activity
20192024
most citedA Functional approach for Two Way Dimension Reduction in Time Series

12 citations · 33 across the 12 of their papers we have counts for

collaborators

13 papers

cs.AI2024

Multi-Agent Decision Transformers for Dynamic Dispatching in Material Handling Systems Leveraging Enterprise Big Data

Xian Yeow Lee, Haiyan Wang, Daisuke Katsumata +2

Dynamic dispatching rules that allocate resources to tasks in real-time play a critical role in ensuring efficient operations of many automated material handling systems across ind…

cs.LG2024★ 1 cited

Multi-agent Reinforcement Learning for Dynamic Dispatching in Material Handling Systems

Xian Yeow Lee, Haiyan Wang, Daisuke Katsumata +2

This paper proposes a multi-agent reinforcement learning (MARL) approach to learn dynamic dispatching strategies, which is crucial for optimizing throughput in material handling sy…

cs.LG2024★ 1 cited

Predictive Analysis for Optimizing Port Operations

Aniruddha Rajendra Rao, Haiyan Wang, Chetan Gupta

Maritime transport is a pivotal logistics mode for the long-distance and bulk transportation of goods. However, the intricate planning involved in this mode is often hindered by un…

cs.LG2023★ 12 cited

A Functional approach for Two Way Dimension Reduction in Time Series

Aniruddha Rajendra Rao, Haiyan Wang, Chetan Gupta

The rise in data has led to the need for dimension reduction techniques, especially in the area of non-scalar variables, including time series, natural language processing, and com…

cs.LG2022★ 5 cited

Distributional Actor-Critic Ensemble for Uncertainty-Aware Continuous Control

Takuya Kanazawa, Haiyan Wang, Chetan Gupta

Uncertainty quantification is one of the central challenges for machine learning in real-world applications. In reinforcement learning, an agent confronts two kinds of uncertainty,…

cs.LG2022

K-nearest Multi-agent Deep Reinforcement Learning for Collaborative Tasks with a Variable Number of Agents

Hamed Khorasgani, Haiyan Wang, Hsiu-Khuern Tang +1

Traditionally, the performance of multi-agent deep reinforcement learning algorithms are demonstrated and validated in gaming environments where we often have a fixed number of age…