Publications

Log-Likelihood Ratio Minimizing Flows: Towards Robust and Quantifiable Neural Distribution Alignment
- - Ben Usman
  - Avneesh Sud
  - 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
Higher-Order Certification For Randomized Smoothing
- - Jeet Mohapatra; Ching-Yun Ko
  - Tsui-Wei Weng
  - et al.
- 2020
- NeurIPS 2020
Training Stronger Baselines for Learning to Optimize
- - Tianlong Chen
  - Weiyi Zhang
  - 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
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
ScaleCom: Scalable Sparsified Gradient Compression for Communication-Efficient Distributed Training
- - Chia-Yu Chen
  - Jiamin Ni
  - et al.
- 2020
- NeurIPS 2020
Approximate Cross-Validation for Structured Models
- - Soumya Ghosh
  - William T. Stephenson
  - et al.
- 2020
- NeurIPS 2020
Model Agnostic Multilevel Explanations
- - Karthikeyan Natesan Ramamurthy
  - Bhanukiran Vinzamuri
  - et al.
- 2020
- NeurIPS 2020