84 citations · 518 across the 35 of their papers we have counts for
5 papers · 1 filter
Orthogonal Gradient Descent for Continual Learning
Mehrdad Farajtabar, Navid Azizan, Alex Mott +1
Neural networks are achieving state of the art and sometimes super-human performance on learning tasks across a variety of domains. Whenever these problems require learning in a co…
Prediction, Consistency, Curvature: Representation Learning for Locally-Linear Control
Nir Levine, Yinlam Chow, Rui Shu +3
Many real-world sequential decision-making problems can be formulated as optimal control with high-dimensional observations and unknown dynamics. A promising approach is to embed t…
PhysGAN: Generating Physical-World-Resilient Adversarial Examples for Autonomous Driving
Zelun Kong, Junfeng Guo, Ang Li +1
Although Deep neural networks (DNNs) are being pervasively used in vision-based autonomous driving systems, they are found vulnerable to adversarial attacks where small-magnitude p…
Cross-View Policy Learning for Street Navigation
Ang Li, Huiyi Hu, Piotr Mirowski +1
The ability to navigate from visual observations in unfamiliar environments is a core component of intelligent agents and an ongoing challenge for Deep Reinforcement Learning (RL).…
A Generalized Framework for Population Based Training
Ang Li, Aleksandra Spyra, Sagi Perel +6
Population Based Training (PBT) is a recent approach that jointly optimizes neural network weights and hyperparameters which periodically copies weights of the best performers and…