Fartash Faghri

According to our database, Fartash Faghri authored at least 23 papers between 2012 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2023

Weight subcloning: direct initialization of transformers using larger pretrained ones.

Mohammad Samragh, Mehrdad Farajtabar, Sachin Mehta, Raviteja Vemulapalli, Fartash Faghri, Devang Naik, Oncel Tuzel, Mohammad Rastegari

CoRR, 2023

Label-efficient Training of Small Task-specific Models by Leveraging Vision Foundation Models.

Raviteja Vemulapalli, Hadi Pouransari, Fartash Faghri, Sachin Mehta, Mehrdad Farajtabar, Mohammad Rastegari, Oncel Tuzel

CoRR, 2023

MobileCLIP: Fast Image-Text Models through Multi-Modal Reinforced Training.

Pavan Kumar Anasosalu Vasu, Hadi Pouransari, Fartash Faghri, Raviteja Vemulapalli, Oncel Tuzel

CoRR, 2023

TiC-CLIP: Continual Training of CLIP Models.

Saurabh Garg, Mehrdad Farajtabar, Hadi Pouransari, Raviteja Vemulapalli, Sachin Mehta, Oncel Tuzel, Vaishaal Shankar, Fartash Faghri

CoRR, 2023

SAM-CLIP: Merging Vision Foundation Models towards Semantic and Spatial Understanding.

Haoxiang Wang, Pavan Kumar Anasosalu Vasu, Fartash Faghri, Raviteja Vemulapalli, Mehrdad Farajtabar, Sachin Mehta, Mohammad Rastegari, Oncel Tuzel, Hadi Pouransari

CoRR, 2023

CLIP meets Model Zoo Experts: Pseudo-Supervision for Visual Enhancement.

Mohammadreza Salehi, Mehrdad Farajtabar, Maxwell Horton, Fartash Faghri, Hadi Pouransari, Raviteja Vemulapalli, Oncel Tuzel, Ali Farhadi, Mohammad Rastegari, Sachin Mehta

CoRR, 2023

FastFill: Efficient Compatible Model Update.

Florian Jaeckle, Fartash Faghri, Ali Farhadi, Oncel Tuzel, Hadi Pouransari

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Reinforce Data, Multiply Impact: Improved Model Accuracy and Robustness with Dataset Reinforcement.

Fartash Faghri, Hadi Pouransari, Sachin Mehta, Mehrdad Farajtabar, Ali Farhadi, Mohammad Rastegari, Oncel Tuzel

Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

2022

MixTailor: Mixed Gradient Aggregation for Robust Learning Against Tailored Attacks.

Ali Ramezani-Kebrya, Iman Tabrizian, Fartash Faghri, Petar Popovski

Trans. Mach. Learn. Res., 2022

RangeAugment: Efficient Online Augmentation with Range Learning.

Sachin Mehta, Saeid Naderiparizi, Fartash Faghri, Maxwell Horton, Lailin Chen, Ali Farhadi, Oncel Tuzel, Mohammad Rastegari

CoRR, 2022

APE: Aligning Pretrained Encoders to Quickly Learn Aligned Multimodal Representations.

Elan Rosenfeld, Preetum Nakkiran, Hadi Pouransari, Oncel Tuzel, Fartash Faghri

CoRR, 2022

2021

NUQSGD: Provably Communication-efficient Data-parallel SGD via Nonuniform Quantization.

Ali Ramezani-Kebrya, Fartash Faghri, Ilya Markov, Vitalii Aksenov, Dan Alistarh, Daniel M. Roy

J. Mach. Learn. Res., 2021

Training Efficiency and Robustness in Deep Learning.

Fartash Faghri

CoRR, 2021

Bridging the Gap Between Adversarial Robustness and Optimization Bias.

Fartash Faghri, Cristina Nader Vasconcelos, David J. Fleet, Fabian Pedregosa, Nicolas Le Roux

CoRR, 2021

2020

A Study of Gradient Variance in Deep Learning.

Fartash Faghri, David Duvenaud, David J. Fleet, Jimmy Ba

CoRR, 2020

Adversarial Robustness through Regularization: A Second-Order Approach.

Avery Ma, Fartash Faghri, Amir-massoud Farahmand

CoRR, 2020

Adaptive Gradient Quantization for Data-Parallel SGD.

Fartash Faghri, Iman Tabrizian, Ilia Markov, Dan Alistarh, Daniel M. Roy, Ali Ramezani-Kebrya

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

2019

NUQSGD: Improved Communication Efficiency for Data-parallel SGD via Nonuniform Quantization.

Ali Ramezani-Kebrya, Fartash Faghri, Daniel M. Roy

CoRR, 2019

2018

Adversarial Spheres.

Justin Gilmer, Luke Metz, Fartash Faghri, Samuel S. Schoenholz, Maithra Raghu, Martin Wattenberg, Ian J. Goodfellow

Proceedings of the 6th International Conference on Learning Representations, 2018

VSE++: Improving Visual-Semantic Embeddings with Hard Negatives.

Fartash Faghri, David J. Fleet, Jamie Ryan Kiros, Sanja Fidler

Proceedings of the British Machine Vision Conference 2018, 2018

2017

VSE++: Improved Visual-Semantic Embeddings.

Fartash Faghri, David J. Fleet, Jamie Ryan Kiros, Sanja Fidler

CoRR, 2017

2016

Adversarial Manipulation of Deep Representations.

Sara Sabour, Yanshuai Cao, Fartash Faghri, David J. Fleet

Proceedings of the 4th International Conference on Learning Representations, 2016

2012

Graph based semi-supervised human pose estimation: When the output space comes to help.

Nima Pourdamghani, Hamid R. Rabiee, Fartash Faghri, Mohammad Hossein Rohban

Pattern Recognit. Lett., 2012