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A Polynomial-time Form of Robust Regression
Yao-Liang Yu · Özlem Aslan · Dale Schuurmans

Mon Dec 03 07:00 PM -- 12:00 AM (PST) @ Harrah’s Special Events Center 2nd Floor

Despite the variety of robust regression methods that have been developed, current regression formulations are either NP-hard, or allow unbounded response to even a single leverage point. We present a general formulation for robust regression --Variational M-estimation--that unifies a number of robust regression methods while allowing a tractable approximation strategy. We develop an estimator that requires only polynomial-time, while achieving certain robustness and consistency guarantees. An experimental evaluation demonstrates the effectiveness of the new estimation approach compared to standard methods.

Author Information

Yao-Liang Yu (University of Waterloo)
Özlem Aslan (University of Alberta)
Dale Schuurmans (Google Brain & University of Alberta)

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