483 citations · 760 across the 48 of their papers we have counts for
7 papers · 1 filter
On the Efficiency of ERM in Feature Learning
Ayoub El Hanchi, Chris J. Maddison, Murat A. Erdogdu
Given a collection of feature maps indexed by a set , we study the performance of empirical risk minimization (ERM) on regression problems with square loss over the un…
Robust Feature Learning for Multi-Index Models in High Dimensions
Alireza Mousavi-Hosseini, Adel Javanmard, Murat A. Erdogdu
Recently, there have been numerous studies on feature learning with neural networks, specifically on learning single- and multi-index models where the target is a function of a low…
Learning Multi-Index Models with Neural Networks via Mean-Field Langevin Dynamics
Alireza Mousavi-Hosseini, Denny Wu, Murat A. Erdogdu
We study the problem of learning multi-index models in high-dimensions using a two-layer neural network trained with the mean-field Langevin algorithm. Under mild distributional as…
Minimax Linear Regression under the Quantile Risk
Ayoub El Hanchi, Chris J. Maddison, Murat A. Erdogdu
We study the problem of designing minimax procedures in linear regression under the quantile risk. We start by considering the realizable setting with independent Gaussian noise, w…
Pruning is Optimal for Learning Sparse Features in High-Dimensions
Nuri Mert Vural, Murat A. Erdogdu
While it is commonly observed in practice that pruning networks to a certain level of sparsity can improve the quality of the features, a theoretical explanation of this phenomenon…
A Separation in Heavy-Tailed Sampling: Gaussian vs. Stable Oracles for Proximal Samplers
Ye He, Alireza Mousavi-Hosseini, Krishnakumar Balasubramanian +1
We study the complexity of heavy-tailed sampling and present a separation result in terms of obtaining high-accuracy versus low-accuracy guarantees i.e., samplers that require only…
Sampling from the Mean-Field Stationary Distribution
Yunbum Kook, Matthew S. Zhang, Sinho Chewi +2
We study the complexity of sampling from the stationary distribution of a mean-field SDE, or equivalently, the complexity of minimizing a functional over the space of probability m…