Databases · Computer Science
Pruned Landmark Labeling Meets Vertex Centric Computation: A Surprisingly Happy Marriage!
Ruoming Jin, Zhen Peng, Wendell Wu, Feodor Dragan +2
2019-07-01
Distributed, Parallel, and Cluster Computing · Computer Science
Planting Trees for scalable and efficient Canonical Hub Labeling
Kartik Lakhotia, Qing Dong, Rajgopal Kannan, Viktor Prasanna
2019-11-28
Machine Learning · Statistics
Labeled Directed Acyclic Graphs: a generalization of context-specific independence in directed graphical models
Johan Pensar, Henrik Nyman, Timo Koski, Jukka Corander
2014-11-12
Machine Learning · Computer Science
Towards Quantized Model Parallelism for Graph-Augmented MLPs Based on Gradient-Free ADMM Framework
Junxiang Wang, Hongyi Li, Zheng Chai, Yongchao Wang +2
2022-11-18
Distributed, Parallel, and Cluster Computing · Computer Science
Parallel Path Progression DAG Scheduling
Niklas Ueter, Mario Günzel, Georg von der Brüggen, Jian-Jia Chen
2022-08-26
Machine Learning · Computer Science
Beyond DAGs: A Latent Partial Causal Model for Multimodal Learning
Yuhang Liu, Zhen Zhang, Dong Gong, Erdun Gao +5
2026-03-03
Data Structures and Algorithms · Computer Science
Improved Parallel Algorithms for Spanners and Hopsets
Gary L. Miller, Richard Peng, Adrian Vladu, Shen Chen Xu
2015-06-25
Distributed, Parallel, and Cluster Computing · Computer Science
Efficiently Scheduling Parallel DAG Tasks on Identical Multiprocessors
Shardul Lendve, Konstantinos Bletsas, Pedro F. Souto
2024-10-24
Distributed, Parallel, and Cluster Computing · Computer Science
Parallel Graph Partitioning for Complex Networks
Henning Meyerhenke, Peter Sanders, Christian Schulz
2015-01-27
Machine Learning · Statistics
Exact Estimation of Multiple Directed Acyclic Graphs
Chris J. Oates, Jim Q. Smith, Sach Mukherjee, James Cussens
2014-11-13
Machine Learning · Computer Science
DAG-AFL:Directed Acyclic Graph-based Asynchronous Federated Learning
Shuaipeng Zhang, Lanju Kong, Yixin Zhang, Wei He +3
2025-07-29
Machine Learning · Computer Science
Graph Partial Label Learning with Potential Cause Discovering
Hang Gao, Jiaguo Yuan, Jiangmeng Li, Peng Qiao +3
2024-08-23
Artificial Intelligence · Computer Science
Plan-over-Graph: Towards Parallelable LLM Agent Schedule
Shiqi Zhang, Xinbei Ma, Zouying Cao, Zhuosheng Zhang +1
2025-02-21
Computer Vision and Pattern Recognition · Computer Science
SPL-MLL: Selecting Predictable Landmarks for Multi-Label Learning
Junbing Li, Changqing Zhang, Pengfei Zhu, Baoyuan Wu +2
2020-08-18
Distributed, Parallel, and Cluster Computing · Computer Science
Rethinking Dynamic Networks and Heterogeneous Computing with Automatic Parallelization
Ruilong Wu, Xinjiao Li, Yisu Wang, Xinyu Chen +1
2025-06-04
Machine Learning · Computer Science
pLSTM: parallelizable Linear Source Transition Mark networks
Korbinian Pöppel, Richard Freinschlag, Thomas Schmied, Wei Lin +1
2025-06-16
Machine Learning · Computer Science
GLL: A Differentiable Graph Learning Layer for Neural Networks
Jason Brown, Bohan Chen, Harris Hardiman-Mostow, Jeff Calder +1
2025-12-10
Machine Learning · Computer Science
Reduction-based Pseudo-label Generation for Instance-dependent Partial Label Learning
Congyu Qiao, Ning Xu, Yihao Hu, Xin Geng
2024-10-29
Machine Learning · Computer Science
Strada-LLM: Graph LLM for traffic prediction
Seyed Mohamad Moghadas, Bruno Cornelis, Alexandre Alahi, Adrian Munteanu
2025-11-17
Distributed, Parallel, and Cluster Computing · Computer Science
Parallel Online Directed Acyclic Graph Exploration for Atlasing Soft-Matter Assembly Configuration Spaces
Rahul Prabhu, Amit Verma, Meera Sitharam
2024-11-05