Search Results for author:
Found 3 papers, 1 papers with code
AB/BA analysis: A framework for estimating keyword spotting recall improvement while maintaining audio privacy
The KWS is designed to only collect data when the keyword is present, limiting the availability of hard samples that may contain false negatives, and preventing direct estimation of model recall from production data.
Scalable Label Propagation for Multi-relational Learning on the Tensor Product of Graphs
In this paper, we generalize a widely used label propagation model to the normalized tensor product graph, and propose an optimization formulation and a scalable Low-rank Tensor-based Label Propagation algorithm (LowrankTLP) to infer multi-relations for two learning tasks, hyperlink prediction and multiple graph alignment.
Low-rank Label Propagation for Semi-supervised Learning with 100 Millions Samples
The success of semi-supervised learning crucially relies on the scalability to a huge amount of unlabelled data that are needed to capture the underlying manifold structure for better classification.
