Nielsen, Frank

29 publications

NeurIPSW 2024 A New Geometric Approach of Adaptive Neighborhood Selection for Classification Alexandre Luís Magalhães Levada, Frank Nielsen, Michel Ferreira Cardia Haddad

ICML 2024 A Rate-Distortion View of Uncertainty Quantification Ifigeneia Apostolopoulou, Benjamin Eysenbach, Frank Nielsen, Artur Dubrawski

NeurIPS 2024 Hyperbolic Embeddings of Supervised Models Richard Nock, Ehsan Amid, Frank Nielsen, Alexander Soen, Manfred K. Warmuth

AAAI 2024 Optimal Transport with Tempered Exponential Measures Ehsan Amid, Frank Nielsen, Richard Nock, Manfred K. Warmuth

ICMLW 2023 Fisher-Rao and Pullback Hilbert Cone Distances on the Multivariate Gaussian Manifold with Applications to Simplification and Quantization of Mixtures Frank Nielsen

ICMLW 2023 Non-Linear Embeddings in Hilbert Simplex Geometry Frank Nielsen, Ke Sun

ICML 2023 Simplifying Momentum-Based Positive-Definite Submanifold Optimization with Applications to Deep Learning Wu Lin, Valentin Duruisseaux, Melvin Leok, Frank Nielsen, Mohammad Emtiyaz Khan, Mark Schmidt

NeurIPSW 2022 Practical Structured Riemannian Optimization with Momentum by Using Generalized Normal Coordinates Wu Lin, Valentin Duruisseaux, Melvin Leok, Frank Nielsen, Mohammad Emtiyaz Khan, Mark Schmidt

UAI 2021 Q-Paths: Generalizing the Geometric Annealing Path Using Power Means Vaden Masrani, Rob Brekelmans, Thang Bui, Frank Nielsen, Aram Galstyan, Greg Ver Steeg, Frank Wood

ICML 2021 Tractable Structured Natural-Gradient Descent Using Local Parameterizations Wu Lin, Frank Nielsen, Khan Mohammad Emtiyaz, Mark Schmidt

NeurIPSW 2020 Annealed Importance Sampling with Q-Paths Rob Brekelmans, Vaden Masrani, Thang D Bui, Frank Wood, Aram Galstyan, Greg Ver Steeg, Frank Nielsen

NeurIPSW 2020 Likelihood Ratio Exponential Families Rob Brekelmans, Frank Nielsen, Alireza Makhzani, Aram Galstyan, Greg Ver Steeg

UAI 2019 Sinkhorn AutoEncoders Giorgio Patrini, Rianne Berg, Patrick Forré, Marcello Carioni, Samarth Bhargav, Max Welling, Tim Genewein, Frank Nielsen

ICML 2017 DeepBach: A Steerable Model for Bach Chorales Generation Gaëtan Hadjeres, François Pachet, Frank Nielsen

ICML 2017 Relative Fisher Information and Natural Gradient for Learning Large Modular Models Ke Sun, Frank Nielsen

AAAI 2017 Tsallis Regularized Optimal Transport and Ecological Inference Boris Muzellec, Richard Nock, Giorgio Patrini, Frank Nielsen

IJCAI 2016 Clustering Financial Time Series: How Long Is Enough? Gautier Marti, Sébastien Andler, Frank Nielsen, Philippe Donnat

ICML 2016 K-Variates++: More Pluses in the K-Means++ Richard Nock, Raphael Canyasse, Roksana Boreli, Frank Nielsen

ICML 2016 Loss Factorization, Weakly Supervised Learning and Label Noise Robustness Giorgio Patrini, Frank Nielsen, Richard Nock, Marcello Carioni

ECML-PKDD 2012 Boosting Nearest Neighbors for the Efficient Estimation of Posteriors Roberto D'Ambrosio, Richard Nock, Wafa Bel Haj Ali, Frank Nielsen, Michel Barlaud

ICML 2011 On Tracking Portfolios with Certainty Equivalents on a Generalization of Markowitz Model: The Fool, the Wise and the Adaptive Richard Nock, Brice Magdalou, Eric Briys, Frank Nielsen

ECCV 2010 Texture Regimes for Entropy-Based Multiscale Image Analysis Sylvain Boltz, Frank Nielsen, Stefano Soatto

CVPR 2010 Total Bregman Divergence and Its Applications to Shape Retrieval Meizhu Liu, Baba C. Vemuri, Shun-ichi Amari, Frank Nielsen

NeurIPS 2008 On the Efficient Minimization of Classification Calibrated Surrogates Richard Nock, Frank Nielsen

IJCAI 2007 Real Boosting a La Carte with an Application to Boosting Oblique Decision Tree Claudia Henry, Richard Nock, Frank Nielsen

ECML-PKDD 2005 Fitting the Smallest Enclosing Bregman Ball Richard Nock, Frank Nielsen

CVPR 2005 Interactive Pinpoint Image Object Removal Frank Nielsen, Richard Nock

CVPR 2004 Grouping with Bias Revisited Richard Nock, Frank Nielsen

CVPR 2003 On Region Merging: The Statistical Soundness of Fast Sorting, with Applications Frank Nielsen, Richard Nock