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06/27/2023
Wasserstein Generative Regression
In this paper, we propose a new and unified approach for nonparametric r...
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05/19/2023
Complexity of Feed-Forward Neural Networks from the Perspective of Functional Equivalence
In this paper, we investigate the complexity of feed-forward neural netw...
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05/01/2023
Differentiable Neural Networks with RePU Activation: with Applications to Score Estimation and Isotonic Regression
We study the properties of differentiable neural networks activated by r...
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10/18/2022
Nonparametric Quantile Regression: Non-Crossing Constraints and Conformal Prediction
We propose a nonparametric quantile regression method using deep neural ...
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07/21/2022
Estimation of Non-Crossing Quantile Regression Process with Deep ReQU Neural Networks
We propose a penalized nonparametric approach to estimating the quantile...
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07/21/2021
Robust Nonparametric Regression with Deep Neural Networks
In this paper, we study the properties of robust nonparametric estimatio...
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07/10/2021
Deep Quantile Regression: Mitigating the Curse of Dimensionality Through Composition
This paper considers the problem of nonparametric quantile regression un...
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05/01/2021
Non-asymptotic Excess Risk Bounds for Classification with Deep Convolutional Neural Networks
In this paper, we consider the problem of binary classification with a c...
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04/14/2021
