2 citations · 18 across the 31 of their papers we have counts for
13 papers · 1 filter
An Algorithm for Computing the Capacity of Symmetrized KL Information for Discrete Channels
Haobo Chen, Gholamali Aminian, Yuheng Bu
Symmetrized Kullback-Leibler (KL) information (\(I_{\mathrm{SKL}}\)), which symmetrizes the traditional mutual information by integrating Lautum information, has been shown as a cr…
Information-theoretic Characterizations of Generalization Error for the Gibbs Algorithm
Gholamali Aminian, Yuheng Bu, Laura Toni +2
Various approaches have been developed to upper bound the generalization error of a supervised learning algorithm. However, existing bounds are often loose and even vacuous when ev…
How Does Pseudo-Labeling Affect the Generalization Error of the Semi-Supervised Gibbs Algorithm?
Haiyun He, Gholamali Aminian, Yuheng Bu +2
We provide an exact characterization of the expected generalization error (gen-error) for semi-supervised learning (SSL) with pseudo-labeling via the Gibbs algorithm. The gen-error…
Tighter Expected Generalization Error Bounds via Convexity of Information Measures
Gholamali Aminian, Yuheng Bu, Gregory Wornell +1
Generalization error bounds are essential to understanding machine learning algorithms. This paper presents novel expected generalization error upper bounds based on the average jo…
An Information-theoretical Approach to Semi-supervised Learning under Covariate-shift
Gholamali Aminian, Mahed Abroshan, Mohammad Mahdi Khalili +2
A common assumption in semi-supervised learning is that the labeled, unlabeled, and test data are drawn from the same distribution. However, this assumption is not satisfied in man…
Information-Theoretic Bounds on the Moments of the Generalization Error of Learning Algorithms
Gholamali Aminian, Laura Toni, Miguel R. D. Rodrigues
Generalization error bounds are critical to understanding the performance of machine learning models. In this work, building upon a new bound of the expected value of an arbitrary…
Jensen-Shannon Information Based Characterization of the Generalization Error of Learning Algorithms
Gholamali Aminian, Laura Toni, Miguel R. D. Rodrigues
Generalization error bounds are critical to understanding the performance of machine learning models. In this work, we propose a new information-theoretic based generalization erro…
Diffusion Based Molecular Communication with Limited Molecule Production Rate
Hamid G. Bafghi, Amin Gohari, Mahtab Mirmohseni +1
This paper studies the impact of a transmitter's molecule generation process on the capacity of a concentration based Molecular Communication (MC) system. Constraints caused by the…
On the Capacity of a Class of Signal-Dependent Noise Channels
Hamid Ghourchian, Gholamali Aminian, Amin Gohari +2
In some applications, the variance of additive measurement noise depends on the signal that we aim to measure. For instance, additive Gaussian signal-dependent noise (AGSDN) channe…
On Medium Chemical Reaction in Diffusion-Based Molecular Communication: a Two-Way Relaying Example
Maryam Farahnak-Ghazani, Gholamali Aminian, Mahtab Mirmohseni +2
Chemical reactions are a prominent feature of molecular communication (MC) systems, with no direct parallels in wireless communications. While chemical reactions may be used inside…
On the Capacity of Point-to-Point and Multiple-Access Molecular Communications with Ligand-Receptors
Gholamali Aminian, Maryam Farahnak Ghazani, Mahtab Mirmohseni +2
In this paper, we consider the bacterial point-to-point and multiple-access molecular communications with ligand-receptors. For the point-to-point communication, we investigate com…
On the Capacity of Level and Type Modulation in Molecular Communication with Ligand Receptors
Gholamali Aminian, Mahtab Mirmohseni, Masoumeh Nasiri Kenari +1
In this paper, we consider the bacterial point-to-point communication problem with one transmitter and one receiver by considering the ligand receptor binding process. The most com…
Capacity of Diffusion based Molecular Communication Networks over LTI-Poisson Channels
Hamidreza Arjmandi, Gholamali Aminian, Amin Gohari +2
In this paper, the capacity of a diffusion based molecular communication network under the model of a Linear Time Invarient-Poisson (LTI-Poisson) channel is studied. Introduced in…