2270 results for "earn" across all locations

W. Ma, D. Huang, N. Lee, K. Kitani
We develop predictive models of pedestrian dynamics by encoding the coupled nature of multi-pedestrian interaction using game theory, and deep learning-based visual analysis to estimate person-specific behavior parameters. Building predictive models for multi-pedestrian interactions however, is very challenging due to two reasons […] [PDF]
Conference on Computer Vision and Pattern Recognition (CVPR), 2017

Y.-C. Wang, R. Wang, G. Tur, H. Williams
Goal-oriented conversational agents are becoming ubiquitous in daily life for tasks ranging from personal assistants to customer support systems. For these systems to engage users and achieve their goals in a more natural manner, they need to not just provide informative replies and guide users through the problems but also to socialize with users. To this end, we extend the line of style transfer research on developing generative deep learning models to control for a specific style such as sentiment and personality. […] [PDF]
Conversational Intelligence Challenge at Conference on Neural Information Processing Systems (ConvAI @ NeurIPS), 2018

J. Huizinga, J. Clune
An important challenge in reinforcement learning, including evolutionary robotics, is to solve multimodal problems, where agents have to act in qualitatively different ways depending on the circumstances. Because multimodal problems are often too difficult to solve directly, it is helpful to take advantage of staging, where a difficult task is divided into simpler subtasks that can serve as stepping stones for solving the overall problem. […] [PDF]
2017