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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 21:30 CEST by the dblp team
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