101 citations · 159 across the 6 of their papers we have counts for
9 papers
Kernel Stein Generative Modeling
Wei-Cheng Chang, Chun-Liang Li, Youssef Mroueh +1
We are interested in gradient-based Explicit Generative Modeling where samples can be derived from iterative gradient updates based on an estimate of the score function of the data…
Correlation-aware Unsupervised Change-point Detection via Graph Neural Networks
Ruohong Zhang, Yu Hao, Donghan Yu +3
Change-point detection (CPD) aims to detect abrupt changes over time series data. Intuitively, effective CPD over multivariate time series should require explicit modeling of the d…
Pre-training Tasks for Embedding-based Large-scale Retrieval
Wei-Cheng Chang, Felix X. Yu, Yin-Wen Chang +2
We consider the large-scale query-document retrieval problem: given a query (e.g., a question), return the set of relevant documents (e.g., paragraphs containing the answer) from a…
XL-Editor: Post-editing Sentences with XLNet
Yong-Siang Shih, Wei-Cheng Chang, Yiming Yang
While neural sequence generation models achieve initial success for many NLP applications, the canonical decoding procedure with left-to-right generation order (i.e., autoregressiv…
Taming Pretrained Transformers for Extreme Multi-label Text Classification
Wei-Cheng Chang, Hsiang-Fu Yu, Kai Zhong +2
We consider the extreme multi-label text classification (XMC) problem: given an input text, return the most relevant labels from a large label collection. For example, the input te…
Implicit Kernel Learning
Chun-Liang Li, Wei-Cheng Chang, Youssef Mroueh +2
Kernels are powerful and versatile tools in machine learning and statistics. Although the notion of universal kernels and characteristic kernels has been studied, kernel selection…