Anand Padmanabha Iyer |


Towards Fast and Scalable Graph Pattern Mining

Monarch: Gaining Command on Geo-Distributed Graph Analytics

Bridging the GAP: Towards Approximate Graph Analytics

A Scalable Distributed Spatial Index for the Internet-of-Things

Automating Diagnosis of Cellular Radio Access Network Problems

Time-evolving Graph Processing at Scale

Blog Posts

RISELab publication wins best paper award at SIGMOD GRADES-NDA 2018

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RISELab publication “Bridging the GAP: Towards Approximate Graph Analytics“, authored by Anand Iyer, Aurojit Panda, Shivaram Venkataraman, Mosharaf Chowdhury, Prof. Aditya Akella, Prof. Scott Shenker and Prof. Ion Stoica, has won the best paper award at ACM GRADES-NDA 2018, co-located with SIGMOD. The paper proposes the use of approximation to speed up distributed graph processing.