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Afshin Abdi
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2020 – today
- 2024
- [i6]Gianluigi Silvestri, Fabio Valerio Massoli, Tribhuvanesh Orekondy, Afshin Abdi, Arash Behboodi:
Reinforcement Learning of Adaptive Acquisition Policies for Inverse Problems. CoRR abs/2407.07794 (2024) - 2023
- [c31]Afshin Abdi, Saeed Rashidi, Faramarz Fekri
, Tushar Krishna:
Efficient Distributed Inference of Deep Neural Networks via Restructuring and Pruning. AAAI 2023: 6640-6648 - 2022
- [c30]Aditya Sant, Afshin Abdi, Joseph Soriaga:
Deep Sequential Beamformer Learning for Multipath Channels in Mmwave Communication Systems. ICASSP 2022: 5198-5202 - [c29]Yashas Malur Saidutta
, Faramarz Fekri
, Afshin Abdi:
A Machine Learning Framework for Privacy-Aware Distributed Functional Compression over AWGN Channels. ITW 2022: 380-385 - [i5]Yashas Malur Saidutta, Afshin Abdi, Faramarz Fekri:
A Machine Learning Framework for Distributed Functional Compression over Wireless Channels in IoT. CoRR abs/2201.09483 (2022) - [i4]Hang Zhang, Afshin Abdi, Faramarz Fekri
:
Structure Learning in Graphical Models from Indirect Observations. CoRR abs/2205.03454 (2022) - 2021
- [j4]Yashas Malur Saidutta
, Afshin Abdi
, Faramarz Fekri
:
Joint Source-Channel Coding Over Additive Noise Analog Channels Using Mixture of Variational Autoencoders. IEEE J. Sel. Areas Commun. 39(7): 2000-2013 (2021) - [c28]Yashas Malur Saidutta
, Afshin Abdi, Faramarz Fekri
:
Analog Joint Source-Channel Coding for Distributed Functional Compression using Deep Neural Networks. ISIT 2021: 2429-2434 - [c27]Hang Zhang, Afshin Abdi, Faramarz Fekri
:
A General Framework for the Design of Compressive Sensing using Density Evolution. ITW 2021: 1-6 - 2020
- [b1]Afshin Abdi:
Distributed learning and inference in deep models. Georgia Institute of Technology, Atlanta, GA, USA, 2020 - [j3]Alireza Aghasi, Afshin Abdi, Justin Romberg:
Fast Convex Pruning of Deep Neural Networks. SIAM J. Math. Data Sci. 2(1): 158-188 (2020) - [c26]Afshin Abdi, Faramarz Fekri
:
Quantized Compressive Sampling of Stochastic Gradients for Efficient Communication in Distributed Deep Learning. AAAI 2020: 3105-3112 - [c25]Afshin Abdi, Faramarz Fekri
:
Indirect Stochastic Gradient Quantization and Its Application in Distributed Deep Learning. AAAI 2020: 3113-3120 - [c24]Afshin Abdi, Yashas Malur Saidutta
, Faramarz Fekri
:
Analog Compression and Communication for Federated Learning over Wireless MAC. SPAWC 2020: 1-5 - [c23]Yashas Malur Saidutta
, Afshin Abdi, Faramarz Fekri
:
VAE for Joint Source-Channel Coding of Distributed Gaussian Sources over AWGN MAC. SPAWC 2020: 1-5 - [i3]Afshin Abdi, Saeed Rashidi, Faramarz Fekri, Tushar Krishna:
Restructuring, Pruning, and Adjustment of Deep Models for Parallel Distributed Inference. CoRR abs/2008.08289 (2020)
2010 – 2019
- 2019
- [c22]Yashas Malur Saidutta
, Afshin Abdi, Faramarz Fekri
:
Joint Source-Channel Coding of Gaussian sources over AWGN channels via Manifold Variational Autoencoders. Allerton 2019: 514-520 - [c21]Hang Zhang, Afshin Abdi, Faramarz Fekri
:
Recovering Noisy-Pseudo-Sparse Signals From Linear Measurements via l∞. Allerton 2019: 1154-1159 - [c20]Yashas Malur Saidutta
, Afshin Abdi, Faramarz Fekri
:
M to 1 Joint Source-Channel Coding of Gaussian Sources via Dichotomy of the Input Space Based on Deep Learning. DCC 2019: 488-497 - [c19]Hang Zhang, Afshin Abdi, Faramarz Fekri
:
