Deep Learning

A Divergence Minimization Perspective on Imitation Learning Methods CoRL 2019 A Domain Agnostic Measure for Monitoring and Evaluating GANs NeurIPS 2019 A Dual Approach to Verify and Train Deep Networks IJCAI 2019 A Dual Attention Network with Semantic Embedding for Few-Shot Learning AAAI 2019 A Dual-Path Model With Adaptive Attention for Vehicle Re-Identification ICCV 2019 Advances in Automatic Speech Recognition for Child Speech Using Factored Time Delay Neural Network Interspeech 2019 Advancing Sequence-to-Sequence Based Speech Recognition Interspeech 2019 AD-VAT: An Asymmetric Dueling mechanism for learning Visual Active Tracking ICLR 2019 ADVENT: Adversarial Entropy Minimization for Domain Adaptation in Semantic Segmentation CVPR 2019 Adversarial Attack on Sentiment Classification ACL 2019 Adversarial Attacks Beyond the Image Space CVPR 2019 Adversarial Attacks on Graph Neural Networks via Meta Learning ICLR 2019 Adversarial Attacks on Neural Networks for Graph Data IJCAI 2019 Adversarial Attacks on Node Embeddings via Graph Poisoning ICML 2019 Adversarial Audio Synthesis ICLR 2019 Adversarial Defense by Restricting the Hidden Space of Deep Neural Networks ICCV 2019 Adversarial Defense by Stratified Convolutional Sparse Coding CVPR 2019 Adversarial Discrete Sequence Generation without Explicit NeuralNetworks as Discriminators AISTATS 2019 Adversarial Domain Adaptation for Machine Reading Comprehension EMNLP 2019 Adversarial Domain Adaptation Using Artificial Titles for Abstractive Title Generation ACL 2019 Adversarial Dropout for Recurrent Neural Networks AAAI 2019 Adversarial Examples Are a Natural Consequence of Test Error in Noise ICML 2019 Adversarial Examples Are Not Bugs, They Are Features NeurIPS 2019 Adversarial Examples for Graph Data: Deep Insights into Attack and Defense IJCAI 2019 Adversarial Feedback Loop ICCV 2019