Zobrazeno 1 - 10
of 228
pro vyhledávání: '"Sekhon, Jasjeet"'
Autor:
You, Chenyu, Min, Yifei, Dai, Weicheng, Sekhon, Jasjeet S., Staib, Lawrence, Duncan, James S.
Fine-tuning pre-trained vision-language models, like CLIP, has yielded success on diverse downstream tasks. However, several pain points persist for this paradigm: (i) directly tuning entire pre-trained models becomes both time-intensive and computat
Externí odkaz:
http://arxiv.org/abs/2403.07241
Autor:
Chan, Colleen, You, Kisung, Chung, Sunny, Giuffrè, Mauro, Saarinen, Theo, Rajashekar, Niroop, Pu, Yuan, Shin, Yeo Eun, Laine, Loren, Wong, Ambrose, Kizilcec, René, Sekhon, Jasjeet, Shung, Dennis
Applications of large language models (LLMs) like ChatGPT have potential to enhance clinical decision support through conversational interfaces. However, challenges of human-algorithmic interaction and clinician trust are poorly understood. GutGPT, a
Externí odkaz:
http://arxiv.org/abs/2312.10072
Deep learning research has uncovered the phenomenon of benign overfitting for overparameterized statistical models, which has drawn significant theoretical interest in recent years. Given its simplicity and practicality, the ordinary least squares (O
Externí odkaz:
http://arxiv.org/abs/2309.15769
Autor:
You, Chenyu, Dai, Weicheng, Min, Yifei, Staib, Lawrence, Sekhon, Jasjeet S., Duncan, James S.
Medical data often exhibits long-tail distributions with heavy class imbalance, which naturally leads to difficulty in classifying the minority classes (i.e., boundary regions or rare objects). Recent work has significantly improved semi-supervised m
Externí odkaz:
http://arxiv.org/abs/2304.02689
A central goal in social science is to evaluate the causal effect of a policy. One dominant approach is through panel data analysis in which the behaviors of multiple units are observed over time. The information across time and space motivates two g
Externí odkaz:
http://arxiv.org/abs/2207.14481
Autor:
Shung, Dennis L., Chan, Colleen E., You, Kisung, Nakamura, Shinpei, Saarinen, Theo, Zheng, Neil S., Simonov, Michael, Li, Darrick K., Tsay, Cynthia, Kawamura, Yuki, Shen, Matthew, Hsiao, Allen, Sekhon, Jasjeet S., Laine, Loren
Publikováno v:
In Gastroenterology November 2024 167(6):1198-1212
We argue that randomized controlled trials (RCTs) are special even among settings where average treatment effects are identified by a nonparametric unconfoundedness assumption. This claim follows from two results of Robins and Ritov (1997): (1) with
Externí odkaz:
http://arxiv.org/abs/2108.11342
Autor:
Luo, Jianmei, Annakula, ChandraVyas, Kannamareddy, Aruna Sai, Sekhon, Jasjeet S., Hsu, William Henry, Higgins, Michael
As the size $n$ of datasets become massive, many commonly-used clustering algorithms (for example, $k$-means or hierarchical agglomerative clustering (HAC) require prohibitive computational cost and memory. In this paper, we propose a solution to the
Externí odkaz:
http://arxiv.org/abs/1907.02907
Regression trees and their ensemble methods are popular methods for nonparametric regression: they combine strong predictive performance with interpretable estimators. To improve their utility for locally smooth response surfaces, we study regression
Externí odkaz:
http://arxiv.org/abs/1906.06463
We develop and analyze empirical Bayes Stein-type estimators for use in the estimation of causal effects in large-scale online experiments. While online experiments are generally thought to be distinguished by their large sample size, we focus on the
Externí odkaz:
http://arxiv.org/abs/1904.12918