Published in Acre Labs, 2022
Recommended citation: Ahluwalia, Saran. " SFR Returns and HPA - A cross-section study across the United States" Working Paper http://ahlusar1989.github.io/files/SFR_returns_and_HPA_sample.pdf
Published in Fundamentals of Statistical Inference II with Dr. Ana-Marie Staicu, 2020
This paper was a part of my graduate coursework in non-parametric statistics and Bayesian estimation
Recommended citation: Ahluwalia, Saran, Kim, Minjee and Park, Hannah. (2020, May). " Review of Joint Clustering with Correlated Variables" Unpublished Manucript http://ahlusar1989.github.io/files/joint_clustering_paper.pdf
Published in North Carolina State University Symposium, 2019
There are two main approaches to reinforcement learning: value based methods that aim to find an optimal Q-function, and policy based ones that directly look for the optimal policy. However most of reinforcement learning problems (such as learning to play games) have large or even continuous states spaces, which makes constructing Q-values table impossible. Thus, there is a need for approximate reinforcement learning. In this paper the Deep reinforcement learning methods we’ve used to train an agent to play in a Doom environment.
Recommended citation: Ahluwalia, Saran and Laber, Eric. (2019, May). " Deep Learning within the Context of Doom" Unpublished Manucript http://ahlusar1989.github.io/files/st_498_independent_study_05_04_2019.pdf
Published in North Carolina State University OUR Symposium, 2018
This paper was prepared after exploratory work in telephony studies of open-sourced feedback and complaints from victims of robocalls and of predatory phishing scams.
Recommended citation: Ahluwalia, S. & Reaves, B. (2018, April). Repucall. Paper submission at the North Carolina State University OUR Symposium, Raleigh, NC. http://ahlusar1989.github.io/files/repucall.pdf
Published in Laboratory for Analytical Sciences Conference, 2017
This conference presentation highlights the use of deep learning applied to human trafficking.
Recommended citation: Saanchi, Y, Wang, M., Ahluwalia, S., Laber, E. & Caltagirone, S. (2017, December). Multi-angled Statistical Approach to Human Trafficking Detection and Profiling. Laboratory for Analytical Sciences, Raleigh, NC. http://ahlusar1989.github.io/files/las_2017_trafficking_detection_v2.pdf