@inproceedings{50b3c8279a26491dada0b82f0a6f9d2a,
title = "Sparse coding with anomaly detection",
abstract = "We consider the problem of simultaneous sparse coding and anomaly detection in a collection of data vectors. The majority of the data vectors are assumed to conform with a sparse representation model, whereas the anomaly is caused by an unknown subset of the data vectors - the outliers - which significantly deviate from this model. The proposed approach utilizes the Alternating Direction Method of Multipliers (ADMM) to recover simultaneously the sparse representations and the outliers components for the entire collection. This approach provides a unified solution both for jointly sparse and independently sparse data vectors. We demonstrate the usefulness of the proposed approach for irregular heartbeats detection in Electrocardiogram (ECG) and specular reflectance removal from natural images.",
keywords = "ADMM, anomaly detection, arrythmia detection, sparse coding, specular reflectance removal",
author = "Amir Adler and Michael Elad and Yacov Hel-Or and Ehud Rivlin",
year = "2013",
doi = "10.1109/MLSP.2013.6661898",
language = "אנגלית",
isbn = "9781479911806",
series = "IEEE International Workshop on Machine Learning for Signal Processing, MLSP",
publisher = "IEEE Computer Society",
booktitle = "2013 IEEE International Workshop on Machine Learning for Signal Processing - Proceedings of MLSP 2013",
address = "ארצות הברית",
note = "23rd IEEE International Workshop on Machine Learning for Signal Processing, MLSP 2013 ; Conference date: 22-09-2013 Through 25-09-2013",
}