Siyu Liao - Citegraph

Author Info

Name	Affiliation	Papers
SIYU LIAO	City University of New York, City College	23
Collaborators	Citations	PageRank
59	41	8.73
Referers	Referees	References
184	320	109

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100320

Publications (23 rows)

Collaborators (59 rows)

Referers (100 rows)

Referees (100 rows)

Title	Citations	PageRank	Year
BATUDE: Budget-Aware Neural Network Compression Based on Tucker Decomposition.	0	0.34	2022
Towards Efficient Tensor Decomposition-Based DNN Model Compression with Optimization Framework	1	0.34	2021
GoSPA: An Energy-efficient High-performance Globally Optimized SParse Convolutional Neural Network Accelerator	4	0.38	2021
Doubly Residual Neural Decoder: Towards Low-Complexity High-Performance Channel Decoding	0	0.34	2021
<sc>PermCNN</sc>: Energy-Efficient Convolutional Neural Network Hardware Architecture With Permuted Diagonal Structure	0	0.34	2021
Towards Extremely Compact RNNs for Video Recognition with Fully Decomposed Hierarchical Tucker Structure	0	0.34	2021
Embedding Compression With Isotropic Iterative Quantization	0	0.34	2020
VLSI Hardware Architecture for Gaussian Process	1	0.35	2020
Low-complexity Neural Network-based MIMO Detector using Permuted Diagonal Matrix	0	0.34	2020
Cag: A Real-Time Low-Cost Enhanced-Robustness High-Transferability Content-Aware Adversarial Attack Generator	0	0.34	2020
Structured Neural Network with Low Complexity for MIMO Detection	0	0.34	2019
Compressing Deep Neural Networks Using Toeplitz Matrix: Algorithm Design And Fpga Implementation	0	0.34	2019
CircConv: A Structured Convolution with Low Complexity	0	0.34	2019
CircConv: A Structured Convolution with Low Complexity.	0	0.34	2019
Reduced-Complexity Deep Neural Networks Design Using Multi-Level Compression.	1	0.36	2019
Towards Ultra-High Performance and Energy Efficiency of Deep Learning Systems: An Algorithm-Hardware Co-Optimization Framework.	7	0.55	2018
PermDNN - Efficient Compressed DNN Architecture with Permuted Diagonal Matrices.	8	0.57	2018
Large-scale short-term urban taxi demand forecasting using deep learning.	2	0.38	2018
Energy-efficient, high-performance, highly-compressed deep neural network design using block-circulant matrices.	3	0.39	2017
Towards reliability-aware circuit design in nanoscale FinFET technology: - New-generation aging model and circuit reliability simulator.	1	0.40	2017
Theoretical Properties for Neural Networks with Weight Matrices of Low Displacement Rank.	10	0.55	2017
CirCNN: Accelerating and Compressing Deep Neural Networks Using Block-Circulant Weight Matrices	0	0.34	2017
Fully-Parallel Area-Efficient Deep Neural Network Design Using Stochastic Computing.	3	0.42	2017