Deep Learning
Self-Critical Reasoning for Robust Visual Question Answering
Neural Information Processing Systems http://nips.cc/
Model Compression with Adversarial Robustness: A Unified Optimization Framework
Shupeng Gui, Haotao N. Wang, Haichuan Yang, Chen Yu, Zhangyang Wang, Ji Liu
Previous literature suggested that the goals of robustness and compactness might sometimes contradict.
MaCow: Masked Convolutional Generative Flow
Xuezhe Ma, Xiang Kong, Shanghang Zhang, Eduard Hovy
Unsupervised learning of probabilistic models is a central yet challenging problem. Deep generative models have shown promising results in modeling complex distributions such as natural images (Radford et al., 2015), audio (V an Den Oord et al., 2016) and text (Bowman et al., 2015).
Controllable Text-to-Image Generation
Bowen Li, Xiaojuan Qi, Thomas Lukasiewicz, Philip Torr
When the given text description (e.g., colour) is changed,
Deep Imitation Learning for Bimanual Robotic Manipulation Fan Xie 1 Alexander Chowdhury 1 M. Clara De Paolis Kaluza
A core challenge is to generalize the manipulation skills to objects in different locations. We hypothesize that modeling the relational information in the environment can significantly improve generalization.
A Unified Bellman Optimality Principle Combining Reward Maximization and Empowerment
Felix Leibfried, Sergio Pascual-Dรญaz, Jordi Grau-Moya
Neural Information Processing Systems http://nips.cc/
On the Convergence Rate of Training Recurrent Neural Networks
Zeyuan Allen-Zhu, Yuanzhi Li, Zhao Song
Neural Information Processing Systems http://nips.cc/
