TY - GEN
T1 - Robust structured estimation with single-index models
AU - Chen, Sheng
AU - Banerjee, Arindam
N1 - Publisher Copyright:
© 2017 by the author(s).
PY - 2017
Y1 - 2017
N2 - In this paper, we investigate general single-index models (SIMs) in high dimensions. Based on U -statistics, we propose two types of robust estimators for the recovery of model parameters, which can be viewed as generalizations of several existing algorithms for one-bit compressed sensing (1-bit CS). With minimal assumption on noise, the statistical guarantees are established for the generalized estimators under suitable conditions, which allow general structures of underlying parameter. Moreover, the proposed estimator is novelly instantiated for SIMs with monotone transfer function, and the obtained estimator can better leverage the monotonicity. Experimental results are provided to support our theoretical analyses.
AB - In this paper, we investigate general single-index models (SIMs) in high dimensions. Based on U -statistics, we propose two types of robust estimators for the recovery of model parameters, which can be viewed as generalizations of several existing algorithms for one-bit compressed sensing (1-bit CS). With minimal assumption on noise, the statistical guarantees are established for the generalized estimators under suitable conditions, which allow general structures of underlying parameter. Moreover, the proposed estimator is novelly instantiated for SIMs with monotone transfer function, and the obtained estimator can better leverage the monotonicity. Experimental results are provided to support our theoretical analyses.
UR - http://www.scopus.com/inward/record.url?scp=85048418436&partnerID=8YFLogxK
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M3 - Conference contribution
AN - SCOPUS:85048418436
T3 - 34th International Conference on Machine Learning, ICML 2017
SP - 1186
EP - 1201
BT - 34th International Conference on Machine Learning, ICML 2017
PB - International Machine Learning Society (IMLS)
T2 - 34th International Conference on Machine Learning, ICML 2017
Y2 - 6 August 2017 through 11 August 2017
ER -