307 citations · 693 across the 70 of their papers we have counts for
10 papers · 1 filter
Optimal Ensemble Construction for Multi-Study Prediction with Applications to COVID-19 Excess Mortality Estimation
Gabriel Loewinger, Rolando Acosta Nunez, Rahul Mazumder +1
It is increasingly common to encounter prediction tasks in the biomedical sciences for which multiple datasets are available for model training. Common approaches such as pooling d…
Newer is not always better: Rethinking transferability metrics, their peculiarities, stability and performance
Shibal Ibrahim, Natalia Ponomareva, Rahul Mazumder
Fine-tuning of large pre-trained image and language models on small customized datasets has become increasingly popular for improved prediction and efficient use of limited resourc…
Sparse PCA: A New Scalable Estimator Based On Integer Programming
Kayhan Behdin, Rahul Mazumder
We consider the Sparse Principal Component Analysis (SPCA) problem under the well-known spiked covariance model. Recent work has shown that the SPCA problem can be reformulated as…
Predicting Census Survey Response Rates With Parsimonious Additive Models and Structured Interactions
Shibal Ibrahim, Peter Radchenko, Emanuel Ben-David +1
In this paper, we consider the problem of predicting survey response rates using a family of flexible and interpretable nonparametric models. The study is motivated by the US Censu…
Nonparametric Finite Mixture Models with Possible Shape Constraints: A Cubic Newton Approach
Haoyue Wang, Shibal Ibrahim, Rahul Mazumder
We explore computational aspects of maximum likelihood estimation of the mixture proportions of a nonparametric finite mixture model -- a convex optimization problem with old roots…
DSelect-k: Differentiable Selection in the Mixture of Experts with Applications to Multi-Task Learning
Hussein Hazimeh, Zhe Zhao, Aakanksha Chowdhery +5
The Mixture-of-Experts (MoE) architecture is showing promising results in improving parameter sharing in multi-task learning (MTL) and in scaling high-capacity neural networks. Sta…