In real-world applications, clustering or classification can usually be improved by fusing information from different views. Therefore, unsupervised representation learning on multi-view data becomes a compelling topic in machine learning. this paper, we propose novel and flexible model termed Collaborative Multi-View Information Bottleneck Networks (CMIB-Nets), which comprehensively explores t...

Abstract With the development of computer vision technology, demand for deploying inspection tasks on edge mobile devices is becoming increasingly widespread. To meet requirements application scenarios with limited computational resources, many lightweight models have been proposed that achieves good performance fewer parameters. In order to achieve higher model accuracy parameters, a novel con...

Applications that generate bursty I/O load, like checkpointing, require additional support to perform efficiently on next generation petascale supercomputers. Tens of thousands of processors, generating terabytes of snapshot data at once at each timestep, can easily overwhelm a storage system. Further, even at the current peak I/O bandwidth rates, offered by parallel file system deployments at ...

The availability of high-throughput sequencing has created enormous possibilities for scientific discovery. However, the massive amount of data being generated has resulted in a severe informatics bottleneck. A large number of tools exist for analyzing next-generation sequencing (NGS) data, yet often there remains a disconnect between these research tools and the ability of many researchers to ...

High Level Synthesis tools have reduced accelerator design time. However, a complex scaling problem that remains is the data transfer bottleneck. Accelerators require huge amounts of data and are often limited by interconnect resources. Local buffers can reduce communication by exploiting data reuse, but the data access order has a substantial impact on the amount of reuse that can be utilized....