13 citations · 28 across the 9 of their papers we have counts for
11 papers
Robust Bandit Learning with Imperfect Context
Jianyi Yang, Shaolei Ren
A standard assumption in contextual multi-arm bandit is that the true context is perfectly known before arm selection. Nonetheless, in many practical applications (e.g., cloud reso…
Distributed Thompson Sampling
Jing Dong, Tan Li, Shaolei Ren +1
We study a cooperative multi-agent multi-armed bandits with M agents and K arms. The goal of the agents is to minimized the cumulative regret. We adapt a traditional Thompson Sampl…
A Quantitative Perspective on Values of Domain Knowledge for Machine Learning
Jianyi Yang, Shaolei Ren
With the exploding popularity of machine learning, domain knowledge in various forms has been playing a crucial role in improving the learning performance, especially when training…
Scaling Up Deep Neural Network Optimization for Edge Inference
Bingqian Lu, Jianyi Yang, Shaolei Ren
Deep neural networks (DNNs) have been increasingly deployed on and integrated with edge devices, such as mobile phones, drones, robots and wearables. To run DNN inference directly…
Increasing Trustworthiness of Deep Neural Networks via Accuracy Monitoring
Zhihui Shao, Jianyi Yang, Shaolei Ren
Inference accuracy of deep neural networks (DNNs) is a crucial performance metric, but can vary greatly in practice subject to actual test datasets and is typically unknown due to…
Calibrating Deep Neural Network Classifiers on Out-of-Distribution Datasets
Zhihui Shao, Jianyi Yang, Shaolei Ren
To increase the trustworthiness of deep neural network (DNN) classifiers, an accurate prediction confidence that represents the true likelihood of correctness is crucial. Towards t…