Artículos con órdenes de acceso público - Hemank LambaMás información
Disponibles en algún lugar: 10
xStream: Outlier Dete‘x’ion in Feature-Evolving Data Streams
E Manzoor, H Lamba, L Akoglu
Proceedings of the 24th ACM SIGKDD International Conference on Knowledge …, 2018
Órdenes: US National Science Foundation
Empirical observation of negligible fairness–accuracy trade-offs in machine learning for public policy
KT Rodolfa, H Lamba, R Ghani
Nature Machine Intelligence 3 (10), 896-904, 2021
Órdenes: US National Science Foundation
The Many Faces of Link Fraud
N Shah, H Lamba, A Beutel, C Faloutsos
2017 IEEE International Conference on Data Mining (ICDM), 1069-1074, 2017
Órdenes: US National Science Foundation, US Department of Defense
Need for Tweet: How Open Source Developers Talk About Their GitHub Work on Twitter.
H Fang, D Klug, H Lamba, J Herbsleb, B Vasilescu
Mining Software Repositories, 2020
Órdenes: US National Science Foundation
Learning On-the-Job to Re-rank Anomalies from Top-1 Feedback
H Lamba, L Akoglu
Proceedings of the 2019 SIAM International Conference on Data Mining, 612-620, 2019
Órdenes: US National Science Foundation
A Shapley value-based approach to determine gatekeepers in social networks with applications
R Narayanam, O Skibski, H Lamba, T Michalak
ECAI 2014, 651-656, 2014
Órdenes: European Commission
Heard it through the Gitvine: an empirical study of tool diffusion across the npm ecosystem
H Lamba, A Trockman, D Armanios, C Kästner, H Miller, B Vasilescu
Proceedings of the 28th ACM Joint Meeting on European Software Engineering …, 2020
Órdenes: US National Science Foundation
“This Is Damn Slick!” Estimating the Impact of Tweets on Open Source Project Popularity and New Contributors
H Fang, H Lamba, J Herbsleb, B Vasilescu
Órdenes: US National Science Foundation
zooRank: Ranking Suspicious Entities in Time-Evolving Tensors
H Lamba, B Hooi, K Shin, C Faloutsos, J Pfeffer
Joint European Conference on Machine Learning and Knowledge Discovery in …, 2017
Órdenes: US National Science Foundation, US Department of Defense
Model-based cluster analysis for identifying suspicious activity sequences in software
H Lamba, TJ Glazier, J Cámara, B Schmerl, D Garlan, J Pfeffer
Proceedings of the 3rd ACM on International Workshop on Security And Privacy …, 2017
Órdenes: US Department of Defense
La información de publicación y financiación se determina de forma automática mediante un programa informático