Asia
Learning nonlinear level sets for dimensionality reduction in function approximation
Guannan Zhang, Jiaxin Zhang, Jacob Hinkle
Neural Information Processing Systems http://nips.cc/
On the convergence of single-call stochastic extra-gradient methods
Yu-Guan Hsieh, Franck Iutzeler, Jérôme Malick, Panayotis Mertikopoulos
VI problems; logarithmic factors ignored throughout. A box indicates a contribution from this paper.
Stochastic Continuous Greedy ++: When Upper and Lower Bounds Match
Amin Karbasi, Hamed Hassani, Aryan Mokhtari, Zebang Shen
Neural Information Processing Systems http://nips.cc/
GRU-ODE-Bayes: Continuous modeling of sporadically-observed time series
Modeling real-world multidimensional time series can be particularly challenging when these are sporadically observed ( i.e., sampling is irregular both in time
SQ Lower Bounds for Learning Mixtures of Linear Classifiers
We study the problem of learning mixtures of linear classifiers under Gaussian covariates.
