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Vahid Partovi Nia
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2020 – today
- 2024
- [c23]Alireza Ghaffari, Justin Yu, Mahsa Ghazvini Nejad, Masoud Asgharian, Boxing Chen, Vahid Partovi Nia:
Mitigating Outlier Activations in Low-Precision Fine-Tuning of Language Models. ICPRAM 2024: 478-484 - [i37]Yiwei Lu, Yaoliang Yu, Xinlin Li, Vahid Partovi Nia:
Understanding Neural Network Binarization with Forward and Backward Proximal Quantizers. CoRR abs/2402.17710 (2024) - [i36]Alireza Ghaffari, Sharareh Younesian, Vahid Partovi Nia, Boxing Chen, Masoud Asgharian:
AdpQ: A Zero-shot Calibration Free Adaptive Post Training Quantization Method for LLMs. CoRR abs/2405.13358 (2024) - [i35]Ali Edalati, Alireza Ghaffari, Masoud Asgharian, Lu Hou, Boxing Chen, Vahid Partovi Nia:
OAC: Output-adaptive Calibration for Accurate Post-training Quantization. CoRR abs/2405.15025 (2024) - 2023
- [j5]Vahid Partovi Nia
, Eyyüb Sari, Vanessa Courville, Masoud Asgharian:
Training Integer-Only Deep Recurrent Neural Networks. SN Comput. Sci. 4(5): 501 (2023) - [j4]Xinlin Li, Mariana Parazeres, Adam Oberman, Alireza Ghaffari, Masoud Asgharian, Vahid Partovi Nia
:
EuclidNets: An Alternative Operation for Efficient Inference of Deep Learning Models. SN Comput. Sci. 4(5): 507 (2023) - [c22]Ali Mosleh, Marzieh S. Tahaei, James J. Clark, Vahid Partovi Nia:
Towards Low-Cost Learning-based Camera ISP via Unrolled Optimization. CRV 2023: 9-18 - [c21]Mohammadreza Tayaranian, Alireza Ghaffari, Marzieh S. Tahaei, Mehdi Rezagholizadeh, Masoud Asgharian, Vahid Partovi Nia:
Towards Fine-tuning Pre-trained Language Models with Integer Forward and Backward Propagation. EACL (Findings) 2023: 1867-1876 - [c20]Xinlin Li, Bang Liu, Rui Heng Yang, Vanessa Courville, Chao Xing, Vahid Partovi Nia:
DenseShift : Towards Accurate and Efficient Low-Bit Power-of-Two Quantization. ICCV 2023: 16964-16974 - [c19]Matteo Cacciola, Antonio Frangioni, Masoud Asgharian, Alireza Ghaffari, Vahid Partovi Nia:
On the Convergence of Stochastic Gradient Descent in Low-Precision Number Formats. ICPRAM 2023: 542-549 - [c18]Yiwei Lu, Yaoliang Yu, Xinlin Li, Vahid Partovi Nia:
Understanding Neural Network Binarization with Forward and Backward Proximal Quantizers. NeurIPS 2023 - [i34]Matteo Cacciola, Antonio Frangioni, Masoud Asgharian, Alireza Ghaffari, Vahid Partovi Nia:
On the Convergence of Stochastic Gradient Descent in Low-precision Number Formats. CoRR abs/2301.01651 (2023) - [i33]Dounia Lakhmiri, Mahdi Zolnouri, Vahid Partovi Nia, Christophe Tribes, Sébastien Le Digabel:
Scaling Deep Networks with the Mesh Adaptive Direct Search algorithm. CoRR abs/2301.06641 (2023) - [i32]Vahid Partovi Nia, Guojun Zhang, Ivan Kobyzev, Michael R. Metel, Xinlin Li, Ke Sun, Sobhan Hemati, Masoud Asgharian, Linglong Kong, Wulong Liu, Boxing Chen:
Mathematical Challenges in Deep Learning. CoRR abs/2303.15464 (2023) - [i31]Alireza Ghaffari, Justin Yu, Mahsa Ghazvini Nejad, Masoud Asgharian, Boxing Chen, Vahid Partovi Nia:
