Publications

Auxiliary Task Reweighting for Minimum-data Learning
- - Baifeng Shi
  - Judy Hoffman
  - et al.
- 2020
- NeurIPS 2020
SnapBoost: A Heterogeneous Boosting Machine
- - Thomas Parnell
  - Andreea Anghel
  - 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
A Scalable MIP-based Method for Learning Optimal Multivariate Decision Trees
- - Haoran Zhu
  - Pavankumar Murali
  - 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
Mix and Match: An Optimistic Tree-Search Approach for Learning Models from Mixture Distributions
- - Matthew Faw
  - Rajat Sen
  - 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
Uncertainty-Aware Learning for Zero-Shot Semantic Segmentation
- - Ping Hu
  - Stan Sclaroff
  - et al.
- 2020
- NeurIPS 2020
Approximate Cross-Validation for Structured Models
- - Soumya Ghosh
  - William T. Stephenson
  - et al.
- 2020
- NeurIPS 2020