11 citations · 33 across the 8 of their papers we have counts for
8 papers
EPISODE: Episodic Gradient Clipping with Periodic Resampled Corrections for Federated Learning with Heterogeneous Data
Michael Crawshaw, Yajie Bao, Mingrui Liu
Gradient clipping is an important technique for deep neural networks with exploding gradients, such as recurrent neural networks. Recent studies have shown that the loss functions…
Selective conformal inference with false coverage-statement rate control
Yajie Bao, Yuyang Huo, Haojie Ren +1
Conformal inference is a popular tool for constructing prediction intervals (PI). We consider here the scenario of post-selection/selective conformal inference, that is PIs are rep…
An Information-Theoretic Approach to Transferability in Task Transfer Learning
Yajie Bao, Yang Li, Shao-Lun Huang +4
Task transfer learning is a popular technique in image processing applications that uses pre-trained models to reduce the supervision cost of related tasks. An important question i…
Fast Composite Optimization and Statistical Recovery in Federated Learning
Yajie Bao, Michael Crawshaw, Shan Luo +1
As a prevalent distributed learning paradigm, Federated Learning (FL) trains a global model on a massive amount of devices with infrequent communication. This paper investigates a…
A Learning- and Scenario-based MPC Design for Nonlinear Systems in LPV Framework with Safety and Stability Guarantees
Yajie Bao, Hossam S. Abbas, Javad Mohammadpour Velni
This paper presents a learning- and scenario-based model predictive control (MPC) design approach for systems modeled in linear parameter-varying (LPV) framework. Using input-outpu…
Optimal Lighting Control in Greenhouses Using Bayesian Neural Networks for Sunlight Prediction
Shirin Afzali, Yajie Bao, Marc W. van Iersel +1
Controlling the environmental parameters, including light in greenhouses, increases the crop yield; however, the electricity cost of supplemental lighting can be high. Therefore, t…
A Deep Reinforcement Learning-based Sliding Mode Control Design for Partially-known Nonlinear Systems
Sahand Mosharafian, Shirin Afzali, Yajie Bao +1
Presence of model uncertainties creates challenges for model-based control design, and complexity of the control design is further exacerbated when coping with nonlinear systems. T…
Varying Coefficient Linear Discriminant Analysis for Dynamic Data
Yajie Bao, Yuyang Liu
Linear discriminant analysis (LDA) is an important classification tool in statistics and machine learning. This paper investigates the varying coefficient LDA model for dynamic dat…