Model Agnostic Multilevel Explanations
- Karthikeyan Natesan Ramamurthy
- Bhanukiran Vinzamuri
- et al.
- 2020
- NeurIPS 2020
Publications
Mix and Match: An Optimistic Tree-Search Approach for Learning Models from Mixture Distributions
- Matthew Faw
- Rajat Sen
- et al.
- 2020
- NeurIPS 2020
Higher-Order Certification For Randomized Smoothing
- Jeet Mohapatra; Ching-Yun Ko
- Tsui-Wei Weng
- 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
Learning Global Transparent Models consistent with Local Contrastive Explanations
- Tejaswini Pedapati
- Avinash Balakrishnan
- et al.
- 2020
- NeurIPS 2020
Training Stronger Baselines for Learning to Optimize
- Tianlong Chen
- Weiyi Zhang
- et al.
- 2020
- NeurIPS 2020
Model Agnostic Learning of Multilevel Explanations
- Karthikeyan Natesan Ramamurthy
- Bhanu Vinzamuri
- et al.
- 2020
- NeurIPS 2020
Ultra-Low Precision 4-bit Training of Deep Neural Networks
- Xiao Sun
- Naigang Wang
- 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
DAGs with No Fears: A Closer Look at Continuous Optimization for Learning Bayesian Networks
- Dennis Wei
- Tian Gao
- et al.
- 2020
- NeurIPS 2020