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01/23/2023
On the Convergence of the Gradient Descent Method with Stochastic Fixed-point Rounding Errors under the Polyak-Lojasiewicz Inequality
When training neural networks with low-precision computation, rounding e...
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01/08/2023
CameraPose: Weakly-Supervised Monocular 3D Human Pose Estimation by Leveraging In-the-wild 2D Annotations
To improve the generalization of 3D human pose estimators, many existing...
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11/16/2022
De-biased lasso for stratified Cox models with application to the national kidney transplant data
The Scientific Registry of Transplant Recipients (SRTR) system has becom...
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07/24/2022
Statistical inference for high-dimensional generalized estimating equations
We propose a novel inference procedure for linear combinations of high-d...
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02/24/2022
On the influence of roundoff errors on the convergence of the gradient descent method with low-precision floating-point computation
The employment of stochastic rounding schemes helps prevent stagnation o...
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10/09/2021
De-biased Lasso for Generalized Linear Models with A Diverging Number of Covariates
Modeling and drawing inference on the joint associations between single ...
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06/06/2021
Statistical Inference for Cox Proportional Hazards Models with a Diverging Number of Covariates
For statistical inference on regression models with a diverging number o...
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03/24/2021
A Simple and Efficient Stochastic Rounding Method for Training Neural Networks in Low Precision
Conventional stochastic rounding (CSR) is widely employed in the trainin...
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06/23/2020
A Revisit to De-biased Lasso for Generalized Linear Models
De-biased lasso has emerged as a popular tool to draw statistical infere...
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05/31/2020
Improved stochastic rounding
Due to the limited number of bits in floating-point or fixed-point arith...
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07/17/2019
Accounting for total variation and robustness in profiling health care providers
Monitoring outcomes of health care providers, such as patient deaths, ho...
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06/20/2014
