Papers
Differentially Private Bayesian Inference for Exponential Families
Garrett Bernstein, Daniel R. Sheldon
Differentially Private Change-Point Detection
Rachel Cummings, Sara Krehbiel, Yajun Mei et al.
Differentially Private Contextual Linear Bandits
Roshan Shariff, Or Sheffet
Differentially Private k-Means with Constant Multiplicative Error
Uri Stemmer, Haim Kaplan
Differentially Private Robust Low-Rank Approximation
Raman Arora, Vladimir braverman, Jalaj Upadhyay
Differentially Private Testing of Identity and Closeness of Discrete Distributions
Jayadev Acharya, Ziteng Sun, Huanyu Zhang
Differentially Private Uniformly Most Powerful Tests for Binomial Data
Jordan Awan, Aleksandra Slavković
Differential Privacy for Growing Databases
Rachel Cummings, Sara Krehbiel, Kevin A Lai et al.
Differential Properties of Sinkhorn Approximation for Learning with Wasserstein Distance
Giulia Luise, Alessandro Rudi, Massimiliano Pontil et al.
Diffusion Maps for Textual Network Embedding
Xinyuan Zhang, Yitong Li, Dinghan Shen et al.
DifNet: Semantic Segmentation by Diffusion Networks
Peng Jiang, Fanglin Gu, Yunhai Wang et al.
Dimensionality Reduction for Stationary Time Series via Stochastic Nonconvex Optimization
Minshuo Chen, Lin Yang, Mengdi Wang et al.
Dimensionality Reduction has Quantifiable Imperfections: Two Geometric Bounds
Kry Lui, Gavin Weiguang Ding, Ruitong Huang et al.
Dimensionally Tight Bounds for Second-Order Hamiltonian Monte Carlo
Oren Mangoubi, Nisheeth Vishnoi
Diminishing Returns Shape Constraints for Interpretability and Regularization
Maya Gupta, Dara Bahri, Andrew Cotter et al.
Direct Estimation of Differences in Causal Graphs
Yuhao Wang, Chandler Squires, Anastasiya Belyaeva et al.
Direct Runge-Kutta Discretization Achieves Acceleration
Jingzhao Zhang, Aryan Mokhtari, Suvrit Sra et al.
Dirichlet-based Gaussian Processes for Large-scale Calibrated Classification
Dimitrios Milios, Raffaello Camoriano, Pietro Michiardi et al.
Dirichlet belief networks for topic structure learning
He Zhao, Lan Du, Wray Buntine et al.
Disconnected Manifold Learning for Generative Adversarial Networks
Mahyar Khayatkhoei, Maneesh K. Singh, Ahmed Elgammal
Discovery of Latent 3D Keypoints via End-to-end Geometric Reasoning
Supasorn Suwajanakorn, Noah Snavely, Jonathan J Tompson et al.
Discretely Relaxing Continuous Variables for tractable Variational Inference
Trefor Evans, Prasanth Nair
Discrimination-aware Channel Pruning for Deep Neural Networks
Zhuangwei Zhuang, Mingkui Tan, Bohan Zhuang et al.
Distilled Wasserstein Learning for Word Embedding and Topic Modeling
Hongteng Xu, Wenlin Wang, Wei Liu et al.
Distributed $k$-Clustering for Data with Heavy Noise
Shi Li, Xiangyu Guo