Papers
Differentially Private Learning of Geometric Concepts
Haim Kaplan, Yishay Mansour, Yossi Matias et al.
Dimensionality Reduction for Tukey Regression
Kenneth Clarkson, Ruosong Wang, David Woodruff
Dimension-Wise Importance Sampling Weight Clipping for Sample-Efficient Reinforcement Learning
Seungyul Han, Youngchul Sung
Direct Uncertainty Prediction for Medical Second Opinions
Maithra Raghu, Katy Blumer, Rory Sayres et al.
Dirichlet Simplex Nest and Geometric Inference
Mikhail Yurochkin, Aritra Guha, Yuekai Sun et al.
Discovering Conditionally Salient Features with Statistical Guarantees
Jaime Roquero Gimenez, James Zou
Discovering Context Effects from Raw Choice Data
Arjun Seshadri, Alex Peysakhovich, Johan Ugander
Discovering Latent Covariance Structures for Multiple Time Series
Anh Tong, Jaesik Choi
Discovering Options for Exploration by Minimizing Cover Time
Yuu Jinnai, Jee Won Park, David Abel et al.
Discriminative Regularization for Latent Variable Models with Applications to Electrocardiography
Andrew Miller, Ziad Obermeyer, John Cunningham et al.
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.