Deep Learning

Distilling Discrimination and Generalization Knowledge for Event Detection via Delta-Representation Learning ACL 2019 Distilling Object Detectors With Fine-Grained Feature Imitation CVPR 2019 Distilling Policy Distillation AISTATS 2019 Distilling Translations with Visual Awareness ACL 2019 Distraction-Aware Shadow Detection CVPR 2019 Distributed, Egocentric Representations of Graphs for Detecting Critical Structures ICML 2019 Distributed Low-rank Matrix Factorization With Exact Consensus NeurIPS 2019 DISTRIBUTIONAL CONCAVITY REGULARIZATION FOR GANS ICLR 2019 Distributionally Adversarial Attack AAAI 2019 Distributional Multivariate Policy Evaluation and Exploration with the Bellman GAN ICML 2019 Distributional Policy Optimization: An Alternative Approach for Continuous Control NeurIPS 2019 Distributional reinforcement learning with linear function approximation AISTATS 2019 Distributional Reward Decomposition for Reinforcement Learning NeurIPS 2019 Distributional Semantics Meets Multi-Label Learning AAAI 2019 Distribution Consistency Based Covariance Metric Networks for Few-Shot Learning AAAI 2019 Distribution-Interpolation Trade off in Generative Models ICLR 2019 Divergence-Augmented Policy Optimization NeurIPS 2019 Divergence Triangle for Joint Training of Generator Model, Energy-Based Model, and Inferential Model CVPR 2019 Diverse Exploration via Conjugate Policies for Policy Gradient Methods AAAI 2019 Diverse Generation for Multi-Agent Sports Games CVPR 2019 Diversify and Match: A Domain Adaptive Representation Learning Paradigm for Object Detection CVPR 2019 Diversifying Reply Suggestions Using a Matching-Conditional Variational Autoencoder NAACL 2019 Diversity and Depth in Per-Example Routing Models ICLR 2019 Diversity-Driven Extensible Hierarchical Reinforcement Learning AAAI 2019 Diversity-Sensitive Conditional Generative Adversarial Networks ICLR 2019