Shubhomoy Das
Shubhomoy Das
Unknown affiliation
Verified email at espressive.com - Homepage
Title
Cited by
Cited by
Year
Detecting insider threats in a real corporate database of computer usage activity
TE Senator, HG Goldberg, A Memory, WT Young, B Rees, R Pierce, ...
Proceedings of the 19th ACM SIGKDD international conference on Knowledge …, 2013
1342013
Systematic construction of anomaly detection benchmarks from real data
AF Emmott, S Das, T Dietterich, A Fern, WK Wong
Proceedings of the ACM SIGKDD workshop on outlier detection and description …, 2013
1262013
Incorporating expert feedback into active anomaly discovery
S Das, WK Wong, T Dietterich, A Fern, A Emmott
2016 IEEE 16th International Conference on Data Mining (ICDM), 853-858, 2016
1052016
A meta-analysis of the anomaly detection problem
A Emmott, S Das, T Dietterich, A Fern, WK Wong
arXiv preprint arXiv:1503.01158, 2015
512015
You are the only possible oracle: Effective test selection for end users of interactive machine learning systems
A Groce, T Kulesza, C Zhang, S Shamasunder, M Burnett, WK Wong, ...
IEEE Transactions on Software Engineering 40 (3), 307-323, 2013
412013
Incorporating feedback into tree-based anomaly detection
S Das, WK Wong, A Fern, TG Dietterich, MA Siddiqui
arXiv preprint arXiv:1708.09441, 2017
272017
End-user feature labeling: Supervised and semi-supervised approaches based on locally-weighted logistic regression
S Das, T Moore, WK Wong, S Stumpf, I Oberst, K McIntosh, M Burnett
Artificial Intelligence 204, 56-74, 2013
212013
End-user feature labeling: A locally-weighted regression approach
WK Wong, I Oberst, S Das, T Moore, S Stumpf, K McIntosh, M Burnett
Proceedings of the 16th international conference on Intelligent user …, 2011
162011
Where are my intelligent assistant’s mistakes? A systematic testing approach
T Kulesza, M Burnett, S Stumpf, WK Wong, S Das, A Groce, A Shinsel, ...
International Symposium on End User Development, 171-186, 2011
142011
Finite Sample Complexity of Rare Pattern Anomaly Detection.
MA Siddiqui, A Fern, TG Dietterich, S Das
UAI, 2016
92016
Active anomaly detection via ensembles
S Das, MR Islam, NK Jayakodi, JR Doppa
arXiv preprint arXiv:1809.06477, 2018
72018
Active anomaly detection for time-domain discoveries
EEO Ishida, MV Kornilov, KL Malanchev, MV Pruzhinskaya, AA Volnova, ...
Astronomy & Astrophysics (A&A) 650 (ISSN: 0004-6361 ; e-ISSN: 1432-0746), 2021
62021
Discovering anomalies by incorporating feedback from an expert
S Das, WK Wong, T Dietterich, A Fern, A Emmott
ACM Transactions on Knowledge Discovery from Data (TKDD) 14 (4), 1-32, 2020
62020
Active anomaly detection via ensembles: Insights, algorithms, and interpretability
S Das, MR Islam, NK Jayakodi, JR Doppa
arXiv preprint arXiv:1901.08930, 2019
52019
Anomaly detection meta-analysis benchmarks
A Emmott, S Das, T Dietterich, A Fern, WK Wong
42016
GLAD: GLocalized Anomaly Detection via Human-in-the-Loop Learning
M Rakibul Islam, S Das, J Rao Doppa, S Natarajan
arXiv e-prints, arXiv: 1810.01403, 2018
1*2018
End-user feature labeling via locally weighted logistic regression
WK Wong, I Oberst, S Das, T Moore, S Stumpf, K McIntosh, M Burnett
Twenty-Fifth AAAI Conference on Artificial Intelligence, 2011
12011
GLAD: GLocalized Anomaly Detection via Human-in-the-Loop Learning
MR Islam, S Das, JR Doppa, S Natarajan
arXiv preprint arXiv:1810.01403, 2018
2018
Incorporating User Feedback into Machine Learning Systems
S Das
2017
End-User Feature Labeling: Supervised and Semi-supervised Approaches Based on Locally-Weighted Logistic Regression
K McIntosh, S Das, S Stumpf, T Moore, M Burnetta, WK Wong, I Oberst
2013
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