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2020 – today
- 2024
[j5]Mohammadreza Salehi, Mehrdad Farajtabar, Maxwell Horton, Fartash Faghri, Hadi Pouransari, Raviteja Vemulapalli, Oncel Tuzel, Ali Farhadi, Mohammad Rastegari, Sachin Mehta:
CLIP meets Model Zoo Experts: Pseudo-Supervision for Visual Enhancement. Trans. Mach. Learn. Res. 2024 (2024)- [c12]Haoxiang Wang, Pavan Kumar Anasosalu Vasu, Fartash Faghri, Raviteja Vemulapalli, Mehrdad Farajtabar, Sachin Mehta, Mohammad Rastegari, Oncel Tuzel, Hadi Pouransari:
SAM-CLIP: Merging Vision Foundation Models towards Semantic and Spatial Understanding. CVPR Workshops 2024: 3635-3647 - [c11]Pavan Kumar Anasosalu Vasu, Hadi Pouransari, Fartash Faghri, Raviteja Vemulapalli, Oncel Tuzel:
MobileCLIP: Fast Image-Text Models through Multi-Modal Reinforced Training. CVPR 2024: 15963-15974 - [c10]Jessica Maria Echterhoff, Fartash Faghri, Raviteja Vemulapalli, Ting-Yao Hu, Chun-Liang Li, Oncel Tuzel, Hadi Pouransari:
MUSCLE: A Model Update Strategy for Compatible LLM Evolution. EMNLP (Findings) 2024: 7320-7332 - [c9]Saurabh Garg, Mehrdad Farajtabar, Hadi Pouransari, Raviteja Vemulapalli, Sachin Mehta, Oncel Tuzel, Vaishaal Shankar, Fartash Faghri:
TiC-CLIP: Continual Training of CLIP Models. ICLR 2024 - [c8]Raviteja Vemulapalli, Hadi Pouransari, Fartash Faghri, Sachin Mehta, Mehrdad Farajtabar, Mohammad Rastegari, Oncel Tuzel:
Knowledge Transfer from Vision Foundation Models for Efficient Training of Small Task-specific Models. ICML 2024 - [c7]Jeffrey Li, Alex Fang, Georgios Smyrnis, Maor Ivgi, Matt Jordan, Samir Yitzhak Gadre, Hritik Bansal, Etash Guha, Sedrick Scott Keh, Kushal Arora, Saurabh Garg, Rui Xin, Niklas Muennighoff, Reinhard Heckel, Jean Mercat, Mayee F. Chen, Suchin Gururangan, Mitchell Wortsman, Alon Albalak, Yonatan Bitton, Marianna Nezhurina, Amro Abbas, Cheng-Yu Hsieh, Dhruba Ghosh, Josh Gardner, Maciej Kilian, Hanlin Zhang, Rulin Shao, Sarah M. Pratt, Sunny Sanyal, Gabriel Ilharco, Giannis Daras, Kalyani Marathe, Aaron Gokaslan, Jieyu Zhang, Khyathi Raghavi Chandu, Thao Nguyen, Igor Vasiljevic, Sham M. Kakade, Shuran Song, Sujay Sanghavi, Fartash Faghri, Sewoong Oh, Luke Zettlemoyer, Kyle Lo, Alaaeldin El-Nouby, Hadi Pouransari, Alexander Toshev, Stephanie Wang, Dirk Groeneveld, Luca Soldaini, Pang Wei Koh, Jenia Jitsev, Thomas Kollar, Alex Dimakis, Yair Carmon, Achal Dave, Ludwig Schmidt, Vaishaal Shankar:
DataComp-LM: In search of the next generation of training sets for language models. NeurIPS 2024 - [c6]Hadi Pouransari, Chun-Liang Li, Jen-Hao Rick Chang, Pavan Kumar Anasosalu Vasu, Cem Koc, Vaishaal Shankar, Oncel Tuzel:
Dataset Decomposition: Faster LLM Training with Variable Sequence Length Curriculum. NeurIPS 2024 - [i23]Pavan Kumar Anasosalu Vasu, Hadi Pouransari, Fartash Faghri, Oncel Tuzel:
CLIP with Quality Captions: A Strong Pretraining for Vision Tasks. CoRR abs/2405.08911 (2024) - [i22]Hadi Pouransari, Chun-Liang Li, Jen-Hao Rick Chang, Pavan Kumar Anasosalu Vasu, Cem Koc, Vaishaal Shankar, Oncel Tuzel:
