Papers
Distribution-Interpolation Trade off in Generative Models
Damian Leśniak, Igor Sieradzki, Igor Podolak
Distribution Learning of a Random Spatial Field with a Location-Unaware Mobile Sensor
Meera Pai, Animesh Kumar
Distribution oblivious, risk-aware algorithms for multi-armed bandits with unbounded rewards
Anmol Kagrecha, Jayakrishnan Nair, Krishna Jagannathan
Dive into Deep Learning for Natural Language Processing
Haibin Lin, Xingjian Shi, Leonard Lausen et al.
2019
IJCNLP
Dive into Deep Learning for Natural Language Processing
Haibin Lin, Xingjian Shi, Leonard Lausen et al.
2019
EMNLP
Divergence-Augmented Policy Optimization
Qing Wang, Yingru Li, Jiechao Xiong et al.
Divergence Prior and Vessel-Tree Reconstruction
Zhongwen Zhang, Dmitrii Marin, Egor Chesakov et al.
Divergence Triangle for Joint Training of Generator Model, Energy-Based Model, and Inferential Model
Tian Han, Erik Nijkamp, Xiaolin Fang et al.
Diverse Exploration via Conjugate Policies for Policy Gradient Methods
Andrew Cohen, Xingye Qiao, Lei Yu et al.
Diverse Generation for Multi-Agent Sports Games
Raymond A. Yeh, Alexander G. Schwing, Jonathan Huang et al.
Diverse Image Synthesis From Semantic Layouts via Conditional IMLE
Ke Li, Tianhao Zhang, Jitendra Malik
Diversify and Match: A Domain Adaptive Representation Learning Paradigm for Object Detection
Taekyung Kim, Minki Jeong, Seunghyeon Kim et al.
Diversifying Reply Suggestions Using a Matching-Conditional Variational Autoencoder
Budhaditya Deb, Peter Bailey, Milad Shokouhi
Diversify Your Datasets: Analyzing Generalization via Controlled Variance in Adversarial Datasets
Ohad Rozen, Vered Shwartz, Roee Aharoni et al.
Diversity and Depth in Per-Example Routing Models
Prajit Ramachandran, Quoc V. Le
Diversity-aware Event Prediction based on a Conditional Variational Autoencoder with Reconstruction
Hirokazu Kiyomaru, Kazumasa Omura, Yugo Murawaki et al.
Diversity-Driven Extensible Hierarchical Reinforcement Learning
Yuhang Song, Jianyi Wang, Thomas Lukasiewicz et al.
Diversity-Inducing Policy Gradient: Using Maximum Mean Discrepancy to Find a Set of Diverse Policies
Muhammad Masood, Finale Doshi-Velez
Diversity is All You Need: Learning Skills without a Reward Function
Benjamin Eysenbach, Abhishek Gupta, Julian Ibarz et al.
Diversity-Sensitive Conditional Generative Adversarial Networks
Dingdong Yang, Seunghoon Hong, Yunseok Jang et al.
Diversity With Cooperation: Ensemble Methods for Few-Shot Classification
Nikita Dvornik, Cordelia Schmid, Julien Mairal
Divide and Conquer the Embedding Space for Metric Learning
Artsiom Sanakoyeu, Vadim Tschernezki, Uta Buchler et al.
Divide and Couple: Using Monte Carlo Variational Objectives for Posterior Approximation
Justin Domke, Daniel R. Sheldon
Divide, Conquer and Combine: Hierarchical Feature Fusion Network with Local and Global Perspectives for Multimodal Affective Computing
Sijie Mai, Haifeng Hu, Songlong Xing
DIVINE: A Generative Adversarial Imitation Learning Framework for Knowledge Graph Reasoning
Ruiping Li, Xiang Cheng