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2020 – today
- 2023
[i14]Florian Jaeckle, Fartash Faghri, Ali Farhadi, Oncel Tuzel, Hadi Pouransari:
FastFill: Efficient Compatible Model Update. CoRR abs/2303.04766 (2023)- [i13]Fartash Faghri, Hadi Pouransari, Sachin Mehta, Mehrdad Farajtabar, Ali Farhadi, Mohammad Rastegari, Oncel Tuzel:
Reinforce Data, Multiply Impact: Improved Model Accuracy and Robustness with Dataset Reinforcement. CoRR abs/2303.08983 (2023) - 2022
- [i12]Ali Ramezani-Kebrya, Iman Tabrizian, Fartash Faghri, Petar Popovski:
MixTailor: Mixed Gradient Aggregation for Robust Learning Against Tailored Attacks. CoRR abs/2207.07941 (2022) - [i11]Elan Rosenfeld, Preetum Nakkiran, Hadi Pouransari, Oncel Tuzel, Fartash Faghri:
APE: Aligning Pretrained Encoders to Quickly Learn Aligned Multimodal Representations. CoRR abs/2210.03927 (2022) - [i10]Sachin Mehta, Saeid Naderiparizi, Fartash Faghri, Maxwell Horton, Lailin Chen, Ali Farhadi, Oncel Tuzel, Mohammad Rastegari:
RangeAugment: Efficient Online Augmentation with Range Learning. CoRR abs/2212.10553 (2022) - 2021
- [j2]Ali Ramezani-Kebrya, Fartash Faghri, Ilya Markov, Vitalii Aksenov, Dan Alistarh, Daniel M. Roy:
NUQSGD: Provably Communication-efficient Data-parallel SGD via Nonuniform Quantization. J. Mach. Learn. Res. 22: 114:1-114:43 (2021) - [i9]Fartash Faghri, Cristina Vasconcelos, David J. Fleet, Fabian Pedregosa, Nicolas Le Roux:
Bridging the Gap Between Adversarial Robustness and Optimization Bias. CoRR abs/2102.08868 (2021) - [i8]Ali Ramezani-Kebrya, Fartash Faghri, Ilia Markov, Vitaly Aksenov, Dan Alistarh, Daniel M. Roy:
NUQSGD: Provably Communication-efficient Data-parallel SGD via Nonuniform Quantization. CoRR abs/2104.13818 (2021) - [i7]Fartash Faghri:
Training Efficiency and Robustness in Deep Learning. CoRR abs/2112.01423 (2021) - 2020
- [c4]Fartash Faghri, Iman Tabrizian, Ilia Markov, Dan Alistarh, Daniel M. Roy, Ali Ramezani-Kebrya:
Adaptive Gradient Quantization for Data-Parallel SGD. NeurIPS 2020 - [i6]Avery Ma, Fartash Faghri, Amir-massoud Farahmand:
Adversarial Robustness through Regularization: A Second-Order Approach. CoRR abs/2004.01832 (2020) - [i5]Fartash Faghri, David Duvenaud, David J. Fleet, Jimmy Ba:
A Study of Gradient Variance in Deep Learning. CoRR abs/2007.04532 (2020) - [i4]Fartash Faghri, Iman Tabrizian, Ilia Markov, Dan Alistarh, Daniel M. Roy, Ali Ramezani-Kebrya
:
Adaptive Gradient Quantization for Data-Parallel SGD. CoRR abs/2010.12460 (2020)
2010 – 2019
- 2019
- [i3]Ali Ramezani-Kebrya, Fartash Faghri, Daniel M. Roy:
NUQSGD: Improved Communication Efficiency for Data-parallel SGD via Nonuniform Quantization. CoRR abs/1908.06077 (2019) - 2018
- [c3]Fartash Faghri, David J. Fleet, Jamie Ryan Kiros, Sanja Fidler:
VSE++: Improving Visual-Semantic Embeddings with Hard Negatives. BMVC 2018: 12 - [c2]Justin Gilmer, Luke Metz, Fartash Faghri, Samuel S. Schoenholz, Maithra Raghu, Martin Wattenberg, Ian J. Goodfellow:
Adversarial Spheres. ICLR (Workshop) 2018 - [i2]Justin Gilmer, Luke Metz, Fartash Faghri, Samuel S. Schoenholz, Maithra Raghu, Martin Wattenberg, Ian J. Goodfellow:
Adversarial Spheres. CoRR abs/1801.02774 (2018) - 2017
- [i1]Fartash Faghri, David J. Fleet, Jamie Ryan Kiros, Sanja Fidler:
VSE++: Improved Visual-Semantic Embeddings. CoRR abs/1707.05612 (2017) - 2016
- [c1]Sara Sabour, Yanshuai Cao, Fartash Faghri, David J. Fleet:
Adversarial Manipulation of Deep Representations. ICLR (Poster) 2016 - 2012
- [j1]Nima Pourdamghani, Hamid R. Rabiee, Fartash Faghri, Mohammad Hossein Rohban:
Graph based semi-supervised human pose estimation: When the output space comes to help. Pattern Recognit. Lett. 33(12): 1529-1535 (2012)
Coauthor Index
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last updated on 2023-03-22 03:08 CET by the dblp team
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