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检索条件"任意字段=8th International Conference on Machine Learning and Data Mining in Pattern Recognition, MLDM 2012"
106 条 记 录,以下是1-10 订阅
排序:
Deep Reinforcement learning for Exact Combinatorial Optimization: learning to Branch  26
Deep Reinforcement Learning for Exact Combinatorial Optimiza...
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26th international conference on pattern recognition / 8th international Workshop on Image mining - theory and Applications (IMTA)
作者: Zhang, Tianyu Banitalebi-Dehkordi, Amin Zhang, Yong Univ Alberta Edmonton AB Canada Huawei Technol Canada Co Ltd Vancouver BC Canada
Branch-and-bound is a systematic enumerative method for combinatorial optimization, where the performance highly relies on the variable selection strategy. State-of-theart handcrafted heuristic strategies suffer from ... 详细信息
来源: 评论
Dynamic data Augmentation with Gating Networks for Time Series recognition  26
Dynamic Data Augmentation with Gating Networks for Time Seri...
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26th international conference on pattern recognition / 8th international Workshop on Image mining - theory and Applications (IMTA)
作者: Oba, Daisuke Matsuo, Shinnosuke Iwana, Brian Kenji Kyushu Univ Dept Adv Informat Technol Fukuoka Japan
data augmentation is a technique to improve the generalization ability of machine learning methods by increasing the size of the dataset. However, since every augmentation method is not equally effective for every dat... 详细信息
来源: 评论
Discovery of New Multi-Level Features for Domain Generalization via Knowledge Corruption  26
Discovery of New Multi-Level Features for Domain Generalizat...
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26th international conference on pattern recognition / 8th international Workshop on Image mining - theory and Applications (IMTA)
作者: Frikha, Ahmed Krompass, Denis Tresp, Volker Siemens Technol Mumbai Maharashtra India Univ Munich LMU Munich Germany
machine learning models that can generalize to unseen domains are essential when applied in real-world scenarios involving strong domain shifts. We address the challenging domain generalization (DG) problem, where a m... 详细信息
来源: 评论
Online Adaptive Metrics for Model Evaluation on Non-representative Offline Test data  26
Online Adaptive Metrics for Model Evaluation on Non-represen...
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26th international conference on pattern recognition / 8th international Workshop on Image mining - theory and Applications (IMTA)
作者: Piovano, Enrico Le, Dieu-thu Chen, Bei Bradford, Melanie Amazon Com Inc Bellevue WA 98004 USA
A major challenge encountered in the offline evaluation of machine learning models before being released to production is the discrepancy between the distributions of the offline test data and of the online data, due ... 详细信息
来源: 评论
Solar Flare Forecasting with Deep learning-based Time Series Classifiers  26
Solar Flare Forecasting with Deep Learning-based Time Series...
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26th international conference on pattern recognition / 8th international Workshop on Image mining - theory and Applications (IMTA)
作者: Ji, Anli Wen, Junzhi Angryk, Rafal Aydin, Berkay Georgia State Univ Dept Comp Sci Atlanta GA 30302 USA
Over the past two decades, machine learning and deep learning techniques for forecasting solar flares have generated great impact due to their ability to learn from a high dimensional data space. However, lack of high... 详细信息
来源: 评论
Unsupervised Feature Selection via Feature-Grouping and Orthogonal Constraint  26
Unsupervised Feature Selection via Feature-Grouping and Orth...
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26th international conference on pattern recognition / 8th international Workshop on Image mining - theory and Applications (IMTA)
作者: Yuan, Aihong Huang, Jiahao Wei, Chen Zhang, Wenjie Zhang, Naidan You, Mengbo Northwest A&F Univ Coll Informat Engn Yangling Shaanxi Peoples R China
In the fields of machine learning and data mining, unsupervised feature selection plays an important role in processing large amounts of high-dimensional unlabeled data. this paper proposes an original and novel unsup... 详细信息
来源: 评论
Se2NAS: Self-Semi-Supervised architecture optimization for Semantic Segmentation  26
Se<SUP>2</SUP>NAS: Self-Semi-Supervised architecture optimiz...
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26th international conference on pattern recognition / 8th international Workshop on Image mining - theory and Applications (IMTA)
作者: Pauletto, Loic Amini, Massih-Reza Winckler, Nicolas ATOS Grenoble France Univ Grenoble Alpes Grenoble France
In this paper, we propose a Neural Architecture Search strategy based on self supervision and semi-supervised learning for the task of semantic segmentation. Our approach builds an optimized neural network (NN) model ... 详细信息
来源: 评论
FedGait: A Benchmark for Federated Gait recognition  26
FedGait: A Benchmark for Federated Gait Recognition
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26th international conference on pattern recognition / 8th international Workshop on Image mining - theory and Applications (IMTA)
作者: Li, Ziqiong Li, Yan-ran Yu, Shiqi Shenzhen Univ Coll Comp Sci & Software Engn Shenzhen Peoples R China Southern Univ Sci & Technol Dept Comp Sci & Engn Shenzhen Peoples R China
Gait recognition has been greatly improved by deep learning and can achieve a relative high accuracy. the advances depend on the data size of gait. However, due to public concerns on privacy and regulations and laws f... 详细信息
来源: 评论
Multi-Class Hypersphere Anomaly Detection  26
Multi-Class Hypersphere Anomaly Detection
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26th international conference on pattern recognition / 8th international Workshop on Image mining - theory and Applications (IMTA)
作者: Kirchheim, Konstantin Filax, Marco Ortmeier, Frank Otto von Guericke Univ Dept Comp Sci Magdeburg Germany
machine learning-based classification algorithms typically operate under assumptions that assert that the underlying data generating distribution is stationary and draws from a finite set of categories. In some scenar... 详细信息
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Adv-Cut Paste: Semantic adversarial class specific data augmentation technique for object detection  26
Adv-Cut Paste: Semantic adversarial class specific data augm...
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26th international conference on pattern recognition / 8th international Workshop on Image mining - theory and Applications (IMTA)
作者: Arun, Kumar S. Pal, Abhijit Mopuri, Konda Reddy Gorthi, Rama Krishna Indian Inst Technol Tirupati Tirupati Andhra Pradesh India Indian Inst Technol Guwahati Gauhati India
data augmentation has been a prevalent approach in improving the performance of deep learning models against slight variations in data. Adversarial learning is one such form of data augmentation. In this work, we aim ... 详细信息
来源: 评论