Machine learning
I mainly focus on geometric structures and methods and losses for machine learning.
Credits go to my colleagues for fruitful collaborations.
Some works:
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project
Hyperbolic Embeddings of Supervised Models,
NeurIPS 2024.
(arXiv)
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project
A Rate-Distortion View of Uncertainty Quantification,
ICML 2024.
(arXiv)
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colab
Data Representations on the Bregman Manifold,
GRaM workshop, ICML 2024.
(arXiv)
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project
Optimal Transport with Tempered Exponential Measures,
AAAI 2024.
(arXiv)
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project
Simplifying Momentum-based
Positive-definite Submanifold Optimization with Applications to Deep Learning,
ICML 2023.
(arXiv)
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project
Non-linear Embeddings in Hilbert Simplex Geometry, TAG-ML 2023.
(arXiv)
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project
Fisher-Rao and pullback Hilbert cone distances on the multivariate
Gaussian manifold with applications to simplification and quantization of mixtures, TAG-ML 2023.
(arXiv)
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project
Tractable structured natural-gradient descent using local parameterizations, ICML 2021.
(arXiv)
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project
q-Paths: Generalizing the geometric annealing path using power means, UAI 2021.
(arXiv)
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project
Sinkhorn AutoEncoders, UAI 2020.
(arXiv)
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project
DeepBach: a Steerable Model for Bach Chorales Generation, ICML 2017.
(arXiv)
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project
Relative Fisher Information and Natural Gradient for Learning Large Modular Models, ICML 2017.
(arXiv)
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project
Tsallis Regularized Optimal Transport and Ecological Inference, AAAI 2017.
(arXiv)
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project
k-variates++: more pluses in the k-means++, ICML 2016.
(arXiv)
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project
Loss factorization, weakly supervised learning and label noise robustness, ICML 2016.
(arXiv)
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Clustering Financial Time Series: How Long Is Enough?, IJCAI 2016.
(arXiv)
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project
Exploring and measuring non-linear correlations: Copulas, Lightspeed Transportation and Clustering,
NeurIPS Time Series Workshop 2016.
(arXiv)
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Boosting Nearest Neighbors for the Efficient Estimation of Posteriors, ECML/PKDD 2012.
(hal)
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On tracking portfolios with certainty equivalents on a generalization of Markowitz model:
the Fool, the Wise and the Adaptive, ICML 11.
(arXiv)
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Boosting Bayesian MAP Classification, ICPR 2010.
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On the efficient minimization of convex surrogates in supervised learning, ICPR 2008.
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Real Boosting a la Carte with an Application to Boosting Oblique Decision Tree, IJCAI 2007.
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journal
A Real Generalization of Discrete AdaBoost, ECAI 2006, Artificial Intelligence 2007.
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Soft Uncoupling of Markov Chains for Permeable Language Distinction: A New Algorithm, ECAI 2006.
(arXiv)
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Fitting the Smallest Enclosing Bregman Ball, ECML 2005.