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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81 results at 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
Log-Likelihood Ratio Minimizing Flows: Towards Robust and Quantifiable Neural Distribution Alignment
- Ben Usman
- Avneesh Sud
- et al.
- 2020
- NeurIPS 2020
Impossibility Results for Grammar-Compressed Linear Algebra
- Amir Abboud
- Arturs Backurs
- 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
Ultra-Low Precision 4-bit Training of Deep Neural Networks
- Xiao Sun
- Naigang Wang
- et al.
- 2020
- NeurIPS 2020
TinyTL: Reduce Memory, Not Parameters for Efficient On-Device Learning
- Han Cai
- Chuang Gan
- 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
Finding second-order stationary points efficiently in smooth nonconvex linearly constrained optimization problems
- Songtao Lu
- Meisam Razaviyayn
- et al.
- 2020
- NeurIPS 2020
Universal Domain Adaptation through Self Supervision
- Kuniaki Saito
- Donghyun Kim
- et al.
- 2020
- NeurIPS 2020