3 citations · 6 across the 5 of their papers we have counts for
6 papers
Sample Complexity Bounds for Learning High-dimensional Simplices in Noisy Regimes
Amir Hossein Saberi, Amir Najafi, Seyed Abolfazl Motahari +1
In this paper, we find a sample complexity bound for learning a simplex from noisy samples. Assume a dataset of size is given which includes i.i.d. samples drawn from a uniform…
Zero-Error Feedback Capacity for Bounded Stabilization and Finite-State Additive Noise Channels
Amir Saberi, Farhad Farokhi, Girish Nair
This article studies the zero-error feedback capacity of {\em causal} discrete channels with memory. First, by extending the classical zero-error feedback capacity concept, a new n…
An Explicit Formula for the Zero-Error Feedback Capacity of a Class of Finite-State Additive Noise Channels
Amir Saberi, Farhad Farokhi, Girish N. Nair
It is known that for a discrete channel with correlated additive noise, the ordinary capacity with or without feedback both equal , where $ \mathcal{H}(Z)…
Bounded State Estimation over Finite-State Channels: Relating Topological Entropy and Zero-Error Capacity
Amir Saberi, Farhad Farokhi, Girish N. Nair
We investigate state estimation of linear systems over channels having a finite state not known by the transmitter or receiver. We show that similar to memoryless channels, zero-er…
State Estimation over Worst-Case Erasure and Symmetric Channels with Memory
Amir Saberi, Farhad Farokhi, Girish N. Nair
Worst-case models of erasure and symmetric channels are investigated, in which the number of channel errors occurring in each sliding window of a given length is bounded. Upper and…
On Statistical Learning of Simplices: Unmixing Problem Revisited
Amir Najafi, Saeed Ilchi, Amir H. Saberi +3
We study the sample complexity of learning a high-dimensional simplex from a set of points uniformly sampled from its interior. Learning of simplices is a long studied problem in c…