Matthias W. Seeger
Publication record assembled from the DBLP archive of ranked conferences.
Papers indexed
21
Venues
6
Active years
2000–2024
Best venue rank
A*
Where they publish
Papers
21 indexed papers, newest first.
| Year | Venue | Title | Authors |
|---|---|---|---|
| 2024 | ICML | Explaining Probabilistic Models with Distributional Values. | Luca Franceschi, Michele Donini, Cdric Archambeau, Matthias W. Seeger |
| 2023 | ICML | Optimizing Hyperparameters with Conformal Quantile Regression. | David Salinas, Jacek Golebiowski, Aaron Klein, Matthias W. Seeger, Cdric Archambeau |
| 2021 | ICML | BORE: Bayesian Optimization by Density-Ratio Estimation. | Louis C. Tiao, Aaron Klein, Matthias W. Seeger, Edwin V. Bonilla, Cdric Archambeau, Fabio Ramos |
| 2021 | KDD | Amazon SageMaker Automatic Model Tuning: Scalable Gradient-Free Optimization. | Valerio Perrone, Huibin Shen, Aida Zolic, Iaroslav Shcherbatyi, Amr Ahmed, Tanya Bansal, Michele Donini, Fela Winkelmolen, Rodolphe Jenatton, Jean Baptiste Faddoul, Barbara Pogorzelska, Miroslav Miladinovic, Krishnaram Kenthapadi, Matthias W. Seeger, Cdric Archambeau |
| 2021 | UAI | A Nonmyopic Approach to Cost-Constrained Bayesian Optimization. | Eric Hans Lee, David Eriksson, Valerio Perrone, Matthias W. Seeger |
| 2020 | ICML | LEEP: A New Measure to Evaluate Transferability of Learned Representations. | Cuong V. Nguyen, Tal Hassner, Matthias W. Seeger, Cdric Archambeau |
| 2017 | ICML | Bayesian Optimization with Tree-structured Dependencies. | Rodolphe Jenatton, Cdric Archambeau, Javier Gonzlez, Matthias W. Seeger |
| 2015 | ACML | Expectation Propagation for Rectified Linear Poisson Regression. | Young-Jun Ko, Matthias W. Seeger |
| 2014 | AISTATS | Scalable Collaborative Bayesian Preference Learning. | Mohammad Emtiyaz Khan, Young-Jun Ko, Matthias W. Seeger |
| 2013 | ICML | Fast Dual Variational Inference for Non-Conjugate Latent Gaussian Models. | Mohammad Emtiyaz Khan, Aleksandr Y. Aravkin, Michael P. Friedlander, Matthias W. Seeger |
| 2012 | ICML | Large Scale Variational Bayesian Inference for Structured Scale Mixture Models. | Young-Jun Ko, Matthias W. Seeger |
| 2010 | ICML | Gaussian Covariance and Scalable Variational Inference. | Matthias W. Seeger |
| 2010 | ICML | Gaussian Process Optimization in the Bandit Setting: No Regret and Experimental Design. | Niranjan Srinivas, Andreas Krause, Sham M. Kakade, Matthias W. Seeger |
| 2009 | ICML | Convex variational Bayesian inference for large scale generalized linear models. | Hannes Nickisch, Matthias W. Seeger |
| 2009 | ICML | Workshop summary: Numerical mathematics in machine learning. | Matthias W. Seeger, Suvrit Sra, John P. Cunningham |
| 2008 | ESANN | Learning Inverse Dynamics: a Comparison. | Duy Nguyen-Tuong, Jan Peters, Matthias W. Seeger, Bernhard Schlkopf |
| 2008 | ICML | Compressed sensing and Bayesian experimental design. | Matthias W. Seeger, Hannes Nickisch |
| 2005 | AISTATS | Semiparametric latent factor models. | Yee Whye Teh, Matthias W. Seeger, Michael I. Jordan |
| 2003 | AISTATS | Fast Forward Selection to Speed Up Sparse Gaussian Process Regression. | Matthias W. Seeger, Christopher K. I. Williams, Neil D. Lawrence |
| 2001 | ICML | An Improved Predictive Accuracy Bound for Averaging Classifiers. | John Langford, Matthias W. Seeger, Nimrod Megiddo |
| 2000 | ICML | The Effect of the Input Density Distribution on Kernel-based Classifiers. | Christopher K. I. Williams, Matthias W. Seeger |