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We propose a method for jointly inferring labels across a collection of data samples, where each sample consists of an observation and a prior belief about the label.
Maximum likelihood from incomplete data via the EM algorithm
A. P. Dempster, N. M. Laird, and D. B. Rubin · 1977
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The "wake-sleep" algorithm for unsupervised neural networks
Geoffrey E. Hinton, Peter Dayan, Brendan J. Frey, and R M Neal · 1995
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Learning with multiple labels
Rong Jin and Zoubin Ghahramani · 2002
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Learning with Labeled and Unlabeled Data
Matthias Seeger · 2002
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OpenStreetMap: User-generated street maps
Mordechai Haklay and Patrick Weber · 2008
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Classification with partial labels
Nam Nguyen and Rich Caruana · 2008
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Stel component analysis: Modeling spatial correlations in image class structure
Nebojsa Jojic, Alessandro Perina, Marco Cristani, Vittorio Murino, and Brendan Frey · 2009
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Generative adversarial nets
Ian J. Goodfellow, Jean Pouget-Abadie, Mehdi Mirza, Bing Xu, David Warde-Farley, Sherjil Ozair, Aaron Courville, and Yoshua Bengio · 2014
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Object detection in optical remote sensing images based on weakly supervised learning and high-level feature learning
Junwei Han, Dingwen Zhang, Gong Cheng, Lei Guo, and Jinchang Ren · 2014
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Learning from imprecise and fuzzy observations: Data disambiguation through generalized loss minimization
Eyke Hüllermeier · 2014
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Adam: A method for stochastic optimization
Diederik P Kingma and Jimmy Ba · 2014
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Auto-encoding variational bayes
Diederik P. Kingma and Max Welling · 2014
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Microsoft COCO: common objects in context
Tsung-Yi Lin, Michael Maire, Serge J. Belongie, James Hays, Pietro Perona, Deva Ramanan, Piotr Dollár, and C. Lawrence Zitnick · 2014
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EnviroAtlas: A new geospatial tool to foster ecosystem services science and resource management
Brian R Pickard, Jessica Daniel, Megan Mehaffey, Laura E Jackson, and Anne Neale · 2015
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Weak supervision and other non-standard classification problems: a taxonomy
Jerónimo Hernández-González, Inaki Inza, and Jose A Lozano · 2016
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A benchmark dataset and evaluation methodology for video object segmentation
F. Perazzi, J. Pont-Tuset, B. McWilliams, L. Van Gool, M. Gross, and A. Sorkine-Hornung · 2016
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Data programming: Creating large training sets, quickly
Alexander J Ratner, Christopher M De Sa, Sen Wu, Daniel Selsam, and Christopher Ré · 2016
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Maximum margin partial label learning
Fei Yu and Min-Ling Zhang · 2016
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Osmnx: New methods for acquiring, constructing, analyzing, and visualizing complex street networks
Geoff Boeing · 2017
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One-shot video object segmentation
S. Caelles, K.K. Maninis, J. Pont-Tuset, L. Leal-Taixé, D. Cremers, and L. Van Gool · 2017
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Mask R-CNN
Kaiming He, Georgia Gkioxari, Piotr Dollár, and Ross Girshick · 2017
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Lucid data dreaming for object tracking
A. Khoreva, R. Benenson, E. Ilg, T. Brox, and B. Schiele · 2017
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Decoupled weight decay regularization
Ilya Loshchilov and Frank Hutter · 2017
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Learning in implicit generative models
Shakir Mohamed and Balaji Lakshminarayanan · 2017
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Learning video object segmentation from static images
Federico Perazzi, Anna Khoreva, Rodrigo Benenson, Bernt Schiele, and Alexander Sorkine-Hornung · 2017
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Snorkel: Rapid training data creation with weak supervision
Alexander Ratner, Stephen H Bach, Henry Ehrenberg, Jason Fries, Sen Wu, and Christopher Ré · 2017
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Opening the black box of deep neural networks via information
Ravid Shwartz-Ziv and Naftali Tishby · 2017
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Language models are unsupervised multitask learners
Alec Radford, Jeffrey Wu, Rewon Child, David Luan, Dario Amodei, Ilya Sutskever, et al · 2019
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Large scale high-resolution land cover mapping with multi-resolution data
Caleb Robinson, Le Hou, Nikolay Malkin, Rachel Soobitsky, Jacob Czawlytko, Bistra Dilkina, and Nebojsa Jojic · 2019
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FEELVOS: Fast end-to-end embedding learning for video object segmentation
