Pre-print
We consider the task of learning tree structured Ising models when the signs of different random variables are flipped independently with possibly unequal, unknown probabilities.
Recommended citation: Ashish Katiyar, Vatsal Shah, and Constantine Caramanis. "Robust Estimation of Tree Structured Ising Models." arXiv preprint arXiv:2006.05601 (2020). https://arxiv.org/pdf/2006.05601.pdf
Published in International Conference on Machine Learning, 2019
In this paper, we look at the problem of learning Gaussian Graphical Models when the samples have independent additive Gaussian noise.
Recommended citation: Ashish Katiyar, Jessica Hoffmann, Constantine Caramanis, "Robust Estimation of Tree Structured Gaussian Graphical Models" Proceedings of the 36th International Conference on Machine Learning, PMLR 97:3292-3300, 2019 http://proceedings.mlr.press/v97/katiyar19a/katiyar19a.pdf
Published in BMC bioinformatics, 2018
In this paper, we propose an algorithm to tackle the challenge of determining the composition of a heterogeneous cancer tissue by utilizing the data of accurate, but high cost, single cell line cell-by-cell observation methods in low cost aggregate observation method for heterogeneous cancer cell mixtures to obtain their composition in a Bayesian framework.
Recommended citation: Ashish Katiyar, Anwoy Mohanty, Jianping Hua, Sima Chao, Rosana Lopes, Aniruddha Datta and Michael L. Bittner(2018). "A Bayesian approach to determine the composition of heterogeneous cancer tissue" BMC Bioinformatics. 2018;19(Suppl 3)1 https://bmcbioinformatics.biomedcentral.com/track/pdf/10.1186/s12859-018-2062-0
Published in Proceedings of the 1st International Conference on Wireless Technologies for Humanitarian Relief, 2011
The proposed algorithm employs the temporal correlation of the narrowband sensor data in conjunction with the channel state information (CSI) for detection and error correction of the data received over the Rayleigh fading wireless channel.
Recommended citation: Ashish Katiyar, and Aditya K. Jagannatham (2011) "Bayesian data and channel joint maximum-likelihood based error correction in wireless sensor networks" Proceedings of the 1st International Conference on Wireless Technologies for Humanitarian Relief pp 141-146 http://www.iitk.ac.in/mwn/papers/acwr2011_submission_ashish.pdf