Добірка наукової літератури з теми "Joint sparsity structure"
Оформте джерело за APA, MLA, Chicago, Harvard та іншими стилями
Ознайомтеся зі списками актуальних статей, книг, дисертацій, тез та інших наукових джерел на тему "Joint sparsity structure".
Біля кожної праці в переліку літератури доступна кнопка «Додати до бібліографії». Скористайтеся нею – і ми автоматично оформимо бібліографічне посилання на обрану працю в потрібному вам стилі цитування: APA, MLA, «Гарвард», «Чикаго», «Ванкувер» тощо.
Також ви можете завантажити повний текст наукової публікації у форматі «.pdf» та прочитати онлайн анотацію до роботи, якщо відповідні параметри наявні в метаданих.
Статті в журналах з теми "Joint sparsity structure"
Huang, Junhao, Weize Sun, and Lei Huang. "Joint Structure and Parameter Optimization of Multiobjective Sparse Neural Network." Neural Computation 33, no. 4 (2021): 1113–43. http://dx.doi.org/10.1162/neco_a_01368.
Повний текст джерелаQin, Si, Yimin D. Zhang, Qisong Wu, and Moeness G. Amin. "Structure-Aware Bayesian Compressive Sensing for Near-Field Source Localization Based on Sensor-Angle Distributions." International Journal of Antennas and Propagation 2015 (2015): 1–15. http://dx.doi.org/10.1155/2015/783467.
Повний текст джерелаLi, Meng, Liang Yan, and Qianying Wang. "Group Sparse Regression-Based Learning Model for Real-Time Depth-Based Human Action Prediction." Mathematical Problems in Engineering 2018 (December 24, 2018): 1–7. http://dx.doi.org/10.1155/2018/8201509.
Повний текст джерелаBirdi, Jasleen, Audrey Repetti, and Yves Wiaux. "Sparse interferometric Stokes imaging under the polarization constraint (Polarized SARA)." Monthly Notices of the Royal Astronomical Society 478, no. 4 (July 4, 2018): 4442–63. http://dx.doi.org/10.1093/mnras/sty1182.
Повний текст джерелаCao, Meng, Wenxing Bao, and Kewen Qu. "Hyperspectral Super-Resolution Via Joint Regularization of Low-Rank Tensor Decomposition." Remote Sensing 13, no. 20 (October 14, 2021): 4116. http://dx.doi.org/10.3390/rs13204116.
Повний текст джерелаDai, Ling-Yun, Rong Zhu, and Juan Wang. "Joint Nonnegative Matrix Factorization Based on Sparse and Graph Laplacian Regularization for Clustering and Co-Differential Expression Genes Analysis." Complexity 2020 (November 16, 2020): 1–10. http://dx.doi.org/10.1155/2020/3917812.
Повний текст джерелаAbdulaziz, Abdullah, Arwa Dabbech, and Yves Wiaux. "Wideband super-resolution imaging in Radio Interferometry via low rankness and joint average sparsity models (HyperSARA)." Monthly Notices of the Royal Astronomical Society 489, no. 1 (August 5, 2019): 1230–48. http://dx.doi.org/10.1093/mnras/stz2117.
Повний текст джерелаTigges, Timo, Janis Sarikas, Michael Klum, and Reinhold Orglmeister. "Compressed sensing of multi-lead ECG signals by compressive multiplexing." Current Directions in Biomedical Engineering 1, no. 1 (September 1, 2015): 65–68. http://dx.doi.org/10.1515/cdbme-2015-0017.
Повний текст джерелаGe, Ting, Tianming Zhan, Qinfeng Li, and Shanxiang Mu. "Optimal Superpixel Kernel-Based Kernel Low-Rank and Sparsity Representation for Brain Tumour Segmentation." Computational Intelligence and Neuroscience 2022 (June 24, 2022): 1–12. http://dx.doi.org/10.1155/2022/3514988.
Повний текст джерелаGe, Ting, Ning Mu, Tianming Zhan, Zhi Chen, Wanrong Gao, and Shanxiang Mu. "Brain Lesion Segmentation Based on Joint Constraints of Low-Rank Representation and Sparse Representation." Computational Intelligence and Neuroscience 2019 (July 1, 2019): 1–11. http://dx.doi.org/10.1155/2019/9378014.
Повний текст джерелаДисертації з теми "Joint sparsity structure"
Liu, Penghuan. "Statistical and numerical optimization for speckle blind structured illumination microscopy." Thesis, Ecole centrale de Nantes, 2018. http://www.theses.fr/2018ECDN0008/document.
Повний текст джерелаConventional structured illumination microscopy (SIM) can surpass the resolution limit inoptical microscopy caused by the diffraction effect, through illuminating the object with a set of perfectly known harmonic patterns. However, controlling the illumination patterns is a difficult task. Even worse, strongdistortions of the light grid can be induced by the sample within the investigated volume, which may give rise to strong artifacts in SIM reconstructed images. Recently, blind-SIM strategies were proposed, whereimages are acquired through unknown, non-harmonic,speckle illumination patterns, which are much easier to generate in practice. The super-resolution capacity of such approaches was observed, although it was not well understood theoretically. This thesis presents two new reconstruction methods in SIM using unknown speckle patterns (blind-speckle-SIM): one joint reconstruction approach and one marginal reconstruction approach. In the joint reconstruction approach, we estimate the object and the speckle patterns together by considering a basis pursuit denoising (BPDN) model with lp,q-norm regularization, with p=>1 and 0
Ramesh, Lekshmi. "Support Recovery from Linear Measurements: Tradeoffs in the Measurement-Constrained Regime." Thesis, 2021. https://etd.iisc.ac.in/handle/2005/5500.
