3 papers
cs.AI2020
Autonomous Control of a Particle Accelerator using Deep Reinforcement Learning
Xiaoying Pang, Sunil Thulasidasan, Larry Rybarcyk
We describe an approach to learning optimal control policies for a large, linear particle accelerator using deep reinforcement learning coupled with a high-fidelity physics engine.…
stat.ML2019
On Mixup Training: Improved Calibration and Predictive Uncertainty for Deep Neural Networks
Sunil Thulasidasan, Gopinath Chennupati, Jeff Bilmes +2
Mixup~\cite{zhang2017mixup} is a recently proposed method for training deep neural networks where additional samples are generated during training by convexly combining random pair…
stat.ML2019
Combating Label Noise in Deep Learning Using Abstention
Sunil Thulasidasan, Tanmoy Bhattacharya, Jeff Bilmes +2
We introduce a novel method to combat label noise when training deep neural networks for classification. We propose a loss function that permits abstention during training thereby…