62 citations · 537 across the 44 of their papers we have counts for
7 papers · 1 filter
Scalable Algorithms for Tractable Schatten Quasi-Norm Minimization
Fanhua Shang, Yuanyuan Liu, James Cheng
The Schatten-p quasi-norm is usually used to replace the standard nuclear norm in order to approximate the rank function more accurately. However, existing Schatten-p qua…
Unified Scalable Equivalent Formulations for Schatten Quasi-Norms
Fanhua Shang, Yuanyuan Liu, James Cheng
The Schatten quasi-norm can be used to bridge the gap between the nuclear norm and rank function, and is the tighter approximation to matrix rank. However, most existing Schatten q…
Quegel: A General-Purpose Query-Centric Framework for Querying Big Graphs
Da Yan, James Cheng, M. Tamer Özsu +5
Pioneered by Google's Pregel, many distributed systems have been developed for large-scale graph analytics. These systems expose the user-friendly "think like a vertex" programming…
Lightweight Fault Tolerance in Large-Scale Distributed Graph Processing
Da Yan, James Cheng, Fan Yang
The success of Google's Pregel framework in distributed graph processing has inspired a surging interest in developing Pregel-like platforms featuring a user-friendly "think like a…
Efficient Processing of Reachability and Time-Based Path Queries in a Temporal Graph
Huanhuan Wu, Yuzhen Huang, James Cheng +2
A temporal graph is a graph in which vertices communicate with each other at specific time, e.g., calls at 11 a.m. and talks for 7 minutes, which is modeled by an edge from…
Efficient Processing of Very Large Graphs in a Small Cluster
Da Yan, Yuzhen Huang, James Cheng +1
Inspired by the success of Google's Pregel, many systems have been developed recently for iterative computation over big graphs. These systems provide a user-friendly vertex-centri…