7 citations · 18 across the 8 of their papers we have counts for
8 papers
Compressing and Interpreting Word Embeddings with Latent Space Regularization and Interactive Semantics Probing
Haoyu Li, Junpeng Wang, Yan Zheng +3
Word embedding, a high-dimensional (HD) numerical representation of words generated by machine learning models, has been used for different natural language processing tasks, e.g.,…
Quantized Wasserstein Procrustes Alignment of Word Embedding Spaces
Prince O Aboagye, Yan Zheng, Michael Yeh +6
Optimal Transport (OT) provides a useful geometric framework to estimate the permutation matrix under unsupervised cross-lingual word embedding (CLWE) models that pose the alignmen…
Embedding Compression with Hashing for Efficient Representation Learning in Large-Scale Graph
Chin-Chia Michael Yeh, Mengting Gu, Yan Zheng +6
Graph neural networks (GNNs) are deep learning models designed specifically for graph data, and they typically rely on node features as the input to the first layer. When applying…
Learning-From-Disagreement: A Model Comparison and Visual Analytics Framework
Junpeng Wang, Liang Wang, Yan Zheng +3
With the fast-growing number of classification models being produced every day, numerous model interpretation and comparison solutions have also been introduced. For example, LIME…
Error-bounded Approximate Time Series Joins Using Compact Dictionary Representations of Time Series
Chin-Chia Michael Yeh, Yan Zheng, Junpeng Wang +4
The matrix profile is an effective data mining tool that provides similarity join functionality for time series data. Users of the matrix profile can either join a time series with…
Online Multi-horizon Transaction Metric Estimation with Multi-modal Learning in Payment Networks
Chin-Chia Michael Yeh, Zhongfang Zhuang, Junpeng Wang +5
Predicting metrics associated with entities' transnational behavior within payment processing networks is essential for system monitoring. Multivariate time series, aggregated from…
VERB: Visualizing and Interpreting Bias Mitigation Techniques for Word Representations
Archit Rathore, Sunipa Dev, Jeff M. Phillips +6
Word vector embeddings have been shown to contain and amplify biases in data they are extracted from. Consequently, many techniques have been proposed to identify, mitigate, and at…
Merchant Category Identification Using Credit Card Transactions
Chin-Chia Michael Yeh, Zhongfang Zhuang, Yan Zheng +3
Digital payment volume has proliferated in recent years with the rapid growth of small businesses and online shops. When processing these digital transactions, recognizing each mer…