Dataset Decomposition: Faster LLM Training with Variable Sequence Length Curriculum. CoRR abs/2405.13226 (2024) - [i21]Jeffrey Li, Alex Fang, Georgios Smyrnis, Maor Ivgi, Matt Jordan, Samir Yitzhak Gadre, Hritik Bansal, Etash Kumar Guha, Sedrick Keh, Kushal Arora, Saurabh Garg, Rui Xin, Niklas Muennighoff, Reinhard Heckel, Jean Mercat, Mayee F. Chen, Suchin Gururangan, Mitchell Wortsman, Alon Albalak, Yonatan Bitton, Marianna Nezhurina, Amro Abbas, Cheng-Yu Hsieh, Dhruba Ghosh, Josh Gardner, Maciej Kilian, Hanlin Zhang, Rulin Shao, Sarah M. Pratt, Sunny Sanyal, Gabriel Ilharco, Giannis Daras, Kalyani Marathe, Aaron Gokaslan, Jieyu Zhang, Khyathi Raghavi Chandu, Thao Nguyen, Igor Vasiljevic, Sham M. Kakade, Shuran Song, Sujay Sanghavi, Fartash Faghri, Sewoong Oh, Luke Zettlemoyer, Kyle Lo, Alaaeldin El-Nouby, Hadi Pouransari, Alexander Toshev, Stephanie Wang, Dirk Groeneveld, Luca Soldaini, Pang Wei Koh, Jenia Jitsev, Thomas Kollar, Alexandros G. Dimakis, Yair Carmon, Achal Dave, Ludwig Schmidt, Vaishaal Shankar:
DataComp-LM: In search of the next generation of training sets for language models. CoRR abs/2406.11794 (2024) - [i20]Jessica Maria Echterhoff, Fartash Faghri, Raviteja Vemulapalli, Ting-Yao Hu, Chun-Liang Li, Oncel Tuzel, Hadi Pouransari:
MUSCLE: A Model Update Strategy for Compatible LLM Evolution. CoRR abs/2407.09435 (2024) - [i19]Ran Liu, Wenrui Ma, Ellen L. Zippi, Hadi Pouransari, Jingyun Xiao, Christopher M. Sandino, Behrooz Mahasseni, Juri Minxha, Erdrin Azemi, Eva L. Dyer, Ali Moin:
Generalizable autoregressive modeling of time series through functional narratives. CoRR abs/2410.08421 (2024) - [i18]Ching Fang, Christopher M. Sandino, Behrooz Mahasseni, Juri Minxha, Hadi Pouransari, Erdrin Azemi, Ali Moin, Ellen L. Zippi:
Promoting cross-modal representations to improve multimodal foundation models for physiological signals. CoRR abs/2410.16424 (2024) - [i17]Pavan Kumar Anasosalu Vasu, Fartash Faghri, Chun-Liang Li, Cem Koc, Nate True, Albert Antony, Gokul Santhanam, James Gabriel, Peter Grasch, Oncel Tuzel, Hadi Pouransari:
FastVLM: Efficient Vision Encoding for Vision Language Models. CoRR abs/2412.13303 (2024) - 2023
- [c5]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. ICCV 2023: 16986-16997 - [c4]Florian Jaeckle, Fartash Faghri, Ali Farhadi, Oncel Tuzel, Hadi Pouransari:
FastFill: Efficient Compatible Model Update. ICLR 2023 - [i16]Florian Jaeckle, Fartash Faghri, Ali Farhadi, Oncel Tuzel, Hadi Pouransari:
FastFill: Efficient Compatible Model Update. CoRR abs/2303.04766 (2023) - [i15]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) - [i14]Ran Liu, Ellen L. Zippi, Hadi Pouransari, Christopher M. Sandino, Jingping Nie, Hanlin Goh, Erdrin Azemi, Ali Moin:
Frequency-Aware Masked Autoencoders for Multimodal Pretraining on Biosignals. CoRR abs/2309.05927 (2023) - [i13]Mohammadreza Salehi, Mehrdad Farajtabar, Maxwell Horton, Fartash Faghri, Hadi Pouransari, Raviteja Vemulapalli, Oncel Tuzel, Ali Farhadi, Mohammad Rastegari, Sachin Mehta:
CLIP meets Model Zoo Experts: Pseudo-Supervision for Visual Enhancement. CoRR abs/2310.14108 (2023) - [i12]Haoxiang Wang, Pavan Kumar Anasosalu Vasu, Fartash Faghri, Raviteja Vemulapalli, Mehrdad Farajtabar, Sachin Mehta, Mohammad Rastegari, Oncel Tuzel, Hadi Pouransari:
