38 citations · 176 across the 26 of their papers we have counts for
3 papers · 1 filter
Gradient Descent for Low-Rank Functions
Romain Cosson, Ali Jadbabaie, Anuran Makur +2
Several recent empirical studies demonstrate that important machine learning tasks, e.g., training deep neural networks, exhibit low-rank structure, where the loss function varies…
Functional Linear Regression of Cumulative Distribution Functions
Qian Zhang, Anuran Makur, Kamyar Azizzadenesheli
The estimation of cumulative distribution functions (CDF) is an important learning task with a great variety of downstream applications, such as risk assessments in predictions and…
Federated Optimization of Smooth Loss Functions
Ali Jadbabaie, Anuran Makur, Devavrat Shah
In this work, we study empirical risk minimization (ERM) within a federated learning framework, where a central server minimizes an ERM objective function using training data that…