LeArning Abstract
Learning, in the context of these papers, encompasses a broad range of research focused on improving the efficiency, robustness, and adaptability of machine learning models across diverse applications. Current efforts concentrate on developing novel self-supervised learning techniques, particularly for structured data like tabular formats, and on leveraging low-rank adaptations for efficient fine-tuning of large language and other foundation models. These advancements are significant because they address key challenges in data efficiency, computational cost, and the generalization capabilities of machine learning systems, impacting fields ranging from personalized medicine to autonomous robotics.
2549papers
Papers - Page 7
March 11, 2025
Data-driven Nonlinear Modal Analysis with Physics-constrained Deep Learning: Numerical and Experimental Study
Abdolvahhab Rostamijavanani, Shanwu Li, Yongchao YangMichigan Technological UniversitySmoothing ADMM for Non-convex and Non-smooth Hierarchical Federated Learning
Reza Mirzaeifard, Stefan WernerNorwegian University of Science and TechnologyExtra Clients at No Extra Cost: Overcome Data Heterogeneity in Federated Learning with Filter Decomposition
Wei Chen, Qiang QiuPurdue UniversityLearning to Match Unpaired Data with Minimum Entropy Coupling
Mustapha Bounoua, Giulio Franzese, Pietro MichiardiAmpere Software Technology●EURECOMExMAG: Learning of Maximally Ancestral Graphs
Petr Ryšavý, Pavel Rytíř, Xiaoyu He, Georgios Korpas, Jakub MarečekCzech Technical University in Prague●HSBC Quantum Technologies Group●Archimedes Research Unit on AICL-MVSNet: Unsupervised Multi-view Stereo with Dual-level Contrastive Learning
Kaiqiang Xiong, Rui Peng, Zhe Zhang, Tianxing Feng, Jianbo Jiao, Feng Gao, Ronggang WangPeking University●Peng Cheng Laboratory●Migu Culture Technology Co.●University of BirminghamCooperative Bearing-Only Target Pursuit via Multiagent Reinforcement Learning: Design and Experiment
Jianan Li, Zhikun Wang, Susheng Ding, Shiliang Guo, Shiyu ZhaoShanghai AI Laboratory●Westlake UniversityStructural and Statistical Texture Knowledge Distillation and Learning for Segmentation
Deyi Ji, Feng Zhao, Hongtao Lu, Feng Wu, Jieping YeUniversity of Science and Technology of China●Shanghai Jiao Tong University●Alibaba GroupEnhancing Traffic Signal Control through Model-based Reinforcement Learning and Policy Reuse
Yihong Li, Chengwei Zhang, Furui Zhan, Wanting Liu, Kailing Zhou, Longji ZhengDalian Maritime UniversityLearning second-order TVD flux limiters using differentiable solvers
Chenyang Huang, Amal S. Sebastian, Venkatasubramanian ViswanathanUniversity of Michigan
March 10, 2025
Learning and Evaluating Hierarchical Feature Representations
Depanshu Sani, Saket AnandIndraprastha Institute of Information TechnologyEfficient Distributed Learning over Decentralized Networks with Convoluted Support Vector Machine
Canyi Chen, Nan Qiao, Liping ZhuUniversity of Michigan●Renmin University of ChinaLearning Physics-Based Full-Body Human Reaching and Grasping from Brief Walking References
Yitang Li, Mingxian Lin, Zhuo Lin, Yipeng Deng, Yue Cao, Li YiTsinghua University●Shanghai Qi Zhi Institute●Galbot●The University of Hong Kong●Shanghai Artificial Intelligence LaboratoryLearning and planning for optimal synergistic human-robot coordination in manufacturing contexts
Samuele Sandrini, Marco Faroni, Nicola PedrocchiNational Research Council of Italy●Politecnico di Milano●Politecnico di TorinoLearning A Zero-shot Occupancy Network from Vision Foundation Models via Self-supervised Adaptation
Sihao Lin, Daqi Liu, Ruochong Fu, Dongrui Liu, Andy Song, Hongwei Xie, Zhihui Li, Bing Wang, Xiaojun ChangRMIT University●Xiaomi Auto●SJTU●USTC●UTSLearning Energy-Based Models by Self-normalising the Likelihood
Hugo Senetaire, Paul Jeha, Pierre-Alexandre Mattei, Jes FrellsenTechnical University of Denmark●Université Côte d’Azur●Inria●LJAD●CNRSTaking Notes Brings Focus? Towards Multi-Turn Multimodal Dialogue Learning
Jiazheng Liu, Sipeng Zheng, Börje F. Karlsson, Zongqing LuPeking University●Beijing Academy of Artificial Intelligence
March 9, 2025
Agile Climate-Sensor Design and Calibration Algorithms Using Machine Learning: Experiments From Cape Point
Travis Barrett, Amit Kumar MishraUniversity of Cape TownInvestigating Image Manifolds of 3D Objects: Learning, Shape Analysis, and Comparisons
Benjamin Beaudett, Shenyuan Liang, Anuj SrivastavaFlorida State UniversityPrivacy Protection in Prosumer Energy Management Based on Federated Learning
Yunfeng Li, Xiaolin Li Zhitao Li, Gangqiang LiShenzhen University