Mitigating Outlier Activations in Low-Precision Fine-Tuning of Language Models. CoRR abs/2312.09211 (2023) - 2022
- [c17]Marawan Gamal Abdel Hameed, Marzieh S. Tahaei, Ali Mosleh, Vahid Partovi Nia:
Convolutional Neural Network Compression through Generalized Kronecker Product Decomposition. AAAI 2022: 771-779 - [c16]Ali Edalati, Marzieh S. Tahaei, Ahmad Rashid, Vahid Partovi Nia, James J. Clark, Mehdi Rezagholizadeh:
Kronecker Decomposition for GPT Compression. ACL (2) 2022: 219-226 - [c15]Eyyüb Sari, Vanessa Courville, Vahid Partovi Nia:
iRNN: Integer-only Recurrent Neural Network. ICPRAM 2022: 110-121 - [c14]Mariana Oliveira Prazeres, Xinlin Li, Adam M. Oberman, Vahid Partovi Nia:
EuclidNets: Combining Hardware and Architecture Design for Efficient Training and Inference. ICPRAM 2022: 141-151 - [c13]Marzieh S. Tahaei, Ella Charlaix, Vahid Partovi Nia, Ali Ghodsi, Mehdi Rezagholizadeh:
KroneckerBERT: Significant Compression of Pre-trained Language Models Through Kronecker Decomposition and Knowledge Distillation. NAACL-HLT 2022: 2116-2127 - [c12]Alireza Ghaffari, Marzieh S. Tahaei, Mohammadreza Tayaranian, Masoud Asgharian, Vahid Partovi Nia:
Is Integer Arithmetic Enough for Deep Learning Training? NeurIPS 2022 - [i30]Vahid Partovi Nia, Alireza Ghaffari, Mahdi Zolnouri, Yvon Savaria:
Rethinking Pareto Frontier for Performance Evaluation of Deep Neural Networks. CoRR abs/2202.09275 (2022) - [i29]Alireza Ghaffari, Marzieh S. Tahaei, Mohammadreza Tayaranian, Masoud Asgharian, Vahid Partovi Nia:
Is Integer Arithmetic Enough for Deep Learning Training? CoRR abs/2207.08822 (2022) - [i28]Xinlin Li, Bang Liu, Rui Heng Yang, Vanessa Courville, Chao Xing, Vahid Partovi Nia:
DenseShift: Towards Accurate and Transferable Low-Bit Shift Network. CoRR abs/2208.09708 (2022) - [i27]Mohammadreza Tayaranian, Alireza Ghaffari, Marzieh S. Tahaei, Mehdi Rezagholizadeh, Masoud Asgharian, Vahid Partovi Nia:
Integer Fine-tuning of Transformer-based Models. CoRR abs/2209.09815 (2022) - [i26]Marawan Gamal Abdel Hameed, Ali Mosleh, Marzieh S. Tahaei, Vahid Partovi Nia:
SeKron: A Decomposition Method Supporting Many Factorization Structures. CoRR abs/2210.06299 (2022) - [i25]Ali Edalati, Marzieh S. Tahaei, Ivan Kobyzev, Vahid Partovi Nia, James J. Clark, Mehdi Rezagholizadeh:
KronA: Parameter Efficient Tuning with Kronecker Adapter. CoRR abs/2212.10650 (2022) - [i24]Vahid Partovi Nia, Eyyüb Sari, Vanessa Courville, Masoud Asgharian:
Training Integer-Only Deep Recurrent Neural Networks. CoRR abs/2212.11791 (2022) - [i23]Xinlin Li, Mariana Parazeres, Adam M. Oberman, Alireza Ghaffari, Masoud Asgharian, Vahid Partovi Nia:
EuclidNets: An Alternative Operation for Efficient Inference of Deep Learning Models. CoRR abs/2212.11803 (2022) - 2021
- [j3]Shaima Tilouche, Vahid Partovi Nia
, Samuel Bassetto:
Parallel coordinate order for high-dimensional data. Stat. Anal. Data Min. 14(5): 501-515 (2021) - [c11]Ryan Razani, Grégoire Morin, Eyyüb Sari, Vahid Partovi Nia:
Adaptive Binary-Ternary Quantization. CVPR Workshops 2021: 4613-4618 - [c10]Tim Dockhorn, Yaoliang Yu, Eyyüb Sari, Mahdi Zolnouri, Vahid Partovi Nia:
