Siting Liu

According to our database, Siting Liu authored at least 17 papers between 2017 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

ApproxPilot: A GNN-based Accelerator Approximation Framework.

Qing Zhang, Cheng Liu, Siting Liu, Yajuan Hui, Huawei Li, Xiaowei Li

CoRR, 2024

LDL-SCA: Linearized Deep Learning Side-Channel Attack Targeting Multi-tenant FPGAs✱.

Yankun Zhu, Siting Liu, Liyu Yang, Pingqiang Zhou

Proceedings of the Great Lakes Symposium on VLSI 2024, 2024

Can Stochastic Computing Truly Tolerate Bit Flips?

Yutong Wang, Zhaojun Ni, Siting Liu

Proceedings of the Great Lakes Symposium on VLSI 2024, 2024

Compact Powers-of-Two: An Efficient Non-Uniform Quantization for Deep Neural Networks.

Xinkuang Geng, Siting Liu, Jianfei Jiang, Kai Jiang, Honglan Jiang

Proceedings of the Design, Automation & Test in Europe Conference & Exhibition, 2024

2023

An Energy-Efficient Binary-Interfaced Stochastic Multiplier Using Parallel Datapaths.

Yongqiang Zhang, Siting Liu, Jie Han, Zhendong Lin, Shaowei Wang, Xin Cheng, Guangjun Xie

IEEE Trans. Very Large Scale Integr. Syst., September, 2023

Delta Sigma Modulator-Based Dividers for Accurate and Low Latency Stochastic Computing Systems.

Xiaochen Tang, Shanshan Liu, Farzad Niknia, Ziheng Wang, Siting Liu, Pedro Reviriego, Fabrizio Lombardi

IEEE J. Emerg. Sel. Topics Circuits Syst., March, 2023

Feature-Embedding Triplet Networks with a Separately Constrained Loss Function.

Ziheng Wang, Farzad Niknia, Shanshan Liu, Honglan Jiang, Siting Liu, Pedro Reviriego, Fabrizio Lombardi

Proceedings of the IEEE International Symposium on Circuits and Systems, 2023

2022

Fault-Tolerant Deep Learning: A Hierarchical Perspective.

Cheng Liu, Zhen Gao, Siting Liu, Xuefei Ning, Huawei Li, Xiaowei Li

CoRR, 2022

Special Session: Fault-Tolerant Deep Learning: A Hierarchical Perspective.

Cheng Liu, Zhen Gao, Siting Liu, Xuefei Ning, Huawei Li, Xiaowei Li

Proceedings of the 40th IEEE VLSI Test Symposium, 2022

HSB-GDM: a Hybrid Stochastic-Binary Circuit for Gradient Descent with Momentum in the Training of Neural Networks.

Han Li, Heng Shi, Honglan Jiang, Siting Liu

Proceedings of the 17th ACM International Symposium on Nanoscale Architectures, 2022

2021

A Survey of Stochastic Computing Neural Networks for Machine Learning Applications.

Yidong Liu, Siting Liu, Yanzhi Wang, Fabrizio Lombardi, Jie Han

IEEE Trans. Neural Networks Learn. Syst., 2021

2020

Dynamic Stochastic Computing for Digital Signal Processing Applications.

Siting Liu, Jie Han

Proceedings of the 2020 Design, Automation & Test in Europe Conference & Exhibition, 2020

2018

Toward Energy-Efficient Stochastic Circuits Using Parallel Sobol Sequences.

Siting Liu, Jie Han

IEEE Trans. Very Large Scale Integr. Syst., 2018

Gradient Descent Using Stochastic Circuits for Efficient Training of Learning Machines.

Siting Liu, Honglan Jiang, Leibo Liu, Jie Han

IEEE Trans. Comput. Aided Des. Integr. Circuits Syst., 2018

A Stochastic Computational Multi-Layer Perceptron with Backward Propagation.

Yidong Liu, Siting Liu, Yanzhi Wang, Fabrizio Lombardi, Jie Han

IEEE Trans. Computers, 2018

2017

Energy efficient stochastic computing with Sobol sequences.

Siting Liu, Jie Han

Proceedings of the Design, Automation & Test in Europe Conference & Exhibition, 2017

Hardware ODE Solvers using Stochastic Circuits.

Siting Liu, Jie Han

Proceedings of the 54th Annual Design Automation Conference, 2017