Asymptotic Guarantees for Generative Modeling Based on the Smooth Wasserstein Distance
- Ziv Goldfeld
- Kristjan Greenewald
- et al.
- 2020
- NeurIPS 2020
Publications
Date
Featured collections
Popular topics
81 results at NeurIPS 2020
Finding second-order stationary points efficiently in smooth nonconvex linearly constrained optimization problems
- Songtao Lu
- Meisam Razaviyayn
- et al.
- 2020
- NeurIPS 2020
Log-Likelihood Ratio Minimizing Flows: Towards Robust and Quantifiable Neural Distribution Alignment
- Ben Usman
- Avneesh Sud
- et al.
- 2020
- NeurIPS 2020
Quantifying the Empirical Wasserstein Distance to a Set of Measures: Beating the Curse of Dimensionality
- Nian Si
- Jose Blanchet
- et al.
- 2020
- NeurIPS 2020
Auxiliary Task Reweighting for Minimum-data Learning
- Baifeng Shi
- Judy Hoffman
- et al.
- 2020
- NeurIPS 2020
Private Identity Testing for High-Dimensional Distributions
- Clément L. Canonne
- Gautam Kamath
- et al.
- 2020
- NeurIPS 2020
Finite-Sample Analysis of Contractive Stochastic Approximation Using Smooth Convex Envelopes
- Zaiwei Chen
- Siva Theja Maguluri
- et al.
- 2020
- NeurIPS 2020
AI Assisted Data Labeling
- Michael Desmond
- Evelyn Duesterwald
- et al.
- 2020
- NeurIPS 2020
IBM Federated Learning Community Edition: An Interactive Demonstration
- Laura Wynter
- 2020
- NeurIPS 2020
Shared Interest: Human Annotations vs. AI Saliency
- Angie Boggust
- Benjamin Hoover
- et al.
- 2020
- NeurIPS 2020