Demystifying and Generalizing BinaryConnect. NeurIPS 2021: 13202-13216 - [c9]Xinlin Li, Bang Liu, Yaoliang Yu, Wulong Liu, Chunjing Xu, Vahid Partovi Nia:
S$^3$: Sign-Sparse-Shift Reparametrization for Effective Training of Low-bit Shift Networks. NeurIPS 2021: 14555-14566 - [i22]Mouloud Belbahri, Olivier Gandouet, Alejandro Murua, Vahid Partovi Nia:
A Twin Neural Model for Uplift. CoRR abs/2105.05146 (2021) - [i21]Xinlin Li, Bang Liu, Yaoliang Yu, Wulong Liu, Chunjing Xu, Vahid Partovi Nia:
S3: Sign-Sparse-Shift Reparametrization for Effective Training of Low-bit Shift Networks. CoRR abs/2107.03453 (2021) - [i20]Marzieh S. Tahaei, Ella Charlaix, Vahid Partovi Nia, Ali Ghodsi, Mehdi Rezagholizadeh:
KroneckerBERT: Learning Kronecker Decomposition for Pre-trained Language Models via Knowledge Distillation. CoRR abs/2109.06243 (2021) - [i19]Eyyüb Sari, Vanessa Courville, Vahid Partovi Nia:
iRNN: Integer-only Recurrent Neural Network. CoRR abs/2109.09828 (2021) - [i18]Marawan Gamal Abdel Hameed, Marzieh S. Tahaei, Ali Mosleh, Vahid Partovi Nia:
Convolutional Neural Network Compression through Generalized Kronecker Product Decomposition. CoRR abs/2109.14710 (2021) - [i17]Ali Edalati, Marzieh S. Tahaei, Ahmad Rashid, Vahid Partovi Nia, James J. Clark, Mehdi Rezagholizadeh:
Kronecker Decomposition for GPT Compression. CoRR abs/2110.08152 (2021) - [i16]Tim Dockhorn, Yaoliang Yu, Eyyüb Sari, Mahdi Zolnouri, Vahid Partovi Nia:
Demystifying and Generalizing BinaryConnect. CoRR abs/2110.13220 (2021) - 2020
- [c8]Ramchalam Kinattinkara Ramakrishnan, Eyyüb Sari, Vahid Partovi Nia:
Differentiable Mask for Pruning Convolutional and Recurrent Networks. CRV 2020: 222-229 - [c7]Farnoush Farhadi, Vahid Partovi Nia, Andrea Lodi:
Activation Adaptation in Neural Networks. ICPRAM 2020: 249-257 - [i15]Eyyüb Sari, Vahid Partovi Nia:
Batch Normalization in Quantized Networks. CoRR abs/2004.14214 (2020) - [i14]Mahdi Zolnouri, Xinlin Li, Vahid Partovi Nia:
Importance of Data Loading Pipeline in Training Deep Neural Networks. CoRR abs/2005.02130 (2020) - [i13]Vahid Partovi Nia, Xinlin Li, Masoud Asgharian, Shoubo Hu, Zhitang Chen, Yanhui Geng:
Clustering Causal Additive Noise Models. CoRR abs/2006.04877 (2020) - [i12]Alejandro Murua, Ramchalam Ramakrishnan, Xinlin Li, Rui Heng Yang, Vahid Partovi Nia:
Tensor train decompositions on recurrent networks. CoRR abs/2006.05442 (2020)
2010 – 2019
- 2019
- [j2]Mohammad Sajjad Ghaemi, Daniel B. DiGiulio, Kévin Contrepois, Benjamin J. Callahan
, Thuy T. M. Ngo, Brittany Lee-McMullen, Benoit Lehallier, Anna Robaczewska, David Mcilwain, Yael Rosenberg-Hasson, Ronald J. Wong, Cecele Quaintance, Anthony Culos, Natalie Stanley, Athena Tanada, Amy Tsai
, Dyani Gaudilliere
, Edward Ganio, Xiaoyuan Han, Kazuo Ando
, Leslie McNeil, Martha Tingle, Paul H. Wise, Ivana Maric, Marina Sirota, Tony Wyss-Coray
, Virginia D. Winn
, Maurice L. Druzin
, Ronald Gibbs, Gary L. Darmstadt
, David B. Lewis, Vahid Partovi Nia
, Bruno Agard
, Robert Tibshirani, Garry P. Nolan, Michael P. Snyder
, David A. Relman, Stephen R. Quake, Gary M. Shaw
