Europe
Large Scale Structure of Neural Network Loss Landscapes
Stanislav Fort, Stanislaw Jastrzebski
Neural Information Processing Systems http://nips.cc/
Generalization in Generative Adversarial Networks: A Novel Perspective from Privacy Protection
Bingzhe Wu, Shiwan Zhao, Chaochao Chen, Haoyang Xu, Li Wang, Xiaolu Zhang, Guangyu Sun, Jun Zhou
Some recent studies attempted to explore this problemindifferentcontexts.
ChimpACT: A Longitudinal Dataset for Understanding Chimpanzee Behaviors
Studying the behavior of non-human primates is essential for gaining evolutionary insights (Langer-graber et al., 2012), conducting biomedical research (Schapiro et al., 2005), and improving animal
Fast and Accurate Least-Mean-Squares Solvers
Alaa Maalouf, Ibrahim Jubran, Dan Feldman
Generalization for streaming and distributed (big) data is trivial.
ArchimedesMeetsPrivacy: OnPrivatelyEstimatingQuantilesinHighDimensions UnderMinimalAssumptions
Computing statistics of large, complex high-dimensional datasets under privacy constraints is a fundamental challenge in modern data science.
Credal Learning Theory
Statistical learning theory is the foundation of machine learning, providing theoretical bounds for the risk of models learned from a (single) training set, assumed to issue from an unknown probability distribution.