Cong Leng

Model Compression and Hardware Acceleration for Neural Networks: A Comprehensive Survey

A Comprehensive Survey of Graph Embedding: Problems, Techniques, and Applications

Large-Scale Multi-View Subspace Clustering in Linear Time

Dimensionality reduction on Anchorgraph with an efficient Locality Preserving Projection

Scalable Semi-Supervised Learning by Efficient Anchor Graph Regularization

Extremely Low Bit Neural Network: Squeeze the Last Bit Out With ADMM

Quantized CNN: A Unified Approach to Accelerate and Compress Convolutional Networks

Semi-supervised multi-graph hashing for scalable similarity search