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05/17/2023
OpenSLU: A Unified, Modularized, and Extensible Toolkit for Spoken Language Understanding
Spoken Language Understanding (SLU) is one of the core components of a t...
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04/19/2023
MixPro: Simple yet Effective Data Augmentation for Prompt-based Learning
Prompt-based learning reformulates downstream tasks as cloze problems by...
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04/18/2023
A Two-Stage Framework with Self-Supervised Distillation For Cross-Domain Text Classification
Cross-domain text classification aims to adapt models to a target domain...
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02/04/2023
Semantic-Guided Image Augmentation with Pre-trained Models
Image augmentation is a common mechanism to alleviate data scarcity in c...
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09/29/2020
A Framework of Learning Through Empirical Gain Maximization
We develop in this paper a framework of empirical gain maximization (EGM...
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09/27/2020
A Statistical Learning Assessment of Huber Regression
As one of the triumphs and milestones of robust statistics, Huber regres...
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09/24/2020
N-LTP: A Open-source Neural Chinese Language Technology Platform with Pretrained Models
We introduce N-LTP, an open-source Python Chinese natural language proce...
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06/19/2020
New Insights into Learning with Correntropy Based Regression
Stemming from information-theoretic learning, the correntropy criterion ...
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03/01/2018
Learning with Correntropy-induced Losses for Regression with Mixture of Symmetric Stable Noise
In recent years, correntropy and its applications in machine learning ha...
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03/01/2018
Learning with Correntripy-induced Losses for Regression with Mixture of Symmetric Stable Noise
In recent years, correntropy and its applications in machine learning ha...
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02/20/2017
A Statistical Learning Approach to Modal Regression
This paper studies the nonparametric modal regression problem systematic...
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07/13/2016
Kernel Density Estimation for Dynamical Systems
We study the density estimation problem with observations generated by c...
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05/10/2016