J. Ascenso, P. Akyazi, F. Pereira, and T. Ebrahimi, Learning-based image coding: early solutions reviewing and subjective quality evaluation, Optics, Photonics and Digital Technologies for Imaging Applications VI, vol.11353, p.113530, 2020.

J. Chen, M. Karczewicz, Y. Huang, K. Choi, J. Ohm et al., The joint exploration model (JEM) for video compression with capability beyond HEVC, IEEE Transactions on Circuits and Systems for Video Technology, 2019.

Z. Shi, X. Sun, and F. Wu, Photo album compression for cloud storage using local features, IEEE Journal on emerging and selected topics in circuits and systems, vol.4, issue.1, pp.17-28, 2014.

X. Zhang, Y. Zhang, W. Lin, S. Ma, and W. Gao, An inter-image redundancy measure for image set compression, 2015 IEEE International Symposium on Circuits and Systems (ISCAS), pp.1274-1277, 2015.

L. Sha, W. Wu, and B. Li, Novel image set compression algorithm using rate-distortion optimized multiple reference image selection, IEEE Access, vol.6, pp.66-903, 2018.

X. Liu, G. Cheung, C. Lin, D. Zhao, and W. Gao, Prior-based quantization bin matching for cloud storage of JPEG images, IEEE Transactions on Image Processing, vol.27, issue.7, pp.3222-3235, 2018.

K. M. Anstreicher, M. Fampa, J. Lee, and J. Williams, Maximumentropy remote sampling, Discrete Applied Mathematics, vol.108, issue.3, pp.211-226, 2001.

S. P. Chepuri and G. Leus, Graph sampling for covariance estimation, IEEE Transactions on Signal and Information Processing over Networks, vol.3, issue.3, pp.451-466, 2017.

P. M. Baggenstoss, Uniform manifold sampling (ums): Sampling the maximum entropy pdf, IEEE Transactions on Signal Processing, vol.65, issue.9, pp.2455-2470, 2017.

J. Lim, Q. Tian, and P. Mulhem, Home photo content modeling for personalized event-based retrieval, IEEE MultiMedia, vol.10, issue.4, pp.28-37, 2003.

Z. Ji, K. Xiong, Y. Pang, and X. Li, Video summarization with attention-based encoder-decoder networks, IEEE Transactions on Circuits and Systems for Video Technology, 2019.

A. Sharghi, A. Borji, C. Li, T. Yang, and B. Gong, Improving sequential determinantal point processes for supervised video summarization, Proceedings of the European Conference on Computer Vision (ECCV), pp.517-533, 2018.

A. Belhadji, R. Bardenet, and P. Chainais, A determinantal point process for column subset selection, 2018.
URL : https://hal.archives-ouvertes.fr/hal-01966298

A. Kulesza and B. Taskar, k-DPPs: Fixed-size determinantal point processes, ICML, 2011.

K. Muller, S. Mika, G. Ratsch, K. Tsuda, and B. Scholkopf, An introduction to kernel-based learning algorithms, IEEE transactions on neural networks, vol.12, issue.2, pp.181-201, 2001.

D. Charte, F. Charte, S. García, M. J. Jesus, and F. Herrera, A practical tutorial on autoencoders for nonlinear feature fusion: Taxonomy, models, software and guidelines, Information Fusion, vol.44, pp.78-96, 2018.

L. Kuhnel, T. Fletcher, S. Joshi, and S. Sommer, Latent space nonlinear statistics, 2018.

M. Naumov, D. Mudigere, H. M. Shi, J. Huang, N. Sundaraman et al., Deep learning recommendation model for personalization and recommendation systems, 2019.

X. Yu, Y. Chu, F. Jiang, Y. Guo, and D. Gong, Svms classification based two-side cross domain collaborative filtering by inferring intrinsic user and item features, Knowledge-Based Systems, vol.141, pp.80-91, 2018.

X. Yu, F. Jiang, J. Du, and D. Gong, A cross-domain collaborative filtering algorithm with expanding user and item features via the latent factor space of auxiliary domains, Pattern Recognition, vol.94, pp.96-109, 2019.

A. Kulesza and B. Taskar, Determinantal point processes for machine learning, Foundations and Trends R in Machine Learning, vol.5, pp.123-286, 2012.

N. Tremblay, P. Amblard, and S. Barthelmé, Graph sampling with determinantal processes, 2017 25th European Signal Processing Conference (EUSIPCO), pp.1674-1678, 2017.
URL : https://hal.archives-ouvertes.fr/hal-01483347

E. J. Candès and M. B. Wakin, An introduction to compressive sampling, IEEE signal processing magazine, vol.25, issue.2, pp.21-30, 2008.

E. J. Candes and Y. Plan, Matrix completion with noise, Proceedings of the IEEE, vol.98, issue.6, pp.925-936, 2010.

S. Chen, R. Varma, A. Sandryhaila, and J. Kova?evi?, Discrete signal processing on graphs: Sampling theory¡? pub newline=, IEEE transactions on signal processing, vol.63, pp.6510-6523, 2015.

I. Pesenson, Variational splines and paley-wiener spaces on combinatorial graphs, Constructive Approximation, vol.29, issue.1, pp.1-21, 2009.

N. Perraudin, J. Paratte, D. Shuman, L. Martin, V. Kalofolias et al., GSPBOX: A toolbox for signal processing on graphs, 2014.