Tensor decomposition on big data has attracted significant attention recently. Among the most popular methods is a class of algorithms that leverages compression in order to reduce the size of the tensor and potentially parallelize computations. A fundamental requirement for such methods to work properly is that the low-rank tensor structure is retained upon compression. In lieu of efficient and realistic means of computing and studying the effects of compression on the low rank of a tensor, we study the effects of compression on the core consistency; a widely used heuristic that has been used as a proxy for estimating that low rank. We provide theoretical analysis, where we identify sufficient conditions for the compression such that the core consistency is preserved, and we conduct extensive experiments that validate our analysis. Further, we explore popular compression schemes and how they affect the core consistency.
Quantum Compressed Sensing with Unsupervised Tensor-Network Machine Learning
Capital Normal University（首都师范大学）；University of Chinese Academy of Sciences（中国科学院大学）；Max-Planck-Institute for Mathematics in the Sciences（马克斯·普朗克数学科学研究所）；Kavli Institute for Theoretical Sciences（卡弗里理论科学研究所）；CAS Center for Excellence in Topological Quantum Computation（中国科学院拓扑量子计算卓越创新中心）；ICFO-Institut de Ciencies Fotoniques（光子科学研究所）；The Barcelona Institute of Science and Technology（巴塞罗那科学技术研究所）；ICREA（加泰罗尼亚高等研究院）
HOTCAKE: Higher Order Tucker Articulated Kernels for Deeper CNN Compression
Institute for Clarity in Documentation（清晰度文献研究所）；Inria Paris-Rocquencourt（法国国家信息与自动化研究所巴黎-罗康库尔中心）；Rajiv Gandhi University（拉吉夫·甘地大学）；Tsinghua University（清华大学）；Palmer Research Laboratories（帕尔默研究实验室）
Ultra Memory-Efficient On-FPGA Training of Transformers via Tensor-Compressed Optimization
Department of Electrical and Computer Engineering, University of California, Santa Barbara（加州大学圣芭芭拉分校电子与计算机工程系）；Intel Corporation（英特尔公司）；Department of Computer Science, North Carolina State University（北卡罗来纳州立大学计算机科学系）；School of Electrical and Computer Engineering, Georgia Institute of Technology（佐治亚理工学院电气与计算机工程学院）