SAM-CLIP: Merging Vision Foundation Models towards Semantic and Spatial Understanding. CoRR abs/2310.15308 (2023) - [i11]Saurabh Garg, Mehrdad Farajtabar, Hadi Pouransari, Raviteja Vemulapalli, Sachin Mehta, Oncel Tuzel, Vaishaal Shankar, Fartash Faghri:
TiC-CLIP: Continual Training of CLIP Models. CoRR abs/2310.16226 (2023) - [i10]Pavan Kumar Anasosalu Vasu, Hadi Pouransari, Fartash Faghri, Raviteja Vemulapalli, Oncel Tuzel:
MobileCLIP: Fast Image-Text Models through Multi-Modal Reinforced Training. CoRR abs/2311.17049 (2023) - [i9]Raviteja Vemulapalli, Hadi Pouransari, Fartash Faghri, Sachin Mehta, Mehrdad Farajtabar, Mohammad Rastegari, Oncel Tuzel:
Label-efficient Training of Small Task-specific Models by Leveraging Vision Foundation Models. CoRR abs/2311.18237 (2023) - 2022
- [c3]Vivek Ramanujan, Pavan Kumar Anasosalu Vasu, Ali Farhadi, Oncel Tuzel, Hadi Pouransari:
Forward Compatible Training for Large-Scale Embedding Retrieval Systems. CVPR 2022: 19364-19373 - [i8]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) - 2021
- [c2]Hadi Pouransari, Mojan Javaheripi, Vinay Sharma, Oncel Tuzel:
Extracurricular Learning: Knowledge Transfer Beyond Empirical Distribution. CVPR Workshops 2021: 3032-3042 - [i7]Vivek Ramanujan, Pavan Kumar Anasosalu Vasu, Ali Farhadi, Oncel Tuzel, Hadi Pouransari:
Forward Compatible Training for Representation Learning. CoRR abs/2112.02805 (2021) - 2020
- [c1]Hadi Pouransari, Zhucheng Tu, Oncel Tuzel:
Least squares binary quantization of neural networks. CVPR Workshops 2020: 2986-2996 - [i6]Hadi Pouransari, Oncel Tuzel:
Least squares binary quantization of neural networks. CoRR abs/2001.02786 (2020) - [i5]Hadi Pouransari, Oncel Tuzel:
Extracurricular Learning: Knowledge Transfer Beyond Empirical Distribution. CoRR abs/2007.00051 (2020)
2010 – 2019
- 2018
- [j4]Chao Chen
, Hadi Pouransari, Sivasankaran Rajamanickam, Erik G. Boman, Eric Darve:
A distributed-memory hierarchical solver for general sparse linear systems. Parallel Comput. 74: 49-64 (2018) - [i4]Minghuang Ma, Hadi Pouransari, Daniel Chao, Saurabh Adya, Santiago Akle Serrano, Yi Qin, Dan Gimnicher, Dominic Walsh:
Democratizing Production-Scale Distributed Deep Learning. CoRR abs/1811.00143 (2018) - 2017
- [j3]Pieter Coulier, Hadi Pouransari, Eric Darve:
The Inverse Fast Multipole Method: Using a Fast Approximate Direct Solver as a Preconditioner for Dense Linear Systems. SIAM J. Sci. Comput. 39(3) (2017) - [j2]Hadi Pouransari, Pieter Coulier, Eric Darve:
Fast Hierarchical Solvers For Sparse Matrices Using Extended Sparsification and Low-Rank Approximation. SIAM J. Sci. Comput. 39(3) (2017) - [i3]Chao Chen, Hadi Pouransari, Sivasankaran Rajamanickam, Erik G. Boman, Eric Darve:
A distributed-memory hierarchical solver for general sparse linear systems. CoRR abs/1712.07297 (2017) - 2015
- [j1]Hadi Pouransari, Eric Darve:
Optimizing the Adaptive Fast Multipole Method for Fractal Sets. SIAM J. Sci. Comput. 37(2) (2015) - [i2]Pieter Coulier, Hadi Pouransari, Eric Darve:
The inverse fast multipole method: using a fast approximate direct solver as a preconditioner for dense linear systems. CoRR abs/1508.01835 (2015) - [i1]Hadi Pouransari, Pieter Coulier, Eric Darve:
Fast hierarchical solvers for sparse matrices. CoRR abs/1510.07363 (2015)
Coauthor Index
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