, David K. Stevenson, Martin S. Angst, Brice Gaudilliere, Nima Aghaeepour:
Multiomics modeling of the immunome, transcriptome, microbiome, proteome and metabolome adaptations during human pregnancy. Bioinform. 35(1): 95-103 (2019) - [c6]Ali Vahdat, Mouloud Belbahri, Vahid Partovi Nia:
Active Learning for High-Dimensional Binary Features. CNSM 2019: 1-4 - [c5]Mouloud Belbahri, Eyyüb Sari, Sajad Darabi, Vahid Partovi Nia
:
Foothill: A Quasiconvex Regularization for Edge Computing of Deep Neural Networks. ICIAR (2) 2019: 3-14 - [c4]Ramchalam Kinattinkara Ramakrishnan, Shangling Jui, Vahid Partovi Nia
:
Deep Demosaicing for Edge Implementation. ICIAR (1) 2019: 275-286 - [i11]Mouloud Belbahri, Eyyüb Sari, Sajad Darabi, Vahid Partovi Nia:
Foothill: A Quasiconvex Regularization Function. CoRR abs/1901.06414 (2019) - [i10]Farnoush Farhadi, Vahid Partovi Nia, Andrea Lodi:
Activation Adaptation in Neural Networks. CoRR abs/1901.09849 (2019) - [i9]Ali Vahdat, Mouloud Belbahri, Vahid Partovi Nia:
Active Learning for High-Dimensional Binary Features. CoRR abs/1902.01923 (2019) - [i8]Ramchalam Kinattinkara Ramakrishnan, Shangling Jui, Vahid Partovi Nia:
Deep Demosaicing for Edge Implementation. CoRR abs/1904.00775 (2019) - [i7]Shaima Tilouche, Vahid Partovi Nia, Samuel Bassetto:
Parallel Coordinate Order for High-Dimensional Data. CoRR abs/1905.10035 (2019) - [i6]Ramchalam Kinattinkara Ramakrishnan, Eyyüb Sari, Vahid Partovi Nia:
Differentiable Mask Pruning for Neural Networks. CoRR abs/1909.04567 (2019) - [i5]Eyyüb Sari, Mouloud Belbahri, Vahid Partovi Nia:
A Study on Binary Neural Networks Initialization. CoRR abs/1909.09139 (2019) - [i4]Grégoire Morin, Ryan Razani, Vahid Partovi Nia, Eyyüb Sari:
Smart Ternary Quantization. CoRR abs/1909.12205 (2019) - [i3]Xinlin Li, Vahid Partovi Nia:
Random Bias Initialization Improving Binary Neural Network Training. CoRR abs/1909.13446 (2019) - 2018
- [c3]Shoubo Hu, Zhitang Chen, Vahid Partovi Nia, Lai-Wan Chan, Yanhui Geng:
Causal Inference and Mechanism Clustering of A Mixture of Additive Noise Models. NeurIPS 2018: 5212-5222 - [i2]Shoubo Hu, Zhitang Chen, Vahid Partovi Nia, Laiwan Chan, Yanhui Geng:
Causal Inference and Mechanism Clustering of a Mixture of Additive Noise Models. CoRR abs/1809.08568 (2018) - [i1]Sajad Darabi, Mouloud Belbahri, Matthieu Courbariaux, Vahid Partovi Nia:
BNN+: Improved Binary Network Training. CoRR abs/1812.11800 (2018) - 2016
- [j1]Amir-Hosein Homaie-Shandizi, Vahid Partovi Nia, Michel Gamache
, Bruno Agard
:
Flight deck crew reserve: From data to forecasting. Eng. Appl. Artif. Intell. 50: 106-114 (2016) - [c2]Mina Mirshahi, Vahid Partovi Nia
, Luc Adjengue:
An Online Data Validation Algorithm for Electronic Nose. ICPRAM (Revised Selected Papers) 2016: 104-120 - [c1]Mina Mirshahi, Vahid Partovi Nia, Luc Adjengue:
Statistical Measurement Validation with Application to Electronic Nose Technology. ICPRAM 2016: 407-414
Coauthor Index
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last updated on 2024-06-20 20:42 CEST by the dblp team
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