Publications

81 results at NeurIPS 2020

Asymptotic Guarantees for Generative Modeling Based on the Smooth Wasserstein Distance
- - Ziv Goldfeld
  - Kristjan Greenewald
  - et al.
- 2020
- NeurIPS 2020
TinyTL: Reduce Memory, Not Parameters for Efficient On-Device Learning
- - Han Cai
  - Chuang Gan
  - et al.
- 2020
- NeurIPS 2020
Optimizing Mode Connectivity via Neuron Alignment
- - N. Joseph Tatro
  - Pin-Yu Chen
  - 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
Entropic Causal Inference: Identifiability and Finite Sample Results Spencer Compton
- - Spencer Compton
  - Murat Kocaoglu
  - et al.
- 2020
- NeurIPS 2020
Private Identity Testing for High-Dimensional Distributions
- - Clément L. Canonne
  - Gautam Kamath
  - et al.
- 2020
- NeurIPS 2020
Training Stronger Baselines for Learning to Optimize
- - Tianlong Chen
  - Weiyi Zhang
  - et al.
- 2020
- NeurIPS 2020
Mix and Match: An Optimistic Tree-Search Approach for Learning Models from Mixture Distributions
- - Matthew Faw
  - Rajat Sen
  - et al.
- 2020
- NeurIPS 2020
DAGs with No Fears: A Closer Look at Continuous Optimization for Learning Bayesian Networks
- - Dennis Wei
  - Tian Gao
  - et al.
- 2020
- NeurIPS 2020
Applications of Common Entropy for Causal Inference
- - Murat Kocaoglu
  - Sanjay Shakkottai
  - et al.
- 2020
- NeurIPS 2020