Publications

Ultra-Low Precision 4-bit Training of Deep Neural Networks
- - Xiao Sun
  - Naigang Wang
  - et al.
- 2020
- NeurIPS 2020
ScaleCom: Scalable Sparsified Gradient Compression for Communication-Efficient Distributed Training
- - Chia-Yu Chen
  - Jiamin Ni
  - et al.
- 2020
- NeurIPS 2020
Asymptotic Guarantees for Generative Modeling Based on the Smooth Wasserstein Distance
- - Ziv Goldfeld
  - Kristjan Greenewald
  - et al.
- 2020
- NeurIPS 2020
MCUNet: Tiny Deep Learning on IoT Devices
- - Ji Lin
  - Wei-Ming Chen
  - 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
Learning Global Transparent Models consistent with Local Contrastive Explanations
- - Tejaswini Pedapati
  - Avinash Balakrishnan
  - et al.
- 2020
- NeurIPS 2020
The Discrete Gaussian for Differential Privacy
- - Clément L. Canonne
  - Gautam Kamath
  - et al.
- 2020
- NeurIPS 2020
Impossibility Results for Grammar-Compressed Linear Algebra
- - Amir Abboud
  - Arturs Backurs
  - et al.
- 2020
- NeurIPS 2020
SnapBoost: A Heterogeneous Boosting Machine
- - Thomas Parnell
  - Andreea Anghel
  - 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