Revisiting the Sample Complexity of Sparse Spectrum Approximation of Gaussian Processes
- Minh Hoang
- Trong Nghia Hoang
- et al.
- 2020
- NeurIPS 2020
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Heavy-tailed Representations, Text Polarity Classification & Data Augmentation
- Hamid Jalalzai
- Pierre Colombo
- et al.
- 2020
- NeurIPS 2020
Entropic Causal Inference: Identifiability and Finite Sample Results Spencer Compton
- Spencer Compton
- Murat Kocaoglu
- et al.
- 2020
- NeurIPS 2020
Log-Likelihood Ratio Minimizing Flows: Towards Robust and Quantifiable Neural Distribution Alignment
- Ben Usman
- Avneesh Sud
- et al.
- 2020
- NeurIPS 2020
Model Agnostic Learning of Multilevel Explanations
- Karthikeyan Natesan Ramamurthy
- Bhanu Vinzamuri
- 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
Private Identity Testing for High-Dimensional Distributions
- Clément L. Canonne
- Gautam Kamath
- 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
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