276 citations · 323 across the 12 of their papers we have counts for
13 papers
Domain Generalization via Selective Consistency Regularization for Time Series Classification
Wenyu Zhang, Mohamed Ragab, Chuan-Sheng Foo
Domain generalization methods aim to learn models robust to domain shift with data from a limited number of source domains and without access to target domain samples during traini…
Few-Shot Adaptation of Pre-Trained Networks for Domain Shift
Wenyu Zhang, Li Shen, Wanyue Zhang +1
Deep networks are prone to performance degradation when there is a domain shift between the source (training) data and target (test) data. Recent test-time adaptation methods updat…
An Evaluation of Anomaly Detection and Diagnosis in Multivariate Time Series
Astha Garg, Wenyu Zhang, Jules Samaran +2
Several techniques for multivariate time series anomaly detection have been proposed recently, but a systematic comparison on a common set of datasets and metrics is lacking. This…
POLA: Online Time Series Prediction by Adaptive Learning Rates
Wenyu Zhang
Online prediction for streaming time series data has practical use for many real-world applications where downstream decisions depend on accurate forecasts for the future. Deployme…
Robust Domain-Free Domain Generalization with Class-aware Alignment
Wenyu Zhang, Mohamed Ragab, Ramon Sagarna
While deep neural networks demonstrate state-of-the-art performance on a variety of learning tasks, their performance relies on the assumption that train and test distributions are…
HALO: Learning to Prune Neural Networks with Shrinkage
Skyler Seto, Martin T. Wells, Wenyu Zhang
Deep neural networks achieve state-of-the-art performance in a variety of tasks by extracting a rich set of features from unstructured data, however this performance is closely tie…
Modeling a Nonlinear Biophysical Trend Followed by Long-Memory Equilibrium with Unknown Change Point
Wenyu Zhang, Maryclare Griffin, David S. Matteson
Measurements of many biological processes are characterized by an initial trend period followed by an equilibrium period. Scientists may wish to quantify features of the two period…
CAZSL: Zero-Shot Regression for Pushing Models by Generalizing Through Context
Wenyu Zhang, Skyler Seto, Devesh K. Jha
Learning accurate models of the physical world is required for a lot of robotic manipulation tasks. However, during manipulation, robots are expected to interact with unknown workp…
Multi-label Prediction in Time Series Data using Deep Neural Networks
Wenyu Zhang, Devesh K. Jha, Emil Laftchiev +1
This paper addresses a multi-label predictive fault classification problem for multidimensional time-series data. While fault (event) detection problems have been thoroughly studie…
ABACUS: Unsupervised Multivariate Change Detection via Bayesian Source Separation
Wenyu Zhang, Daniel Gilbert, David Matteson
Change detection involves segmenting sequential data such that observations in the same segment share some desired properties. Multivariate change detection continues to be a chall…
Financial Forecasting and Analysis for Low-Wage Workers
Wenyu Zhang, Raya Horesh, Karthikeyan N. Ramamurthy +4
Despite the plethora of financial services and products on the market nowadays, there is a lack of such services and products designed especially for the low-wage population. Appro…
Pruning and Nonparametric Multiple Change Point Detection
Wenyu Zhang, Nicholas James, David Matteson
Change point analysis is a statistical tool to identify homogeneity within time series data. We propose a pruning approach for approximate nonparametric estimation of multiple chan…
Multivariate Time Series Classification Using Dynamic Time Warping Template Selection for Human Activity Recognition
Skyler Seto, Wenyu Zhang, Yichen Zhou
Accurate and computationally efficient means for classifying human activities have been the subject of extensive research efforts. Most current research focuses on extracting compl…