3 citations · 3 across the 6 of their papers we have counts for
6 papers
Smaller Batches, Bigger Gains? Investigating the Impact of Batch Sizes on Reinforcement Learning Based Real-World Production Scheduling
Arthur Müller, Felix Grumbach, Matthia Sabatelli
Production scheduling is an essential task in manufacturing, with Reinforcement Learning (RL) emerging as a key solution. In a previous work, RL was utilized to solve an extended p…
VDSC: Enhancing Exploration Timing with Value Discrepancy and State Counts
Marius Captari, Remo Sasso, Matthia Sabatelli
Despite the considerable attention given to the questions of \textit{how much} and \textit{how to} explore in deep reinforcement learning, the investigation into \textit{when} to e…
Mapping Transformer Leveraged Embeddings for Cross-Lingual Document Representation
Tsegaye Misikir Tashu, Eduard-Raul Kontos, Matthia Sabatelli +1
Recommendation systems, for documents, have become tools to find relevant content on the Web. However, these systems have limitations when it comes to recommending documents in lan…
Bridging the Reality Gap of Reinforcement Learning based Traffic Signal Control using Domain Randomization and Meta Learning
Arthur Müller, Matthia Sabatelli
Reinforcement Learning (RL) has been widely explored in Traffic Signal Control (TSC) applications, however, still no such system has been deployed in practice. A key barrier to pro…
Learning Perceptive Bipedal Locomotion over Irregular Terrain
Bart van Marum, Matthia Sabatelli, Hamidreza Kasaei
In this paper we propose a novel bipedal locomotion controller that uses noisy exteroception to traverse a wide variety of terrains. Building on the cutting-edge advancements in at…
How Well Do Vision Transformers (VTs) Transfer To The Non-Natural Image Domain? An Empirical Study Involving Art Classification
Vincent Tonkes, Matthia Sabatelli
Vision Transformers (VTs) are becoming a valuable alternative to Convolutional Neural Networks (CNNs) when it comes to problems involving high-dimensional and spatially organized i…