Statistical Learning
Constrained Graph Variational Autoencoders for Molecule Design
Qi Liu, Miltiadis Allamanis, Marc Brockschmidt, Alexander Gaunt
Neural Information Processing Systems http://nips.cc/
Infinite-Horizon Gaussian Processes
Arno Solin, James Hensman, Richard E. Turner
Neural Information Processing Systems http://nips.cc/
Fast Sparse Group Lasso
Yasutoshi Ida, Yasuhiro Fujiwara, Hisashi Kashima
However,asan update ofonlyoneparameter group depends onalltheparameter groups ordata points, the computation cost is high when the number of the parameters or data points islarge. This paper proposes afast Block Coordinate Descent for Sparse GroupLasso.
Qsparse-local-SGD: Distributed SGD with Quantization, Sparsification and Local Computations
Debraj Basu, Deepesh Data, Can Karakus, Suhas Diggavi
Neural Information Processing Systems http://nips.cc/
Scaling Up Differentially Private LASSO Regularized Logistic Regression via Faster Frank-Wolfe Iterations
Note that lower values of ϵ and δ correspond to stronger privacy.
The Pessimistic Limits and Possibilities of Margin-based Losses in Semi-supervised Learning
Neural Information Processing Systems http://nips.cc/
Dirichlet-based Gaussian Processes for Large-scale Calibrated Classification
Dimitrios Milios, Raffaello Camoriano, Pietro Michiardi, Lorenzo Rosasco, Maurizio Filippone
Neural Information Processing Systems http://nips.cc/
Generalizing Point Embeddings using the Wasserstein Space of Elliptical Distributions
Neural Information Processing Systems http://nips.cc/