Výsledky vyhledávání - "Training data"

IFL-GAN: Improved Federated Learning Generative Adversarial Network With Maximum Mean Discrepancy Model Aggregation Autor Li, Wei, Chen, Jinlin, Wang, Zhenyu, Shen, Zhidong, Ma, Chao, Cui, Xiaohui

“…The generative adversarial network (GAN) is usually built from the centralized, independent identically distributed (i.i.d.) training data to generate…”
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Membership Inference Attacks From First Principles Autor Carlini, Nicholas, Chien, Steve, Nasr, Milad, Song, Shuang, Terzis, Andreas, Tramer, Florian

“…A membership inference attack allows an adversary to query a trained machine learning model to predict whether or not a particular example was contained in the…”
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RGBT Tracking via Challenge-Based Appearance Disentanglement and Interaction Autor Liu, Lei, Li, Chenglong, Xiao, Yun, Ruan, Rui, Fan, Minghao

“…RGB and thermal source data suffer from both shared and specific challenges, and how to explore and exploit them plays a critical role in representing the…”
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Deep learning for magnification independent breast cancer histopathology image classification Autor Bayramoglu, Neslihan, Kannala, Juho, Heikkila, Janne

“…Microscopic analysis of breast tissues is necessary for a definitive diagnosis of breast cancer which is the most common cancer among women. Pathology…”
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InstructPix2Pix: Learning to Follow Image Editing Instructions Autor Brooks, Tim, Holynski, Aleksander, Efros, Alexei A.

“…We propose a method for editing images from human instructions: given an input image and a written instruction that tells the model what to do, our model…”
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Toward Causal Representation Learning Autor Scholkopf, Bernhard, Locatello, Francesco, Bauer, Stefan, Ke, Nan Rosemary, Kalchbrenner, Nal, Goyal, Anirudh, Bengio, Yoshua

“…The two fields of machine learning and graphical causality arose and are developed separately. However, there is, now, cross-pollination and increasing…”
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EnlightenGAN: Deep Light Enhancement Without Paired Supervision Autor Jiang, Yifan, Gong, Xinyu, Liu, Ding, Cheng, Yu, Fang, Chen, Shen, Xiaohui, Yang, Jianchao, Zhou, Pan, Wang, Zhangyang

“…Deep learning-based methods have achieved remarkable success in image restoration and enhancement, but are they still competitive when there is a lack of…”
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Informed Machine Learning - A Taxonomy and Survey of Integrating Prior Knowledge into Learning Systems Autor von Rueden, Laura, Mayer, Sebastian, Beckh, Katharina, Georgiev, Bogdan, Giesselbach, Sven, Heese, Raoul, Kirsch, Birgit, Pfrommer, Julius, Pick, Annika, Ramamurthy, Rajkumar, Walczak, Michal, Garcke, Jochen, Bauckhage, Christian, Schuecker, Jannis

“…Despite its great success, machine learning can have its limits when dealing with insufficient training data. A potential solution is the additional…”
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Hybrid Transformers for Music Source Separation Autor Rouard, Simon, Massa, Francisco, Defossez, Alexandre

“…A natural question arising in Music Source Separation (MSS) is whether long range contextual information is useful, or whether local acoustic features are…”
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Leveraging Weakly Supervised Data to Improve End-to-end Speech-to-text Translation Autor Jia, Ye, Johnson, Melvin, Macherey, Wolfgang, Weiss, Ron J., Cao, Yuan, Chiu, Chung-Cheng, Ari, Naveen, Laurenzo, Stella, Wu, Yonghui

“…End-to-end Speech Translation (ST) models have many potential advantages when compared to the cascade of Automatic Speech Recognition (ASR) and text Machine…”
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Machine Learning Testing: Survey, Landscapes and Horizons Autor Zhang, Jie M., Harman, Mark, Ma, Lei, Liu, Yang

“…This paper provides a comprehensive survey of techniques for testing machine learning systems; Machine Learning Testing (ML testing) research. It covers 144…”
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Land cover fraction mapping across global biomes with Landsat data, spatially generalized regression models and spectral-temporal metrics Autor Schug, Franz, Pfoch, Kira A., Pham, Vu-Dong, van der Linden, Sebastian, Okujeni, Akpona, Frantz, David, Radeloff, Volker C.

“…Mapping land cover in highly heterogeneous landscapes is challenging, and classifications have inherent limitations where the spatial resolution of remotely…”
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Dataset Security for Machine Learning: Data Poisoning, Backdoor Attacks, and Defenses Autor Goldblum, Micah, Tsipras, Dimitris, Xie, Chulin, Chen, Xinyun, Schwarzschild, Avi, Song, Dawn, Madry, Aleksander, Li, Bo, Goldstein, Tom

“…As machine learning systems grow in scale, so do their training data requirements, forcing practitioners to automate and outsource the curation of training…”
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Applications of Physics-Informed Neural Networks in Power Systems - A Review Autor Huang, Bin, Wang, Jianhui

“…The advances of deep learning (DL) techniques bring new opportunities to numerous intractable tasks in power systems (PSs). Nevertheless, the extension of the…”
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Harmonious Attention Network for Person Re-identification Autor Li, Wei, Zhu, Xiatian, Gong, Shaogang

“…Existing person re-identification (re-id) methods either assume the availability of well-aligned person bounding box images as model input or rely on…”
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Variance-Reduced Methods for Machine Learning Autor Gower, Robert M., Schmidt, Mark, Bach, Francis, Richtarik, Peter

“…Stochastic optimization lies at the heart of machine learning, and its cornerstone is stochastic gradient descent ( SGD ), a method introduced over 60 years…”
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The Carbon Footprint of Machine Learning Training Will Plateau, Then Shrink Autor Patterson, David, Gonzalez, Joseph, Holzle, Urs, Le, Quoc, Liang, Chen, Munguia, Lluis-Miquel, Rothchild, Daniel, So, David R., Texier, Maud, Dean, Jeff

“…Machine learning (ML) workloads have rapidly grown, raising concerns about their carbon footprint. We show four best practices to reduce ML training energy and…”
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A Continual Learning Survey: Defying Forgetting in Classification Tasks Autor De Lange, Matthias, Aljundi, Rahaf, Masana, Marc, Parisot, Sarah, Jia, Xu, Leonardis, Ales, Slabaugh, Gregory, Tuytelaars, Tinne

“…Artificial neural networks thrive in solving the classification problem for a particular rigid task, acquiring knowledge through generalized learning behaviour…”
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Learning From Noisy Labels With Deep Neural Networks: A Survey Autor Song, Hwanjun, Kim, Minseok, Park, Dongmin, Shin, Yooju, Lee, Jae-Gil

“…Deep learning has achieved remarkable success in numerous domains with help from large amounts of big data. However, the quality of data labels is a concern…”
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Deep Learning for Person Re-Identification: A Survey and Outlook Autor Ye, Mang, Shen, Jianbing, Lin, Gaojie, Xiang, Tao, Shao, Ling, Hoi, Steven C. H.

“…Person re-identification (Re-ID) aims at retrieving a person of interest across multiple non-overlapping cameras. With the advancement of deep neural networks…”
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