Suchergebnisse - "Computing methodologies→Machine learning algorithms"

Learning Metric Fields for Fast Low‐Distortion Mesh Parameterizations von Fargion, G., Weber, O.

“… We present a fast and robust method for computing an injective parameterization with low isometric distortion for disk‐like triangular meshes. Harmonic …”
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Llanimation: Llama Driven Gesture Animation von Windle, J, Matthews, I, Taylor, S

“… Co‐speech gesturing is an important modality in conversation, providing context and social cues. In character animation, appropriate and synchronised gestures …”
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Neural Sequence Transformation von Mukherjee, Sabyasachi, Mukherjee, Sayan, Hua, Binh‐Son, Umetani, Nobuyuki, Meister, Daniel

“… Monte Carlo integration is a technique for numerically estimating a definite integral by stochastically sampling its integrand. These samples can be averaged …”
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Bridging the Gap between Real-world and Synthetic Images for Testing Autonomous Driving Systems von Amini, Mohammad Hossein, Nejati, Shiva

“… Deep Neural Networks (DNNs) for Autonomous Driving Systems (ADS) are typically trained on real-world images and tested using synthetic images from simulators …”
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Personalized HeartSteps: A Reinforcement Learning Algorithm for Optimizing Physical Activity von Liao, Peng, Greenewald, Kristjan, Klasnja, Predrag, Murphy, Susan

“… With the recent proliferation of mobile health technologies, health scientists are increasingly interested in developing just-in-time adaptive interventions …”
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Indirectly-Supervised Anomaly Detection of Clinically-Meaningful Health Events from Smart Home Data von Dahmen, Jessamyn, Cook, Diane J

“… Anomaly detection techniques can extract a wealth of information about unusual events. Unfortunately, these methods yield an abundance of findings that are not …”
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TileFlow: A Framework for Modeling Fusion Dataflow via Tree-based Analysis von Zheng, Size, Chen, Siyuan, Gao, Siyuan, Jia, Liancheng, Sun, Guangyu, Wang, Runsheng, Liang, Yun

“… With the increasing size of DNN models and the growing discrepancy between compute performance and memory bandwidth, fusing multiple layers together to reduce …”
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Learning to Drive Software-Defined Solid-State Drives von Li, Daixuan, Sun, Jinghan, Huang, Jian

“… Thanks to the mature manufacturing techniques, flash-based solid-state drives (SSDs) are highly customizable for applications today, which brings opportunities …”
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MolSearch: Search-based Multi-objective Molecular Generation and Property Optimization von Sun, Mengying, Wang, Huijun, Xing, Jing, Chen, Bin, Meng, Han, Zhou, Jiayu

“… Leveraging computational methods to generate small molecules with desired properties has been an active research area in the drug discovery field. Towards …”
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Selection of an Ideal Machine Learning Framework for Predicting Perturbation Effects on Network Topology of Bacterial KEGG Pathways von Robben, Michael, Mohammad Sadegh Nasr, Das, Avishek, Huber, Manfred, Jaworski, Justyn, Weidanz, Jon, Luber, Jacob M

“… Biological networks for bacterial species are used to assign functional information to newly sequenced organisms but network quality can be largely affected by …”
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Generalized Matrix Local Low Rank Representation by Random Projection and Submatrix Propagation von Dang, Pengtao, Zhu, Haiqi, Guo, Tingbo, Wan, Changlin, Zhao, Tong, Salama, Paul, Wang, Yijie, Cao, Sha, Zhang, Chi

“… Matrix low rank approximation is an effective method to reduce or eliminate the statistical redundancy of its components. Compared with the traditional global …”
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