Asymptotic Guarantees for Generative Modeling Based on the Smooth Wasserstein Distance
- Ziv Goldfeld
- Kristjan Greenewald
- et al.
- 2020
- NeurIPS 2020
Publications
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
ScaleCom: Scalable Sparsified Gradient Compression for Communication-Efficient Distributed Training
- Chia-Yu Chen
- Jiamin Ni
- et al.
- 2020
- NeurIPS 2020
Finding second-order stationary points efficiently in smooth nonconvex linearly constrained optimization problems
- Songtao Lu
- Meisam Razaviyayn
- et al.
- 2020
- NeurIPS 2020
The Discrete Gaussian for Differential Privacy
- Clément L. Canonne
- Gautam Kamath
- et al.
- 2020
- NeurIPS 2020
MCUNet: Tiny Deep Learning on IoT Devices
- Ji Lin
- Wei-Ming Chen
- et al.
- 2020
- NeurIPS 2020
Impossibility Results for Grammar-Compressed Linear Algebra
- Amir Abboud
- Arturs Backurs
- et al.
- 2020
- NeurIPS 2020
TinyTL: Reduce Memory, Not Parameters for Efficient On-Device Learning
- Han Cai
- Chuang Gan
- 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