Mayank Agarwal  Mayank Agarwal photo         

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Research Software Engineer
Cambridge Research Center, Cambridge, MA USA
  

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2020

IBM Federated Learning: an Enterprise Framework White Paper V0. 1
Heiko Ludwig, Nathalie Baracaldo, Gegi Thomas, Yi Zhou, Ali Anwar, Shashank Rajamoni, Yuya Ong, Jayaram Radhakrishnan, Ashish Verma, Mathieu Sinn, others
arXiv preprint arXiv:2007.10987, 2020

TraceHub - A Platform to Bridge the Gap between State-of-the-Art Time-Series Analytics and Datasets
Shubham Agarwal, Christian Muise, Mayank Agarwal, Sohini Upadhyay, Zilu Tang, Zhongshen Zeng, Yasaman Khazaeni
Proceedings of the AAAI Conference on Artificial Intelligence, pp. 13600-13601, 2020
Abstract   machine learning, computer science, artificial intelligence, analytics

CLAI: A Platform for AI Skills on the Command Line
Mayank Agarwal, Jorge J Barroso, Tathagata Chakraborti, Eli M Dow, Kshitij Fadnis, Borja Godoy, Kartik Talamadupula
arXiv preprint arXiv:2002.00762, 2020


2019

Statistical model aggregation via parameter matching
Mikhail Yurochkin, Mayank Agarwal, Soumya Ghosh, Kristjan Greenewald, Nghia Hoang
Advances in Neural Information Processing Systems, pp. 10954--10964, 2019
Abstract

Bayesian Nonparametric Federated Learning of Neural Networks
Mikhail Yurochkin, Mayank Agarwal, Soumya Ghosh, Kristjan Greenewald, Nghia Hoang, Yasaman Khazaeni
Proceedings of the 36th International Conference on Machine Learning, pp. 7252--7261, PMLR, 2019
Abstract

Online Semi-Supervised Learning with Bandit Feedback
Mikhail Yurochkin, Sohini Upadhyay, Djallel Bouneffouf, Mayank Agarwal, Yasaman Khazaeni
2nd Learning from Limited Labeled Data (LLD) Workshop, ICLR 2019
Abstract


2018

Machine Translation: A Literature Review
Ankush Garg, Mayank Agarwal
arXiv preprint arXiv:1901.01122, 2018
Abstract

A Bandit Approach to Posterior Dialog Orchestration Under a Budget
Sohini Upadhyay, Mayank Agarwal, Djallel Bounneffouf, and Yasaman Khazaeni
2nd Conversational AI Workshop , NeurIPS, 2018




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