7.1k citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- SupélecFR486 papers
- Shandong University of Political Science and LawCN485 papers
- Dalle Molle Institute for Artificial Intelligence ResearchCH65 papers
- New York UniversityUS52 papers
- Università della Svizzera italianaCH21 papers
- Google (United States)US16 papers
- Princeton UniversityUS15 papers
- Courant Institute of Mathematical SciencesUS13 papers
- Politecnico di TorinoIT12 papers
- Meta (Israel)IL11 papers
- Massachusetts Institute of TechnologyUS10 papers
- ETH ZurichCH9 papers
6 papers · 2 filters
Deep Equals Shallow for ReLU Networks in Kernel Regimes
Alberto Bietti, Francis Bach
Deep networks are often considered to be more expressive than shallow ones in terms of approximation. Indeed, certain functions can be approximated by deep networks provably more e…
Time series forecasting with Gaussian Processes needs priors
Giorgio Corani, Alessio Benavoli, Marco Zaffalon
Automatic forecasting is the task of receiving a time series and returning a forecast for the next time steps without any human intervention. Gaussian Processes (GPs) are a powerfu…
Dynamic Batch Learning in High-Dimensional Sparse Linear Contextual Bandits
Zhimei Ren, Zhengyuan Zhou
We study the problem of dynamic batch learning in high-dimensional sparse linear contextual bandits, where a decision maker, under a given maximum-number-of-batch constraint and on…
Deep Direct Likelihood Knockoffs
Mukund Sudarshan, Wesley Tansey, Rajesh Ranganath
Predictive modeling often uses black box machine learning methods, such as deep neural networks, to achieve state-of-the-art performance. In scientific domains, the scientist often…
Why Normalizing Flows Fail to Detect Out-of-Distribution Data
Polina Kirichenko, Pavel Izmailov, Andrew Gordon Wilson
Detecting out-of-distribution (OOD) data is crucial for robust machine learning systems. Normalizing flows are flexible deep generative models that often surprisingly fail to disti…
Strong Consistency, Graph Laplacians, and the Stochastic Block Model
Shaofeng Deng, Shuyang Ling, Thomas Strohmer
Spectral clustering has become one of the most popular algorithms in data clustering and community detection. We study the performance of classical two-step spectral clustering via…