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Avradeep Bhowmik
Avradeep Bhowmik
Department of Electrical and Computer Engineering, The University of Texas at Austin
Dirección de correo verificada de utexas.edu - Página principal
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Gradient boosting neural networks: Grownet
S Badirli, X Liu, Z Xing, A Bhowmik, K Doan, SS Keerthi
arXiv preprint arXiv:2002.07971, 2020
792020
Submodularity in team formation problem
A Bhowmik, V Borkar, D Garg, M Pallan
Proceedings of the 2014 SIAM international conference on data mining, 893-901, 2014
442014
Letor methods for unsupervised rank aggregation
A Bhowmik, J Ghosh
Proceedings of the 26th international conference on world wide web, 1331-1340, 2017
222017
Generalized linear models for aggregated data
A Bhowmik, J Ghosh, O Koyejo
Artificial Intelligence and Statistics, 93-101, 2015
202015
Image Generation Via Minimizing Fr\'echet Distance in Discriminator Feature Space
KD Doan, S Manchanda, F Wang, S Keerthi, A Bhowmik, CK Reddy
arXiv preprint arXiv:2003.11774, 2020
92020
EstImAgg: A Learning Framework for Groupwise Aggregated Data
A Bhowmik, M Chen, Z Xing, S Rajan
Proceedings of the 2019 SIAM International Conference on Data Mining, 477-485, 2019
92019
Sparse parameter recovery from aggregated data
A Bhowmik, J Ghosh, O Koyejo
International Conference on Machine Learning, 1090-1099, 2016
92016
Geometry aware mappings for high dimensional sparse factors
A Bhowmik, N Liu, E Zhong, B Bhaskar, S Rajan
Artificial Intelligence and Statistics, 455-463, 2016
72016
Learning from aggregated data
A Bhowmik
The University of Texas at Austin, 2018
42018
Frequency domain predictive modelling with aggregated data
A Bhowmik, J Ghosh, O Koyejo
Artificial Intelligence and Statistics, 971-980, 2017
32017
Aggregation for Sensitive Data
A Bhowmik, J Ghosh, O Koyejo
2019 13th International conference on Sampling Theory and Applications …, 2019
2019
Monotone Retargeting for Unsupervised Rank Aggregation with Object Features
A Bhowmik, J Ghosh
arXiv preprint arXiv:1605.04465, 2016
2016
EstImAgg: A Learning Framework for Groupwise Aggregated Data: Supplement
A Bhowmik, M Chen, Z Xing, S Rajan
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Artículos 1–13