activity
20222026
most citedRobust Explainer Recommendation for Time Series Classification

15 citations · 15 across the 6 of their papers we have counts for

collaborators

6 papers

cs.LG2026

Scaling Time Series Classification via XAI-Driven Data Reduction

Davide Italo Serramazza, Thach Le Nguyen, Georgiana Ifrim

Explainable AI (XAI) for time series has seen significant algorithmic growth, but its utility in providing measurable performance gains for downstream tasks remains under-explored.…

cs.LG2024

Improving the Evaluation and Actionability of Explanation Methods for Multivariate Time Series Classification

Davide Italo Serramazza, Thach Le Nguyen, Georgiana Ifrim

Explanation for Multivariate Time Series Classification (MTSC) is an important topic that is under explored. There are very few quantitative evaluation methodologies and even fewer…

cs.LG2023

Evaluating Explanation Methods for Multivariate Time Series Classification

Davide Italo Serramazza, Thu Trang Nguyen, Thach Le Nguyen +1

Multivariate time series classification is an important computational task arising in applications where data is recorded over time and over multiple channels. For example, a smart…

cs.CV2023

An Examination of Wearable Sensors and Video Data Capture for Human Exercise Classification

Ashish Singh, Antonio Bevilacqua, Timilehin B. Aderinola +5

Wearable sensors such as Inertial Measurement Units (IMUs) are often used to assess the performance of human exercise. Common approaches use handcrafted features based on domain ex…

cs.LG2023★ 15 cited

Robust Explainer Recommendation for Time Series Classification

Thu Trang Nguyen, Thach Le Nguyen, Georgiana Ifrim

Time series classification is a task which deals with temporal sequences, a prevalent data type common in domains such as human activity recognition, sports analytics and general s…

cs.LG2022

Scalable Classifier-Agnostic Channel Selection for Multivariate Time Series Classification

Bhaskar Dhariyal, Thach Le Nguyen, Georgiana Ifrim

Accuracy is a key focus of current work in time series classification. However, speed and data reduction in many applications is equally important, especially when the data scale a…