Analysis of Sparse-integer Measurement Matrices in Compressive Sensing. ICASSP 2019: 4923-4927 - [c18]Hang Zhang, Afshin Abdi, Faramarz Fekri
:
Compressive Sensing with a Multiple Convex Sets Domain. ISIT 2019: 592-596 - [c17]Yashas Malur Saidutta
, Afshin Abdi, Faramarz Fekri
:
Joint Source-Channel Coding for Gaussian Sources over AWGN Channels using Variational Autoencoders. ISIT 2019: 1327-1331 - [c16]Afshin Abdi, Faramarz Fekri
:
Reducing Communication Overhead via CEO in Distributed Training. SPAWC 2019: 1-5 - [i2]Afshin Abdi, Faramarz Fekri:
Nested Dithered Quantization for Communication Reduction in Distributed Training. CoRR abs/1904.01197 (2019) - 2018
- [j2]Ali Payani
, Afshin Abdi
, Xin Tian
, Faramarz Fekri
, Mohamed A. Mohandes:
Advances in Seismic Data Compression via Learning from Data: Compression for Seismic Data Acquisition. IEEE Signal Process. Mag. 35(2): 51-61 (2018) - [c15]Hang Zhang, Afshin Abdi, Faramarz Fekri
:
Sparse Recovery of Sign Vectors under Uncertain Sensing Matrices. ITW 2018: 1-5 - [c14]Xin Tian, Afshin Abdi, Entao Liu, Faramarz Fekri
:
Seismic Signal Compression Through Delay Compensated and Entropy Constrained Dictionary Learning. SPAWC 2018: 1-5 - [i1]Alireza Aghasi, Afshin Abdi, Justin Romberg:
Fast Convex Pruning of Deep Neural Networks. CoRR abs/1806.06457 (2018) - 2017
- [j1]Afshin Abdi
, Arash Einolghozati, Faramarz Fekri
:
Quantization in Molecular Signal Sensing via Biological Agents. IEEE Trans. Mol. Biol. Multi Scale Commun. 3(2): 106-117 (2017) - [c13]Xin Tian, Afshin Abdi, Entao Liu, Faramarz Fekri
:
Memory-assisted seismic signal compression based on dictionary learning and sparse coding. GlobalSIP 2017: 358-362 - [c12]Afshin Abdi, Faramarz Fekri
:
Mixture source identification in non-stationary data streams with applications in compression. ICASSP 2017: 2502-2506 - [c11]Afshin Abdi, Ali Payani, Faramarz Fekri
:
Learning dictionary for efficient signal compression. ICASSP 2017: 3689-3693 - [c10]Afshin Abdi, Faramarz Fekri
:
Optimal sensor selection in the presence of noise and interference. ISIT 2017: 2378-2382 - [c9]Afshin Abdi, Arash Einolghozati, Faramarz Fekri
:
Computing framework in biological cells via stochastic methods. ITW 2017: 339-343 - [c8]Hang Zhang, Afshin Abdi, Faramarz Fekri
:
Recovery of sign vectors in quadratic compressed sensing. ITW 2017: 379-383 - [c7]Hang Zhang, Afshin Abdi, Faramarz Fekri
:
Compressive sensing with energy constraint. ITW 2017: 389-393 - [c6]Alireza Aghasi, Afshin Abdi, Nam Nguyen, Justin Romberg:
Net-Trim: Convex Pruning of Deep Neural Networks with Performance Guarantee. NIPS 2017: 3177-3186 - 2016
- [c5]Hang Zhang, Afshin Abdi, Faramarz Fekri
, Hadi Esmaeilzadeh:
Error correction for approximate computing. Allerton 2016: 948-953 - [c4]Arash Einolghozati, Jun Zou, Afshin Abdi, Faramarz Fekri
:
Micro-RNA profile detection via factor graphs. SPAWC 2016: 1-5 - [c3]Ali Payani, Afshin Abdi, Faramarz Fekri
:
Near optimal representative subset selection from short sequences generated by a stationary source. SPAWC 2016: 1-5 - 2015
- [c2]Afshin Abdi, Faramarz Fekri
:
Source identification and compression of mixture data from finite observations. ITW Fall 2015: 29-33
2000 – 2009
- 2005
- [c1]Afshin Abdi, Kambiz Nayebi:
On the design of FIR optimum orthonormal filter banks. ICASSP (4) 2005: 545-548
Coauthor Index
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last updated on 2024-08-18 00:30 CEST by the dblp team
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