A Data Prism: Semi-verified learning in the small-alpha regime

By Michela Meister, Gregory Valiant. 2018

18 citations recorded by the source corpus.

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

1. Ilias Diakonikolas
2. Daniel M. Kane
3. Jacob Steinhardt
4. Gautam Kamath
5. Gregory Valiant
6. Alistair Stewart
7. Jayadev Acharya
8. Jerry Zheng Li

Citations in the corpus

• Sever: A Robust Meta-Algorithm for Stochastic Optimization (2018, background): “…tradeoffs [DKS17c, DKK + 18], establishing connections to PAC learning [DKS17a], tolerating more noise by outputting a list of hypotheses [CSV17, MV17, DKS17b], robust estimation of discrete structures [Ste17, QV17, SCV18], and robust estimation via sum-of-squares [KS17b, HL17, KS17a].”
• Resilience: A Criterion for Learning in the Presence of Arbitrary Outliers (2017, background): “(2017) study sparse mean estimation, and others have studied problems including regression, Bayes nets, planted clique, and several other settings (Diakonikolas et al., 2016b,c, 2017b,c; Kane et al., 2017; Meister and Valiant, 2017).”