Statistical Learning
Third-order Smoothness Helps: Faster Stochastic Optimization Algorithms for Finding Local Minima
Yaodong Yu, Pan Xu, Quanquan Gu
Neural Information Processing Systems http://nips.cc/
A Stein variational Newton method
Gianluca Detommaso, Tiangang Cui, Youssef Marzouk, Alessio Spantini, Robert Scheichl
Neural Information Processing Systems http://nips.cc/
Thermostat-assisted continuously-tempered Hamiltonian Monte Carlo for Bayesian learning
Rui Luo, Jianhong Wang, Yaodong Yang, Jun WANG, Zhanxing Zhu
Neural Information Processing Systems http://nips.cc/
Unsupervised Meta-Learning for Few-Shot Image Classification
Siavash Khodadadeh, Ladislau Boloni, Mubarak Shah
Neural Information Processing Systems http://nips.cc/
Towards Understanding Acceleration Tradeoff between Momentum and Asynchrony in Nonconvex Stochastic Optimization
Tianyi Liu, Shiyang Li, Jianping Shi, Enlu Zhou, Tuo Zhao
Neural Information Processing Systems http://nips.cc/
Isometric Quotient Variational Auto-Encoders for Structure-Preserving Representation Learning In Huh
A question that arises is what structures should be represented from the data.
A Practical Algorithm for Distributed Clustering and Outlier Detection
Jiecao Chen, Erfan Sadeqi Azer, Qin Zhang
Neural Information Processing Systems http://nips.cc/
The Cells Out of Sample (COOS) dataset and benchmarks for measuring out-of-sample generalization of image classifiers
Alex Lu, Amy Lu, Wiebke Schormann, Marzyeh Ghassemi, David Andrews, Alan Moses
We created a public dataset of 132,209 images of mouse cells, COOS-7 (Cells Out Of Sample 7-Class).