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202 papers · 1 filter
T3S: Improving Multi-Task Reinforcement Learning with Task-Specific Feature Selector and Scheduler
Yuanqiang Yu, Tianpei Yang, Yongliang Lv +2
Multi-task reinforcement learning (MTRL) is a technique to train multiple tasks simultaneously, where previous works usually train a single model to solve different tasks by sharin…
A PPA-Driven 3D-IC Partitioning Selection Framework with Surrogate Models
Shang Wang, Shuai Liu, Owen Randall +1
3D-IC netlist partitioning is commonly optimized using proxy objectives, while final PPA is treated as a costly evaluation rather than an optimization signal. This proxy-driven par…
Locally Linear Continual Learning for Time Series based on VC-Theoretical Generalization Bounds
Yan V. G. Ferreira, Igor B. Lima, Pedro H. G. Mapa S. +2
Most machine learning methods assume fixed probability distributions, limiting their applicability in nonstationary real-world scenarios. While continual learning methods address t…
An Integrated Fusion Framework for Ensemble Learning Leveraging Gradient Boosting and Fuzzy Rule-Based Models
Jinbo Li, Peng Liu, Long Chen +2
The integration of different learning paradigms has long been a focus of machine learning research, aimed at overcoming the inherent limitations of individual methods. Fuzzy rule-b…
An LLM-Guided Tutoring System for Social Skills Training
Michael Guevarra, Indronil Bhattacharjee, Srijita Das +4
Social skills training targets behaviors necessary for success in social interactions. However, traditional classroom training for such skills is often insufficient to teach effect…
Fuzzy Granule Density-Based Outlier Detection with Multi-Scale Granular Balls
Can Gao, Xiaofeng Tan, Jie Zhou +2
Outlier detection refers to the identification of anomalous samples that deviate significantly from the distribution of normal data and has been extensively studied and used in a v…