1 citations · 1 across the 3 of their papers we have counts for
3 papers
stat.ML2024
Agnostic Private Density Estimation for GMMs via List Global Stability
Mohammad Afzali, Hassan Ashtiani, Christopher Liaw
We consider the problem of private density estimation for mixtures of unrestricted high dimensional Gaussians in the agnostic setting. We prove the first upper bound on the sample…
stat.ML2023
On the Role of Noise in the Sample Complexity of Learning Recurrent Neural Networks: Exponential Gaps for Long Sequences
Alireza Fathollah Pour, Hassan Ashtiani
We consider the class of noisy multi-layered sigmoid recurrent neural networks with (unbounded) weights for classification of sequences of length , where independent noise d…
stat.ML2023★ 1 cited
Polynomial Time and Private Learning of Unbounded Gaussian Mixture Models
Jamil Arbas, Hassan Ashtiani, Christopher Liaw
We study the problem of privately estimating the parameters of -dimensional Gaussian Mixture Models (GMMs) with components. For this, we develop a technique to reduce the pr…