Papers
Differentially Private Online Submodular Minimization
Adrian Rivera Cardoso, Rachel Cummings
Differentially Private Optimal Transport: Application to Domain Adaptation
Nam LeTien, Amaury Habrard, Marc Sebban
Differential Networks for Visual Question Answering
Chenfei Wu, Jinlai Liu, Xiaojie Wang et al.
Differential Privacy Has Disparate Impact on Model Accuracy
Eugene Bagdasaryan, Omid Poursaeed, Vitaly Shmatikov
Differentiated Distribution Recovery for Neural Text Generation
Jianing Li, Yanyan Lan, Jiafeng Guo et al.
Difficulty-Aware Attention Network with Confidence Learning for Medical Image Segmentation
Dong Nie, Li Wang, Lei Xiang et al.
Difficulty Controllable Generation of Reading Comprehension Questions
Yifan Gao, Lidong Bing, Wang Chen et al.
Diffusion and Auction on Graphs
Bin Li, Dong Hao, Dengji Zhao et al.
Diffusion Improves Graph Learning
Johannes Gasteiger, Stefan Weißenberger, Stephan Günnemann
Diffusion Scattering Transforms on Graphs
Fernando Gama, Alejandro Ribeiro, Joan Bruna
Digging Into Self-Supervised Monocular Depth Estimation
Clement Godard, Oisin Mac Aodha, Michael Firman et al.
Digitally Stained Confocal Microscopy through Deep Learning
Marc Combalia, Javiera Pérez-Anker, Adriana García-Herrera et al.
Dilated Convolutional Neural Networks for Sequential Manifold-Valued Data
Xingjian Zhen, Rudrasis Chakraborty, Nicholas Vogt et al.
Dilated Convolution with Dilated GRU for Music Source Separation
Jen-Yu Liu, Yi-Hsuan Yang
Dilated LSTM with attention for Classification of Suicide Notes
Annika M Schoene, George Lacey, Alexander P Turner et al.
Dimensionality Reduction and (Bucket) Ranking: a Mass Transportation Approach
Mastane Achab, Anna Korba, Stephan Clémençon
Dimensionality Reduction for Representing the Knowledge of Probabilistic Models
Marc T Law, Jake Snell, Amir-massoud Farahmand et al.
Dimensionality Reduction for Tukey Regression
Kenneth Clarkson, Ruosong Wang, David Woodruff
Dimensionality reduction: theoretical perspective on practical measures
Yair Bartal, Nova Fandina, Ofer Neiman
Dimension-Free Bounds for Low-Precision Training
Zheng Li, Christopher M De Sa
Dimensions of Prosodic Prominence in an Attractor Model
Simon Roessig, Doris Mücke, Lena Pagel
Dimension-Wise Importance Sampling Weight Clipping for Sample-Efficient Reinforcement Learning
Seungyul Han, Youngchul Sung
DINGO: Distributed Newton-Type Method for Gradient-Norm Optimization
Rixon Crane, Fred Roosta
Direct Acceleration of SAGA using Sampled Negative Momentum
Kaiwen Zhou, Qinghua Ding, Fanhua Shang et al.