14 citations · 22 across the 2 of their papers we have counts for
5 papers
Minimax Lower Bounds for Transfer Learning with Linear and One-hidden Layer Neural Networks
Seyed Mohammadreza Mousavi Kalan, Zalan Fabian, A. Salman Avestimehr +1
Transfer learning has emerged as a powerful technique for improving the performance of machine learning models on new domains where labeled training data may be scarce. In this app…
Fitting ReLUs via SGD and Quantized SGD
Seyed Mohammadreza Mousavi Kalan, Mahdi Soltanolkotabi, A. Salman Avestimehr
In this paper we focus on the problem of finding the optimal weights of the shallowest of neural networks consisting of a single Rectified Linear Unit (ReLU). These functions are o…
Polynomially Coded Regression: Optimal Straggler Mitigation via Data Encoding
Songze Li, Seyed Mohammadreza Mousavi Kalan, Qian Yu +2
We consider the problem of training a least-squares regression model on a large dataset using gradient descent. The computation is carried out on a distributed system consisting of…
Fundamental Resource Trade-offs for Encoded Distributed Optimization
A. Salman Avestimehr, Seyed Mohammadreza Mousavi Kalan, Mahdi Soltanolkotabi
Dealing with the shear size and complexity of today's massive data sets requires computational platforms that can analyze data in a parallelized and distributed fashion. A major bo…
Near-Optimal Straggler Mitigation for Distributed Gradient Methods
Songze Li, Seyed Mohammadreza Mousavi Kalan, A. Salman Avestimehr +1
Modern learning algorithms use gradient descent updates to train inferential models that best explain data. Scaling these approaches to massive data sizes requires proper distribut…