Sample Efficient Interactive End-to-End Deep Learning for Self-Driving Cars with Selective Multi-Class Safe Dataset Aggregation
IEEE/RJS International Conference on Intelligent RObots and Systems（2019）
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sample efficient interactive end-to-end deep,self-driving cars,selective multiclass Safe Dataset,sample efficient end-to-end deep learning method,expert driver,end-to-end imitation learning,car policies,expert policy,deep neural network,driving policy,current learned policy,trajectory classes,sampling algorithm,standard safe dagger algorithm,safe dataset aggregation approach
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