Random Bias Initialization Improving Binary Neural Network Training. - Xinlin Li 001; Vahid Partovi Nia (CoRR, 2019)

Importance of Data Loading Pipeline in Training Deep Neural Networks. - Mahdi Zolnouri; Xinlin Li 001; Vahid Partovi Nia (CoRR, 2020)

Clustering Causal Additive Noise Models. - Vahid Partovi Nia; Xinlin Li 001; Masoud Asgharian; Shoubo Hu; Zhitang Chen; Yanhui Geng (CoRR, 2020)

Tensor train decompositions on recurrent networks. - Alejandro Murua; Ramchalam Ramakrishnan; Xinlin Li 001; Rui Heng Yang; Vahid Partovi Nia (CoRR, 2020)

S$^3$: Sign-Sparse-Shift Reparametrization for Effective Training of Low-bit Shift Networks. - Xinlin Li 001; Bang Liu; Yaoliang Yu; Wulong Liu; Chunjing Xu; Vahid Partovi Nia (NeurIPS, 2021)

S3: Sign-Sparse-Shift Reparametrization for Effective Training of Low-bit Shift Networks. - Xinlin Li 001; Bang Liu; Yaoliang Yu; Wulong Liu; Chunjing Xu; Vahid Partovi Nia (CoRR, 2021)

EuclidNets: Combining Hardware and Architecture Design for Efficient Training and Inference. - Mariana Oliveira Prazeres; Xinlin Li 001; Adam M. Oberman; Vahid Partovi Nia (ICPRAM, 2022)

Low-bit Shift Network for End-to-End Spoken Language Understanding. - Anderson R. Avila; Khalil Bibi; Rui Heng Yang; Xinlin Li 001; Chao Xing; Xiao Chen (INTERSPEECH, 2022)

DenseShift: Towards Accurate and Transferable Low-Bit Shift Network. - Xinlin Li 001; Bang Liu; Rui Heng Yang; Vanessa Courville; Chao Xing; Vahid Partovi Nia (CoRR, 2022)

BinaryViT: Pushing Binary Vision Transformers Towards Convolutional Models. - Phuoc-Hoan Charles Le; Xinlin Li 001 (CVPR Workshops, 2023)

DenseShift : Towards Accurate and Efficient Low-Bit Power-of-Two Quantization. - Xinlin Li 001; Bang Liu; Rui Heng Yang; Vanessa Courville; Chao Xing; Vahid Partovi Nia (ICCV, 2023)

Understanding Neural Network Binarization with Forward and Backward Proximal Quantizers. - Yiwei Lu 001; Yaoliang Yu; Xinlin Li 001; Vahid Partovi Nia (NeurIPS, 2023)

Mathematical Challenges in Deep Learning. - Vahid Partovi Nia; Guojun Zhang; Ivan Kobyzev; Michael R. Metel; Xinlin Li 001; Ke Sun 013; Sobhan Hemati; Masoud Asgharian; Linglong Kong; Wulong Liu; Boxing Chen (CoRR, 2023)

EuclidNets: An Alternative Operation for Efficient Inference of Deep Learning Models. - Xinlin Li 001; Mariana Parazeres; Adam Oberman; Alireza Ghaffari; Masoud Asgharian; Vahid Partovi Nia (SN Comput. Sci., 2023)

Deep Neural Networks Pruning via the Structured Perspective Regularization. - Matteo Cacciola; Antonio Frangioni; Xinlin Li 001; Andrea Lodi 001 (SIAM J. Math. Data Sci., 2023)