Showing 21–37 of 37 results
/ Date/ Name
Nov 16, 2022Vector-Valued Least-Squares Regression under Output Regularity AssumptionsMar 23, 2021A Pseudo-Metric between Probability Distributions based on Depth-Trimmed RegionsJun 13, 2024Deep Sketched Output Kernel Regression for Structured PredictionJul 1, 2024Restyling Unsupervised Concept Based Interpretable Networks with Generative ModelsNov 2, 2023Tailoring Mixup to Data for CalibrationMay 11, 2023Tackling Interpretability in Audio Classification Networks with Non-negative Matrix FactorizationFeb 20, 2023Sketch In, Sketch Out: Accelerating both Learning and Inference for Structured Prediction with KernelsOct 28, 2014Parametric Estimation of Ordinary Differential Equations with Orthogonality ConditionsNov 19, 2014Learning nonparametric differential equations with operator-valued kernels and gradient matchingMar 3, 2020Nonlinear Functional Output Regression: a Dictionary ApproachMar 2, 2026Conformal Graph Prediction with Z-Gromov Wasserstein DistancesSep 28, 2023Exploiting Edge Features in Graphs with Fused Network Gromov-Wasserstein DistanceJun 16, 2022Functional Output Regression with Infimal Convolution: Exploring the Huber and $ε$-insensitive LossesMay 28, 2018Autoencoding any Data through Kernel AutoencodersMar 22, 2018Structured Output Learning with Abstention: Application to Accurate Opinion PredictionMay 9, 2016Random Fourier Features for Operator-Valued KernelsNov 18, 2024Learning Differentiable Surrogate Losses for Structured Prediction