392 citations
- Centre National de la Recherche ScientifiqueFR10 papers
- Dartmouth CollegeUS9 papers
- North Carolina State UniversityUS9 papers
- Instituto de Astrofísica de CanariasES8 papers
- Iowa State UniversityUS8 papers
- Astronomical Observatory of RomeIT7 papers
- Friedrich-Alexander-Universität Erlangen-NürnbergDE7 papers
- Oak Ridge National LaboratoryUS7 papers
- The University of Texas at AustinUS7 papers
- The University of TokyoJP7 papers
- Astronomical Observatory of CapodimonteIT6 papers
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10 papers · 1 filter
Personalized Observation Normalization for Federated Reinforcement Learning in Simulation Environments with Heterogeneity
Yiran Pang, Zhen Ni, Xiangnan Zhong
Federated reinforcement learning (FedRL) enables multiple agents to collaboratively train a global policy without sharing raw data, making it ideal for privacy-sensitive applicatio…
Deep learning approaches show promise for predicting childhood malnutrition: A comparative study with traditional machine learning methods using survey data
Deepak Bastola, Yang Li
Childhood malnutrition remains a major public health concern in Nepal and other low-resource settings, while conventional case-finding approaches are labor-intensive and frequently…
Bloom Filter Encoding for Machine Learning
John Cartmell, Mihaela Cardei, Ionut Cardei
We present a method that uses a Bloom filter transform to preprocess data for machine learning. Each sample is encoded into a compact bit-array representation using hash-based enco…
HGEN: Heterogeneous Graph Ensemble Networks
Jiajun Shen, Yufei Jin, Yi He +1
This paper presents HGEN that pioneers ensemble learning for heterogeneous graphs. We argue that the heterogeneity in node types, nodal features, and local neighborhood topology po…
Reconstructing Physics-Informed Machine Learning for Traffic Flow Modeling: a Multi-Gradient Descent and Pareto Learning Approach
Yuan-Zheng Lei, Yaobang Gong, Dianwei Chen +2
Physics-informed machine learning (PIML) is crucial in modern traffic flow modeling because it combines the benefits of both physics-based and data-driven approaches. In convention…
Humanity's Last Exam
Long Phan, Alice Gatti, Ziwen Han +1144
Benchmarks are important tools for tracking the rapid advancements in large language model (LLM) capabilities. However, benchmarks are not keeping pace in difficulty: LLMs now achi…