Making Sense of Touch: Unsupervised Shapelet Learning in Bag-of-words Sense

• URL: http://arxiv.org/abs/2502.04167v1
• Date: Thu, 06 Feb 2025 15:50:40 GMT
• Title: Making Sense of Touch: Unsupervised Shapelet Learning in Bag-of-words Sense
• Authors: Zhicong Xian, Tabish Chaudhary, Jürgen Bock,
• Abstract summary: This paper introduces NN-STNE, a neuralization network using t-distributed neighbor manipulation (t-SNE) data to reduce input dimensions by mapping as to shapelet data.
• Score: 0.0
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• Abstract: This paper introduces NN-STNE, a neural network using t-distributed stochastic neighbor embedding (t-SNE) as a hidden layer to reduce input dimensions by mapping long time-series data into shapelet membership probabilities. A Gaussian kernel-based mean square error preserves local data structure, while K-means initializes shapelet candidates due to the non-convex optimization challenge. Unlike existing methods, our approach uses t-SNE to address crowding in low-dimensional space and applies L1-norm regularization to optimize shapelet length. Evaluations on the UCR dataset and an electrical component manipulation task, like switching on, demonstrate improved clustering accuracy over state-of-the-art feature-learning methods in robotics.

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