Papers
Deep Joint Source-Channel Coding with Iterative Source Error Correction
Changwoo Lee, Xiao Hu, Hun-Seok Kim
Deep Neural Networks with Efficient Guaranteed Invariances
Matthias Rath, Alexandru Paul Condurache
Deep Value Function Networks for Large-Scale Multistage Stochastic Programs
Hyunglip Bae, Jinkyu Lee, Woo Chang Kim et al.
Delayed Feedback in Generalised Linear Bandits Revisited
Benjamin Howson, Ciara Pike-Burke, Sarah Filippi
Density Ratio Estimation and Neyman Pearson Classification with Missing Data
Josh Givens, Song Liu, Henry W. J. Reeve
DIET: Conditional independence testing with marginal dependence measures of residual information
Mukund Sudarshan, Aahlad Puli, Wesley Tansey et al.
Differentiable Change-point Detection With Temporal Point Processes
Paramita Koley, Harshavardhan Alimi, Shrey Singla et al.
Differentially Private Matrix Completion through Low-rank Matrix Factorization
Lingxiao Wang, Boxin Zhao, Mladen Kolar
Differentially Private Synthetic Control
Saeyoung Rho, Rachel Cummings, Vishal Misra
Diffusion Generative Models in Infinite Dimensions
Gavin Kerrigan, Justin Ley, Padhraic Smyth
Dimensionality Collapse: Optimal Measurement Selection for Low-Error Infinite-Horizon Forecasting
Helmuth Naumer, Farzad Kamalabadi
Direct Inference of Effect of Treatment (DIET) for a Cookieless World
Shiv Shankar, Ritwik Sinha, Saayan Mitra et al.
Discovering Many Diverse Solutions with Bayesian Optimization
Natalie Maus, Kaiwen Wu, David Eriksson et al.
Discrete Distribution Estimation under User-level Local Differential Privacy
Jayadev Acharya, Yuhan Liu, Ziteng Sun
Discrete Langevin Samplers via Wasserstein Gradient Flow
Haoran Sun, Hanjun Dai, Bo Dai et al.
Distance-to-Set Priors and Constrained Bayesian Inference
Rick Presman, Jason Xu
Distill n’ Explain: explaining graph neural networks using simple surrogates
Tamara Pereira, Erik Nascimento, Lucas E. Resck et al.
Distributed Offline Policy Optimization Over Batch Data
Han Shen, Songtao Lu, Xiaodong Cui et al.
Distributionally Robust Policy Gradient for Offline Contextual Bandits
Zhouhao Yang, Yihong Guo, Pan Xu et al.
Do Bayesian Neural Networks Need To Be Fully Stochastic?
Mrinank Sharma, Sebastian Farquhar, Eric Nalisnick et al.
Does Label Differential Privacy Prevent Label Inference Attacks?
Ruihan Wu, Jin Peng Zhou, Kilian Q. Weinberger et al.
Domain Adaptation under Missingness Shift
Helen Zhou, Sivaraman Balakrishnan, Zachary Lipton
Don’t be fooled: label leakage in explanation methods and the importance of their quantitative evaluation
Neil Jethani, Adriel Saporta, Rajesh Ranganath
Doubly Fair Dynamic Pricing
Jianyu Xu, Dan Qiao, Yu-Xiang Wang
Dropout-Resilient Secure Multi-Party Collaborative Learning with Linear Communication Complexity
Xingyu Lu, Hasin Us Sami, Başak Güler