# Max-Affine Regression: Provable, Tractable, and Near-Optimal Statistical Estimation

@article{Ghosh2019MaxAffineRP, title={Max-Affine Regression: Provable, Tractable, and Near-Optimal Statistical Estimation}, author={Avishek Ghosh and Ashwin Pananjady and Adityanand Guntuboyina and Kannan Ramchandran}, journal={ArXiv}, year={2019}, volume={abs/1906.09255} }

Max-affine regression refers to a model where the unknown regression function is modeled as a maximum of $k$ unknown affine functions for a fixed $k \geq 1$. This generalizes linear regression and (real) phase retrieval, and is closely related to convex regression. Working within a non-asymptotic framework, we study this problem in the high-dimensional setting assuming that $k$ is a fixed constant, and focus on estimation of the unknown coefficients of the affine functions underlying the model… CONTINUE READING

Create an AI-powered research feed to stay up to date with new papers like this posted to ArXiv

#### Citations

##### Publications citing this paper.

#### References

##### Publications referenced by this paper.

SHOWING 1-10 OF 88 REFERENCES

## Fitting Convex Sets to Data: Algorithms and Applications

VIEW 1 EXCERPT