Deep Learning
Uncertainty-Aware Attention for Reliable Interpretation and Prediction
Jay Heo, Hae Beom Lee, Saehoon Kim, Juho Lee, Kwang Joon Kim, Eunho Yang, Sung Ju Hwang
Further evaluation of both the accuracy of the uncertainty calibration and the prediction performance with "I don't know"
Meta-Gradient Reinforcement Learning
Zhongwen Xu, Hado P. van Hasselt, David Silver
Neural Information Processing Systems http://nips.cc/
Ohad Shamir Department of Computer Science and Applied Mathematics Weizmann Institute of Science Rehovot, Israel nullnullnullnullnullnullnullnullnullnullnullnullnullnullnull
A residual network (or ResNet) is a standard deep neural net architecture, with state-of-the-art performance across numerous applications.
Generating Informative and Diverse Conversational Responses via Adversarial Information Maximization
Yizhe Zhang, Michel Galley, Jianfeng Gao, Zhe Gan, Xiujun Li, Chris Brockett, Bill Dolan
Information Maximization (AIM) model, to address these two related but distinct problems.
Poison Frogs! Targeted Clean-Label Poisoning Attacks on Neural Networks
Ali Shafahi, W. Ronny Huang, Mahyar Najibi, Octavian Suciu, Christoph Studer, Tudor Dumitras, Tom Goldstein
Neural Information Processing Systems http://nips.cc/
Out-of-Distribution Detection using Multiple Semantic Label Representations
Gabi Shalev, Yossi Adi, Joseph Keshet
Neural Information Processing Systems http://nips.cc/
Diffusion Maps for Textual Network Embedding
Xinyuan Zhang, Yitong Li, Dinghan Shen, Lawrence Carin
Textual network embedding leverages rich text information associated with the network to learn low-dimensional vectorial representations of vertices.
Simple, Distributed, and Accelerated Probabilistic Programming
Dustin Tran, Matthew W. Hoffman, Dave Moore, Christopher Suter, Srinivas Vasudevan, Alexey Radul
We describe a simple, low-level approach for embedding probabilistic programming in a deep learning ecosystem.
Bayesian Semi-supervised Learning with Graph Gaussian Processes
Yin Cheng Ng, Nicolò Colombo, Ricardo Silva
Neural Information Processing Systems http://nips.cc/