Paul Voigtlaender, Yuning Chai, Florian Schroff, Hartwig Adam, Bastian Leibe, and Liang-Chieh Chen · 2019
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Structured prediction with partial labelling through the infimum loss
Vivien Cabannnes, Alessandro Rudi, and Francis Bach · 2020
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Mining self-similarity: Label super-resolution with epitomic representations
Nikolay Malkin, Anthony Ortiz, and Nebojsa Jojic · 2020
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Paul Voigtlaender and Bastian Leibe · 2017
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Evaluation of nucleus segmentation in digital pathology images through large scale image synthesis
Naiyun Zhou, Xiaxia Yu, Tianhao Zhao, Si Wen, Fusheng Wang, Wei Zhu, Tahsin Kurc, Allen Tannenbaum, Joel Saltz, and Yi Gao · 2017
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Fast and accurate online video object segmentation via tracking parts
J. Cheng, Y.-H. Tsai, W.-C. Hung, S. Wang, and M.-H. Yang · 2018
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A general framework for maximizing likelihood under incomplete data
Inés Couso and Didier Dubois · 2018
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Premvos: Proposal-generation, refinement and merging for video object segmentation
Jonathon Luiten, Paul Voigtlaender, and Bastian Leibe · 2018
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Video object segmentation without temporal information
Kevis-Kokitsi Maninis, Sergi Caelles, Yuhua Chen, Jordi Pont-Tuset, Laura Leal-Taixé, Daniel Cremers, and Luc Van Gool · 2018
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Weakly-supervised neural text classification
Yu Meng, Jiaming Shen, Chao Zhang, and Jiawei Han · 2018
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Tim Meinhardt and Laura Leal-Taixe · 2020
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Contextualized weak supervision for text classification
Dheeraj Mekala and Jingbo Shang · 2020
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Text classification using label names only: A language model self-training approach
Yu Meng, Yunyi Zhang, Jiaxin Huang, Chenyan Xiong, Heng Ji, Chao Zhang, and Jiawei Han · 2020
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US EPA EnviroAtlas meter-scale urban land cover (MULC): 1-m pixel land cover class definitions and guidance
Andrew Pilant, Keith Endres, Daniel Rosenbaum, and Gillian Gundersen · 2020
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Human-machine collaboration for fast land cover mapping
Caleb Robinson, Anthony Ortiz, Nikolay Malkin, Blake Elias, Andi Peng, Dan Morris, Bistra Dilkina, and Nebojsa Jojic · 2020
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Fourier features let networks learn high frequency functions in low dimensional domains
Matthew Tancik, Pratul P. Srinivasan, Ben Mildenhall, Sara Fridovich-Keil, Nithin Raghavan, Utkarsh Singhal, Ravi Ramamoorthi, Jonathan T. Barron, and Ren Ng · 2020
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Collaborative video object segmentation by foreground-background integration
Zongxin Yang, Yunchao Wei, and Yi Yang · 2020
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Deep discriminative CNN with temporal ensembling for ambiguously-labeled image classification
Yao Yao, Jiehui Deng, Xiuhua Chen, Chen Gong, Jianxin Wu, and Jian Yang · 2020
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Pseudoseg: Designing pseudo labels for semantic segmentation
Yuliang Zou, Zizhao Zhang, Han Zhang, Chun-Liang Li, Xiao Bian, Jia-Bin Huang, and Tomas Pfister · 2020
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Mrta: Multi-resolution training algorithm for multitemporal semantic change detection
Qianyue Bao, Yang Liu, Zixiao Zhang, Dafan Chen, Yuting Yang, Licheng Jiao, and Fang Liu · 2021
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Rethinking space-time networks with improved memory coverage for efficient video object segmentation
Ho Kei Cheng, Yu-Wing Tai, and Chi-Keung Tang · 2021
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Change cross-detection based on label improvements and multi-model fusion for multi-temporal remote sensing images
Zhuohong Li, Fangxiao Lu, Hongyan Zhang, Guangyi Yang, and Liangpei Zhang · 2021
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Coarse2Fine: Fine-grained text classification on coarsely-grained annotated data
Dheeraj Mekala, Varun Gangal, and Jingbo Shang · 2021
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Torchgeo: deep learning with geospatial data
Adam J Stewart, Caleb Robinson, Isaac A Corley, Anthony Ortiz, Juan M Lavista Ferres, and Arindam Banerjee · 2021
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X-Class: Text classification with extremely weak supervision
Zihan Wang, Dheeraj Mekala, and Jingbo Shang · 2021
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Refining pseudo labels with clustering consensus over generations for unsupervised object re-identification
Xiao Zhang, Yixiao Ge, Yu Qiao, and Hongsheng Li · 2021
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Weakly supervised semantic change detection via label refinement framework
Zhuo Zheng, Yinhe Liu, Shiqi Tian, Junjue Wang, Ailong Ma, and Yanfei Zhong · 2021
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