2 citations · 3 across the 5 of their papers we have counts for
8 papers
Gradient-Leakage Resilient Federated Learning
Wenqi Wei, Ling Liu, Yanzhao Wu +2
Federated learning(FL) is an emerging distributed learning paradigm with default client privacy because clients can keep sensitive data on their devices and only share local traini…
RDMAbox : Optimizing RDMA for Memory Intensive Workloads
Juhyun Bae, Ling Liu, Yanzhao Wu +2
We present RDMAbox, a set of low level RDMA optimizations that provide better performance than previous approaches. The optimizations are packaged in easy-to-use kernel and user sp…
Patient-Specific Seizure Prediction Using Single Seizure Electroencephalography Recording
Zaid Bin Tariq, Arun Iyengar, Lara Marcuse +2
Electroencephalogram (EEG) is a prominent way to measure the brain activity for studying epilepsy, thereby helping in predicting seizures. Seizure prediction is an active research…
Efficient Orchestration of Host and Remote Shared Memory for Memory Intensive Workloads
Juhyun Bae, Gong Su, Arun Iyengar +2
Since very few contributions to the development of an unified memory orchestration framework for efficient management of both host and remote idle memory have been made, we present…
Lachesis: Automatic Partitioning for UDF-Centric Analytics
Jia Zou, Amitabh Das, Pratik Barhate +4
Persistent partitioning is effective in avoiding expensive shuffling operations. However it remains a significant challenge to automate this process for Big Data analytics workload…
Schemaless Queries over Document Tables with Dependencies
Mustafa Canim, Cristina Cornelio, Arun Iyengar +2
Unstructured enterprise data such as reports, manuals and guidelines often contain tables. The traditional way of integrating data from these tables is through a two-step process o…