedings of the 26th Annual International Conference on Machine Learning, 2009

2008
Mixtures of robust probabilistic principal component analyzers.
Neurocomputing, 2008

Improving the Robustness to Outliers of Mixtures of Probabilistic PCAs.
Proceedings of the Advances in Knowledge Discovery and Data Mining, 2008

Sparse probabilistic projections.
Proceedings of the Advances in Neural Information Processing Systems 21, 2008

Using Subspace-Based Template Attacks to Compare and Combine Power and Electromagnetic Information Leakages.
Proceedings of the Cryptographic Hardware and Embedded Systems, 2008

2007
Robust Bayesian clustering.
Neural Networks, 2007

Gaussian Process Approximations of Stochastic Differential Equations.
Proceedings of the Gaussian Processes in Practice, 2007

Towards Security Limits in Side-Channel Attacks.
IACR Cryptol. ePrint Arch., 2007

Variational Inference for Diffusion Processes.
Proceedings of the Advances in Neural Information Processing Systems 20, 2007

2006
Assessment of probability density estimation methods: Parzen window and finite Gaussian mixtures.
Proceedings of the International Symposium on Circuits and Systems (ISCAS 2006), 2006

Automatic Adjustment of Discriminant Adaptive Nearest Neighbor.
Proceedings of the 18th International Conference on Pattern Recognition (ICPR 2006), 2006

Robust probabilistic projections.
Proceedings of the Machine Learning, 2006

Template Attacks in Principal Subspaces.
Proceedings of the Cryptographic Hardware and Embedded Systems, 2006

2005
Probabilistic models in noisy environments : and their application to a visual prosthesis for the blind/.
PhD thesis, 2005

Manifold Constrained Finite Gaussian Mixtures.
Proceedings of the Computational Intelligence and Bioinspired Systems, 2005

Manifold Constrained Variational Mixtures.
Proceedings of the Artificial Neural Networks: Formal Models and Their Applications, 2005

2004
Prediction of visual perceptions with artificial neural networks in a visual prosthesis for the blind.
Artif. Intell. Medicine, 2004

Supervised Nonparametric Information Theoretic Classification.
Proceedings of the 17th International Conference on Pattern Recognition, 2004

Towards a Local Separation Performances Estimator Using Common ICA Contrast Functions?
Proceedings of the ESANN 2004, 2004

Flexible and Robust Bayesian Classification by Finite Mixture Models.
Proceedings of the ESANN 2004, 2004

2003
Locally Linear Embedding versus Isotop.
Proceedings of the ESANN 2003, 2003

On Convergence Problems of the EM Algorithm for Finite Gaussian Mixtures.
Proceedings of the ESANN 2003, 2003

2002
Width optimization of the Gaussian kernels in Radial Basis Function Networks.
Proceedings of the ESANN 2002, 2002


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