Повний текст джерела"Joint Optimization of Quantization and Structured Sparsity for Compressed Deep Neural Networks." Master's thesis, 2018. http://hdl.handle.net/2286/R.I.50451.
Повний текст джерелаDissertation/Thesis
Masters Thesis Computer Engineering 2018
Тези доповідей конференцій з теми "Joint sparsity structure"
Tao, Shaozhe, Yifan Sun, and Daniel Boley. "Inverse Covariance Estimation with Structured Groups." In Twenty-Sixth International Joint Conference on Artificial Intelligence. California: International Joint Conferences on Artificial Intelligence Organization, 2017. http://dx.doi.org/10.24963/ijcai.2017/395.
Повний текст джерелаLi, Chen, Xutan Peng, Hao Peng, Jianxin Li, and Lihong Wang. "TextGTL: Graph-based Transductive Learning for Semi-supervised Text Classification via Structure-Sensitive Interpolation." In Thirtieth International Joint Conference on Artificial Intelligence {IJCAI-21}. California: International Joint Conferences on Artificial Intelligence Organization, 2021. http://dx.doi.org/10.24963/ijcai.2021/369.
Повний текст джерелаSun, Fangzheng, Yang Liu, and Hao Sun. "Physics-informed Spline Learning for Nonlinear Dynamics Discovery." In Thirtieth International Joint Conference on Artificial Intelligence {IJCAI-21}. California: International Joint Conferences on Artificial Intelligence Organization, 2021. http://dx.doi.org/10.24963/ijcai.2021/283.
Повний текст джерелаXu, Jie, Cheng Deng, Xinbo Gao, Dinggang Shen, and Heng Huang. "Predicting Alzheimer's Disease Cognitive Assessment via Robust Low-Rank Structured Sparse Model." In Twenty-Sixth International Joint Conference on Artificial Intelligence. California: International Joint Conferences on Artificial Intelligence Organization, 2017. http://dx.doi.org/10.24963/ijcai.2017/542.
Повний текст джерелаGrüttemeier, Niels, and Christian Komusiewicz. "Learning Bayesian Networks Under Sparsity Constraints: A Parameterized Complexity Analysis." In Twenty-Ninth International Joint Conference on Artificial Intelligence and Seventeenth Pacific Rim International Conference on Artificial Intelligence {IJCAI-PRICAI-20}. California: International Joint Conferences on Artificial Intelligence Organization, 2020. http://dx.doi.org/10.24963/ijcai.2020/586.
Повний текст джерелаOliveira, Saullo H. G., André R. Gonçalves, and Fernando J. Von Zuben. "Group LASSO with Asymmetric Structure Estimation for Multi-Task Learning." In Twenty-Eighth International Joint Conference on Artificial Intelligence {IJCAI-19}. California: International Joint Conferences on Artificial Intelligence Organization, 2019. http://dx.doi.org/10.24963/ijcai.2019/444.
Повний текст джерелаWang, Zhangyang, Shuai Huang, Jiayu Zhou, and Thomas S. Huang. "Doubly Sparsifying Network." In Twenty-Sixth International Joint Conference on Artificial Intelligence. California: International Joint Conferences on Artificial Intelligence Organization, 2017. http://dx.doi.org/10.24963/ijcai.2017/421.
Повний текст джерелаLiu, Yanchi, Tan Yan, and Haifeng Chen. "Exploiting Graph Regularized Multi-dimensional Hawkes Processes for Modeling Events with Spatio-temporal Characteristics." In Twenty-Seventh International Joint Conference on Artificial Intelligence {IJCAI-18}. California: International Joint Conferences on Artificial Intelligence Organization, 2018. http://dx.doi.org/10.24963/ijcai.2018/343.
Повний текст джерелаWang, Zihan, Zhaochun Ren, Chunyu He, Peng Zhang, and Yue Hu. "Robust Embedding with Multi-Level Structures for Link Prediction." In Twenty-Eighth International Joint Conference on Artificial Intelligence {IJCAI-19}. California: International Joint Conferences on Artificial Intelligence Organization, 2019. http://dx.doi.org/10.24963/ijcai.2019/728.
Повний текст джерелаZhong, Wanjun, Junjie Huang, Qian Liu, Ming Zhou, Jiahai Wang, Jian Yin, and Nan Duan. "Reasoning over Hybrid Chain for Table-and-Text Open Domain Question Answering." In Thirty-First International Joint Conference on Artificial Intelligence {IJCAI-22}. California: International Joint Conferences on Artificial Intelligence Organization, 2022. http://dx.doi.org/10.24963/ijcai.2022/629.
Повний текст джерела