Optimizing sensing duration for multiple secondary users in cognitive radio networks. - Ashkan Esmaeili; Saeed Mashhadi (IWCIT, 2014)

Fast methods for recovering sparse parameters in linear low rank models. - Ashkan Esmaeili; Arash Amini; Farokh Marvasti (GlobalSIP, 2016)

Comparison of several sparse recovery methods for low rank matrices with random samples. - Ashkan Esmaeili; Farokh Marvasti (IST, 2016)

Iterative Null-space Projection Method with Adaptive Thresholding in Sparse Signal Recovery and Matrix Completion. - Ehsan Asadi; Ashkan Esmaeili; Farokh Marvasti (CoRR, 2016)

New Methods of Enhancing Prediction Accuracy in Linear Models with Missing Data. - Mohammad Amin Fakharian; Ashkan Esmaeili; Farokh Marvasti (CoRR, 2017)

OBTAIN: Real-Time Beat Tracking in Audio Signals. - Ali Mottaghi; Kayhan Behdin; Ashkan Esmaeili; Mohammadreza Heydari; Farrokh Marvasti (CoRR, 2017)

Transduction with Matrix Completion Using Smoothed Rank Function. - Ashkan Esmaeili; Kayhan Behdin; Mohammad Amin Fakharian; Farokh Marvasti (CoRR, 2018)

Recovering Quantized Data with Missing Information Using Bilinear Factorization and Augmented Lagrangian Method. - Ashkan Esmaeili; Kayhan Behdin; Sina Al-E.-Mohammad; Farokh Marvasti (CoRR, 2018)

A Novel Approach to Sparse Inverse Covariance Estimation Using Transform Domain Updates and Exponentially Adaptive Thresholding. - Ashkan Esmaeili; Farokh Marvasti (CoRR, 2018)

Iterative null space projection method with adaptive thresholding in sparse signal recovery. - Ashkan Esmaeili; Ehsan Asadi Kangarshahi; Farokh Marvasti (IET Signal Process., 2018)

A Novel Approach to Quantized Matrix Completion Using Huber Loss Measure. - Ashkan Esmaeili; Farokh Marvasti (IEEE Signal Process. Lett., 2019)

Select to Better Learn: Fast and Accurate Deep Learning Using Data Selection From Nonlinear Manifolds. - Mohsen Joneidi; Saeed Vahidian; Ashkan Esmaeili; Weijia Wang 002; Nazanin Rahnavard; Bill Lin 001; Mubarak Shah (CVPR, 2020)

Transductive multi-label learning from missing data using smoothed rank function. - Ashkan Esmaeili; Kayhan Behdin; Mohammad Amin Fakharian; Farokh Marvasti (Pattern Anal. Appl., 2020)

Missing Low-Rank and Sparse Decomposition Based on Smoothed Nuclear Norm. - Masoumeh Azghani; Ashkan Esmaeili; Kayhan Behdin; Farokh Marvasti (IEEE Trans. Circuits Syst. Video Technol., 2020)

Two-Way Spectrum Pursuit for CUR Decomposition and its Application in Joint Column/Row Subset Selection. - Ashkan Esmaeili; Mohsen Joneidi; Mehrdad Salimitari; Umar Khalid; Nazanin Rahnavard (MLSP, 2021)

LSDAT: Low-Rank and Sparse Decomposition for Decision-based Adversarial Attack. - Ashkan Esmaeili; Marzieh Edraki; Nazanin Rahnavard; Mubarak Shah; Ajmal Mian (CoRR, 2021)

Generative Model Adversarial Training for Deep Compressed Sensing. - Ashkan Esmaeili (CoRR, 2021)

CNLL: A Semi-supervised Approach For Continual Noisy Label Learning. - Nazmul Karim; Umar Khalid; Ashkan Esmaeili; Nazanin Rahnavard (CVPR Workshops, 2022)

RODD: A Self-Supervised Approach for Robust Out-of-Distribution Detection. - Umar Khalid; Ashkan Esmaeili; Nazmul Karim; Nazanin Rahnavard (CVPR Workshops, 2022)

Spectrum Pursuit With Residual Descent for Column Subset Selection Problem: Theoretical Guarantees and Applications in Deep Learning. - Saeed Vahidian; Mohsen Joneidi; Ashkan Esmaeili; Siavash Khodadadeh; Sharare Zehtabian; Bill Lin 001 (IEEE Access, 2022)

Low-Rank and Sparse Decomposition for Low-Query Decision-Based Adversarial Attacks. - Ashkan Esmaeili; Marzieh Edraki; Nazanin Rahnavard; Ajmal Mian; Mubarak Shah (IEEE Trans. Inf. Forensics Secur., 2024)