Zobrazeno 1 - 10
of 633
pro vyhledávání: '"NATARAJAN, KARTHIK"'
Autor:
Pang, Chao, Jiang, Xinzhuo, Pavinkurve, Nishanth Parameshwar, Kalluri, Krishna S., Minto, Elise L., Patterson, Jason, Zhang, Linying, Hripcsak, George, Gürsoy, Gamze, Elhadad, Noémie, Natarajan, Karthik
Synthetic Electronic Health Records (EHR) have emerged as a pivotal tool in advancing healthcare applications and machine learning models, particularly for researchers without direct access to healthcare data. Although existing methods, like rule-bas
Externí odkaz:
http://arxiv.org/abs/2402.04400
Publikováno v:
JMIR mHealth and uHealth, Vol 9, Iss 3, p e20738 (2021)
BackgroundThere is increasing interest in reusing person-generated wearable device data for research purposes, which raises concerns about data quality. However, the amount of literature on data quality challenges, specifically those for person-gener
Externí odkaz:
https://doaj.org/article/4fa84948ffba4e388fab8ed0f3017244
Distributionally robust optimization is used to solve decision making problems under adversarial uncertainty where the distribution of the uncertainty is itself ambiguous. In this paper, we identify a class of these instances that is solvable in poly
Externí odkaz:
http://arxiv.org/abs/2312.04890
A collection of $n$ random events is said to be $(n - 1)$-wise independent if any $n - 1$ events among them are mutually independent. We characterise all probability measures with respect to which $n$ random events are $(n - 1)$-wise independent. We
Externí odkaz:
http://arxiv.org/abs/2211.01596
Autor:
Ramachandra, Arjun, Natarajan, Karthik
In this paper, we provide a characterization of the expected value of monotone submodular set functions with $n$ pairwise independent random inputs. Inspired by the notion of ``correlation gap'', we study the ratio of the maximum expected value of a
Externí odkaz:
http://arxiv.org/abs/2209.08563
Given data on the choices made by consumers for different offer sets, a key challenge is to develop parsimonious models that describe and predict consumer choice behavior while being amenable to prescriptive tasks such as pricing and assortment optim
Externí odkaz:
http://arxiv.org/abs/2208.06115
We study the computational complexity of the optimal transport problem that evaluates the Wasserstein distance between the distributions of two K-dimensional discrete random vectors. The best known algorithms for this problem run in polynomial time i
Externí odkaz:
http://arxiv.org/abs/2203.01161
Autor:
Guide, Andrew, Sulieman, Lina, Garbett, Shawn, Cronin, Robert M, Spotnitz, Matthew, Natarajan, Karthik, Carroll, Robert J., Harris, Paul, Chen, Qingxia
Publikováno v:
In Journal of Biomedical Informatics July 2024 155
Autor:
Pang, Chao, Jiang, Xinzhuo, Kalluri, Krishna S, Spotnitz, Matthew, Chen, RuiJun, Perotte, Adler, Natarajan, Karthik
Publikováno v:
Proceedings of Machine Learning for Health, PMLR 158:239-260, 2021
Embedding algorithms are increasingly used to represent clinical concepts in healthcare for improving machine learning tasks such as clinical phenotyping and disease prediction. Recent studies have adapted state-of-the-art bidirectional encoder repre
Externí odkaz:
http://arxiv.org/abs/2111.08585
Publikováno v:
SIAM Journal on Optimization, 32(4), 2828-2858, 2022
In this paper, we compute the tightest possible bounds on the probability that the optimal value of a combinatorial optimization problem in maximization form with a random objective exceeds a given number, assuming only knowledge of the marginal dist
Externí odkaz:
http://arxiv.org/abs/2109.01591