Stochastic Subgradient Methods

By Stephen P. Boyd, Almir Mutapcic. 2007

101 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. L. Elisa Celis
2. Lingxiao Huang
3. Nisheeth K. Vishnoi
4. Vijay Keswani
5. Manish Raghavan
6. Anay Mehrotra
7. Dana Pessach
8. Sina Baharlouei

Citations in the corpus

• Stable and Fair Classification (2019, methodology): “Our extended algorithm A is to compute a minimizer A S of Program (Stable-Fair) by classic methods, e.g., stochastic gradient descent [11].”
• Classification with Fairness Constraints: A Meta-Algorithm with Provable Guarantees (2018, methodology): “Since is convex and hence we can apply standard convex optimization algorithms, e.g., the stochastic subgradient method [8].”