98 citations · 282 across the 36 of their papers we have counts for
5 papers · 1 filter
Learning Text-Image Joint Embedding for Efficient Cross-Modal Retrieval with Deep Feature Engineering
Zhongwei Xie, Ling Liu, Yanzhao Wu +2
This paper introduces a two-phase deep feature engineering framework for efficient learning of semantics enhanced joint embedding, which clearly separates the deep feature engineer…
Learning TFIDF Enhanced Joint Embedding for Recipe-Image Cross-Modal Retrieval Service
Zhongwei Xie, Ling Liu, Yanzhao Wu +2
It is widely acknowledged that learning joint embeddings of recipes with images is challenging due to the diverse composition and deformation of ingredients in cooking procedures.…
Parallel Detection for Efficient Video Analytics at the Edge
Yanzhao Wu, Ling Liu, Ramana Kompella
Deep Neural Network (DNN) trained object detectors are widely deployed in many mission-critical systems for real time video analytics at the edge, such as autonomous driving and vi…
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…