Technology
From Stochastic Planning to Marginal MAP
Hao(Jackson) Cui, Radu Marinescu, Roni Khardon
Neural Information Processing Systems http://nips.cc/
Cross-modal Learningfor Image-Guided Point Cloud Shape Completion
Theimageencoderisbuiltwitha ResNet18 [36] as 6 Table 1: Mean 3).
Completing State Representations using Spectral Learning
Nan Jiang, Alex Kulesza, Satinder Singh
Neural Information Processing Systems http://nips.cc/
An Inexact Augmented Lagrangian Framework for Nonconvex Optimization with Nonlinear Constraints
Mehmet Fatih Sahin, Armin eftekhari, Ahmet Alacaoglu, Fabian Latorre, Volkan Cevher
Neural Information Processing Systems http://nips.cc/
Augmentation-Aware Self-Supervision for Data-Efficient GAN Training
We further encourage the generator to adversarially learn from the self-supervised discriminator by generating augmentation-predictable real and not fake data.
Continual Unsupervised Representation Learning
Dushyant Rao, Francesco Visin, Andrei Rusu, Razvan Pascanu, Yee Whye Teh, Raia Hadsell
Continual learning aims to improve the ability of modern learning systems todeal with non-stationary distributions, typically by attempting to learn a seriesof tasks sequentially.
Online Learning with an Unknown Fairness Metric
Stephen Gillen, Christopher Jung, Michael Kearns, Aaron Roth
We therefore assume that the algorithm has access to an oracle that knows intuitively what it means to be fair, but cannot explicitly enunciate the fairness metric.