Asia
PICProp: Physics-Informed Confidence Propagation for Uncertainty Quantification
Standard approaches for uncertainty quantification in deep learning and physics-informed learning have persistent limitations.
Unsupervised Skill Discoveryvia Recurrent Skill Training
Thus written = argm JR( ).
Fast Rates of ERM and Stochastic Approximation: Adaptive to Error Bound Conditions
Mingrui Liu, Xiaoxuan Zhang, Lijun Zhang, Rong Jin, Tianbao Yang
Error bound conditions (EBC) are properties that characterize the growth of an objectivefunction when apoint ismovedawayfrom theoptimal set.
Object-Oriented Dynamics Predictor
Guangxiang Zhu, Zhiao Huang, Chongjie Zhang
Neural Information Processing Systems http://nips.cc/
Variational Structured Semantic Inference for Diverse Image Captioning
Fuhai Chen, Rongrong Ji, Jiayi Ji, Xiaoshuai Sun, Baochang Zhang, Xuri Ge, Yongjian Wu, Feiyue Huang, Yan Wang
Neural Information Processing Systems http://nips.cc/
Cost
We then provide an algorithm to efficiently sketch input data using such embeddings. The sketch size of the embedding used in the algorithm has a linear dependence on the number of sketching dimensions of the input.