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We introduce SentEval, a toolkit for evaluating the quality of universal sentence representations.
TENE learns the representations of nodes under the guidance of both proximity matrix which captures the network structure and text cluster membership matrix derived from clustering for text information.
It is not straightforward to integrate the content of each node in the current state-of-the-art network embedding methods.
This work presents a new strategy for multi-class classification that requires no class-specific labels, but instead leverages pairwise similarity between examples, which is a weaker form of annotation.
In this work, we adopt a feature-engineering based approach to tackle the task of speech emotion recognition.
Ranked #2 on Speech Emotion Recognition on IEMOCAP
To improve the proposed methods' practical performance, we give heuristics to use larger step-sizes and acceleration.
SOL is an open-source library for scalable online learning algorithms, and is particularly suitable for learning with high-dimensional data.