498 citations · 1.1k across the 23 of their papers we have counts for
4 papers · 1 filter
CirCNN: Accelerating and Compressing Deep Neural Networks Using Block-CirculantWeight Matrices
Caiwen Ding, Siyu Liao, Yanzhi Wang +13
Large-scale deep neural networks (DNNs) are both compute and memory intensive. As the size of DNNs continues to grow, it is critical to improve the energy efficiency and performanc…
Spectral and Energy Efficiency in Cognitive Radio Systems with Unslotted Primary Users and Sensing Uncertainty
Gozde Ozcan, M. Cenk Gursoy, Jian Tang
This paper studies energy efficiency (EE) and average throughput maximization for cognitive radio systems in the presence of unslotted primary users. It is assumed that primary use…
A Hierarchical Framework of Cloud Resource Allocation and Power Management Using Deep Reinforcement Learning
Ning Liu, Zhe Li, Zhiyuan Xu +5
Automatic decision-making approaches, such as reinforcement learning (RL), have been applied to (partially) solve the resource allocation problem adaptively in the cloud computing…
Theoretical Properties for Neural Networks with Weight Matrices of Low Displacement Rank
Liang Zhao, Siyu Liao, Yanzhi Wang +4
Recently low displacement rank (LDR) matrices, or so-called structured matrices, have been proposed to compress large-scale neural networks. Empirical results have shown that neura…