Amir Erfan Eshratifar

According to our database, Amir Erfan Eshratifar authored at least 13 papers between 2018 and 2021.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2021

JointDNN: An Efficient Training and Inference Engine for Intelligent Mobile Cloud Computing Services.

Amir Erfan Eshratifar, Mohammad Saeed Abrishami, Massoud Pedram

IEEE Trans. Mob. Comput., 2021

Coarse2Fine: a two-stage training method for fine-grained visual classification.

Amir Erfan Eshratifar, David Eigen, Michael Gormish, Massoud Pedram

Mach. Vis. Appl., 2021

2020

Run-time Deep Model Multiplexing.

Amir Erfan Eshratifar, Massoud Pedram

CoRR, 2020

Efficient Training of Deep Convolutional Neural Networks by Augmentation in Embedding Space.

Mohammad Saeed Abrishami, Amir Erfan Eshratifar, David Eigen, Yanzhi Wang, Shahin Nazarian, Massoud Pedram

Proceedings of the 21st International Symposium on Quality Electronic Design, 2020

Runtime Deep Model Multiplexing for Reduced Latency and Energy Consumption Inference.

Amir Erfan Eshratifar, Massoud Pedram

Proceedings of the 38th IEEE International Conference on Computer Design, 2020

Video Person Re-ID: Fantastic Techniques and Where to Find Them (Student Abstract).

Priyank Pathak, Amir Erfan Eshratifar, Michael Gormish

Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019

Video Person Re-ID: Fantastic Techniques and Where to Find Them.

Priyank Pathak, Amir Erfan Eshratifar, Michael Gormish

CoRR, 2019

Towards Collaborative Intelligence Friendly Architectures for Deep Learning.

Amir Erfan Eshratifar, Amirhossein Esmaili, Massoud Pedram

Proceedings of the 20th International Symposium on Quality Electronic Design, 2019

BottleNet: A Deep Learning Architecture for Intelligent Mobile Cloud Computing Services.

Amir Erfan Eshratifar, Amirhossein Esmaili, Massoud Pedram

Proceedings of the 2019 IEEE/ACM International Symposium on Low Power Electronics and Design, 2019

A Meta-Learning Approach for Custom Model Training.

Amir Erfan Eshratifar, Mohammad Saeed Abrishami, David Eigen, Massoud Pedram

Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

2018

Gradient Agreement as an Optimization Objective for Meta-Learning.

Amir Erfan Eshratifar, David Eigen, Massoud Pedram

CoRR, 2018

A hardware-friendly algorithm for scalable training and deployment of dimensionality reduction models on FPGA.

Mahdi Nazemi, Amir Erfan Eshratifar, Massoud Pedram

Proceedings of the 19th International Symposium on Quality Electronic Design, 2018

Energy and Performance Efficient Computation Offloading for Deep Neural Networks in a Mobile Cloud Computing Environment.

Amir Erfan Eshratifar, Massoud Pedram

Proceedings of the 2018 on Great Lakes Symposium on VLSI, 2018