• Publications
  • Influence
Learning Environmental Sounds with Multi-scale Convolutional Neural Network
TLDR
We propose a novel end-to-end network called WaveMsNet based on the multi-scale convolution operation and two-phase method. Expand
Matrix factorization for recommendation with explicit and implicit feedback
TLDR
We propose a latent factor model based on probabilistic MF, by incorporating implicit feedback as complementary information, which outperforms the baselines. Expand
Security Issues and Solutions in Cloud Computing
TLDR
We intend to discuss security requirements and security issues involving data, application and virtualization in cloud computing as well as current solutions to these issues. Expand
OPTAS: Decentralized flow monitoring and scheduling for tiny tasks
TLDR
We present OPTAS, a lightweight, commodity-switch-compatible scheduling solution that efficiently monitors and schedules flows for tiny tasks with low overhead. Expand
PARIX: Speculative Partial Writes in Erasure-Coded Systems
TLDR
This paper presents PARIX, a speculative partial write scheme for fast parity logging. Expand
Deadline-Oriented Task Scheduling for MapReduce Environments
TLDR
We propose a deadline-oriented task scheduling approach, named Dart, to meet the given deadline and maximize the input size if only part of the dataset can be processed before the time limit. Expand
VMThunder: Fast Provisioning of Large-Scale Virtual Machine Clusters
  • Z. Zhang, Z. Li, +4 authors Xicheng Lu
  • Computer Science
  • IEEE Transactions on Parallel and Distributed…
  • 22 January 2014
TLDR
We address this challenge with VMThunder, a new VM provisioning tool, which downloads data blockson demandduring the VM booting process and speeds up VM image streaming by strategically integrating peer-to-peer (P2P) streaming techniques with enhanced optimization schemes such as transfer on demand, cache on read, snapshot on local, and relay on cache. Expand
Fast Release/Capture Sampling in Large-Scale Sensor Networks
TLDR
We develop a novel protocol FLAKE to efficiently and accurately estimate the global information of large-scale sensor networks based on the sparse sampling theory. Expand
A Cluster Feature Based Approach for QoS Prediction in Web Service Recommendation
TLDR
We propose a Cluster Feature based Latent Factor Model (CFLFM) for QoS prediction. Expand
An Effective Approach for Remote Attestation in Trusted Computing
TLDR
This paper proposes an effective approach for remote attestation in trusted computing from the automated negotiations that an application authenticates itself to a remote party automatically. Expand
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