Papers
Disentangled Graph Convolutional Networks
Jianxin Ma, Peng Cui, Kun Kuang et al.
Disentangling Disentanglement in Variational Autoencoders
Emile Mathieu, Tom Rainforth, N Siddharth et al.
Distributed, Egocentric Representations of Graphs for Detecting Critical Structures
Ruo-Chun Tzeng, Shan-Hung Wu
Distributed Learning over Unreliable Networks
Chen Yu, Hanlin Tang, Cedric Renggli et al.
Distributed Learning with Sublinear Communication
Jayadev Acharya, Chris De Sa, Dylan Foster et al.
Distributed Weighted Matching via Randomized Composable Coresets
Sepehr Assadi, Mohammadhossein Bateni, Vahab Mirrokni
Distributional Multivariate Policy Evaluation and Exploration with the Bellman GAN
Dror Freirich, Tzahi Shimkin, Ron Meir et al.
Distributional Reinforcement Learning for Efficient Exploration
Borislav Mavrin, Hengshuai Yao, Linglong Kong et al.
Distribution calibration for regression
Hao Song, Tom Diethe, Meelis Kull et al.
DL2: Training and Querying Neural Networks with Logic
Marc Fischer, Mislav Balunovic, Dana Drachsler-Cohen et al.
Does Data Augmentation Lead to Positive Margin?
Shashank Rajput, Zhili Feng, Zachary Charles et al.
Do ImageNet Classifiers Generalize to ImageNet?
Benjamin Recht, Rebecca Roelofs, Ludwig Schmidt et al.
Domain Adaptation with Asymmetrically-Relaxed Distribution Alignment
Yifan Wu, Ezra Winston, Divyansh Kaushik et al.
Domain Agnostic Learning with Disentangled Representations
Xingchao Peng, Zijun Huang, Ximeng Sun et al.
DoubleSqueeze: Parallel Stochastic Gradient Descent with Double-pass Error-Compensated Compression
Hanlin Tang, Chen Yu, Xiangru Lian et al.
Doubly-Competitive Distribution Estimation
Yi Hao, Alon Orlitsky
Doubly Robust Joint Learning for Recommendation on Data Missing Not at Random
Xiaojie Wang, Rui Zhang, Yu Sun et al.
DP-GP-LVM: A Bayesian Non-Parametric Model for Learning Multivariate Dependency Structures
Andrew Lawrence, Carl Henrik Ek, Neill Campbell
Dropout as a Structured Shrinkage Prior
Eric Nalisnick, Jose Miguel Hernandez-Lobato, Padhraic Smyth
Dual Entangled Polynomial Code: Three-Dimensional Coding for Distributed Matrix Multiplication
Pedro Soto, Jun Li, Xiaodi Fan
Dynamic Measurement Scheduling for Event Forecasting using Deep RL
Chun-Hao Chang, Mingjie Mai, Anna Goldenberg
Dynamic Weights in Multi-Objective Deep Reinforcement Learning
Axel Abels, Diederik Roijers, Tom Lenaerts et al.
EDDI: Efficient Dynamic Discovery of High-Value Information with Partial VAE
Chao Ma, Sebastian Tschiatschek, Konstantina Palla et al.
Efficient Amortised Bayesian Inference for Hierarchical and Nonlinear Dynamical Systems
Geoffrey Roeder, Paul Grant, Andrew Phillips et al.