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ORCIDAntonio Ortega
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- affiliation: University of Southern California, Los Angeles, USA
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2020 – today
- 2023
[j89]Tatsuya Koyakumaru, Masahiro Yukawa, Eduardo Pavez, Antonio Ortega:
Learning Sparse Graph with Minimax Concave Penalty under Gaussian Markov Random Fields. IEICE Trans. Fundam. Electron. Commun. Comput. Sci. 106(1): 23-34 (2023)- [j88]Eduardo Pavez
, Benjamin Girault, Antonio Ortega, Philip A. Chou:
Two Channel Filter Banks on Arbitrary Graphs With Positive Semi Definite Variation Operators. IEEE Trans. Signal Process. 71: 917-932 (2023) - [j87]Feng Ji, Wee Peng Tay, Antonio Ortega:
Graph Signal Processing Over a Probability Space of Shift Operators. IEEE Trans. Signal Process. 71: 1159-1174 (2023) - [c304]Benjamin Girault, Eduardo Pavez, Antonio Ortega:
Joint Graph and Vertex Importance Learning. EUSIPCO 2023: 1858-1862 - [c303]Carlos Hurtado, Sarath Shekkizhar, Javier Ruiz Hidalgo, Antonio Ortega:
Study of Manifold Geometry Using Multiscale Non-Negative Kernel Graphs. ICASSP 2023: 1-5 - [c302]Ajinkya Jayawant, Antonio Ortega:
Towards Bandwidth Estimation for Graph Signal Reconstruction. ICASSP 2023: 1-5 - [c301]Ryosuke Watanabe, Keisuke Nonaka, Eduardo Pavez, Tatsuya Kobayashi, Antonio Ortega:
Graph-Based Point Cloud Color Denoising with 3-Dimensional Patch-Based Similarity. ICASSP 2023: 1-5 - [c300]Ryosuke Watanabe, Keisuke Nonaka, Eduardo Pavez, Tatsuya Kobayashi, Antonio Ortega:
Graph Wavelet-Based Point Cloud Geometric Denoising with Surface-Consistent Non-Negative Kernel Regression. ICASSP 2023: 1-5 - [c299]Xin Xiong, Eduardo Pavez, Antonio Ortega, Balu Adsumilli:
Rate-Distortion Optimization with Alternative References for UGC Video Compression. ICASSP 2023: 1-5 - [c298]Samuel Fernández-Menduiña, Eduardo Pavez, Antonio Ortega:
Image Coding Via Perceptually Inspired Graph Learning. ICIP 2023: 2495-2499 - [c297]Ehab Ghabashneh, Chandan Bothra, Ramesh Govindan, Antonio Ortega, Sanjay G. Rao:
Dragonfly: Higher Perceptual Quality For Continuous 360° Video Playback. SIGCOMM 2023: 516-532 - [i55]Benjamin Girault, Eduardo Pavez, Antonio Ortega:
Joint Graph and Vertex Importance Learning. CoRR abs/2303.08552 (2023) - [i54]Ajitesh Srivastava, Juan Marcos Ramirez, Sergio Diaz, José Aguilar, Antonio Ortega, Antonio Fernández Anta, Rosa Lillo-Rodriguez:
Estimating Temporal Trends using Indirect Surveys. CoRR abs/2307.06643 (2023) - 2022
- [j86]Ajinkya Jayawant, Antonio Ortega:
Practical graph signal sampling with log-linear size scaling. Signal Process. 194: 108436 (2022) - [j85]Yung-Hsuan Chao, Haoran Hong, Gene Cheung, Antonio Ortega:
Pre-Demosaic Graph-Based Light Field Image Compression. IEEE Trans. Image Process. 31: 1816-1829 (2022) - [j84]Keng-Shih Lu, Antonio Ortega, Debargha Mukherjee, Yue Chen:
DCT and DST Filtering With Sparse Graph Operators. IEEE Trans. Signal Process. 70: 1641-1656 (2022) - [c296]Haoran Hong, Eduardo Pavez, Antonio Ortega, Ryosuke Watanabe, Keisuke Nonaka:
Fractional Motion Estimation for Point Cloud Compression. DCC 2022: 369-378 - [c295]Ecem Bozkurt, Antonio Ortega:
Non-Negative Kernel Graphs for Time-Varying Signals Using Visibility Graphs. EUSIPCO 2022: 1781-1785 - [c294]Johanna Garcia-Cardona, Antonio Ortega, Nereida Rodriguez-Alvarez:
Graph-Based Interpolation for Remote Sensing Data. EUSIPCO 2022: 1791-1795 - [c293]Sarath Shekkizhar, Antonio Ortega:
NNK-Means: Data summarization using dictionary learning with non-negative kernel regression. EUSIPCO 2022: 2161-2165 - [c292]Ryosuke Watanabe, Keisuke Nonaka, Haruhisa Kato, Eduardo Pavez, Tatsuya Kobayashi, Antonio Ortega:
Point Cloud Denoising Using Normal Vector-Based Graph Wavelet Shrinkage. ICASSP 2022: 2569-2573 - [c291]Shashank N. Sridhara, Eduardo Pavez, Antonio Ortega, Ryosuke Watanabe, Keisuke Nonaka:
Point Cloud Attribute Compression Via Chroma Subsampling. ICASSP 2022: 2579-2583 - [c290]Pratyusha Das, Antonio Ortega:
Gradient-Weighted Class Activation Mapping for Spatio Temporal Graph Convolutional Network. ICASSP 2022: 4043-4047 - [c289]Xiaoyi Mai, Salman Avestimehr, Antonio Ortega, Mahdi Soltanolkotabi:
On The Effectiveness of Active Learning by Uncertainty Sampling in Classification of High-Dimensional Gaussian Mixture Data. ICASSP 2022: 4238-4242 - [c288]David Bonet, Antonio Ortega, Javier Ruiz Hidalgo, Sarath Shekkizhar:
Channel Redundancy and Overlap in Convolutional Neural Networks with Channel-Wise NNK Graphs. ICASSP 2022: 4328-4332 - [c287]Keisuke Nonaka, Ryosuke Watanabe, Haruhisa Kato, Tatsuya Kobayashi, Eduardo Pavez, Antonio Ortega:
Graph-Based Point Cloud Denoising Using Shape-Aware Consistency For Free-Viewpoint Video. ICASSP 2022: 4663-4667 - [c286]Wen-Yang Lu, Eduardo Pavez, Antonio Ortega, Debargha Mukherjee, Onur G. Guleryuz, Keng-Shih Lu:
Intra Prediction of Regular and Near-Regular Textures Via Graph-Based Inpainting. ICIP 2022: 3526-3530 - [c285]Saghar Bagheri, Tam Thuc Do, Gene Cheung, Antonio Ortega:
Hybrid Model-Based / Data-Driven Graph Transform for Image Coding. ICIP 2022: 3667-3671 - [c284]Eduardo Pavez, Enrique Perez, Xin Xiong, Antonio Ortega, Balu Adsumilli:
Compression of User Generated Content Using Denoised References. ICIP 2022: 4188-4192 - [c283]Johanna Garcia-Cardona, Antonio Ortega, Nereida Rodriguez-Alvarez:
Downscaling SMAP Soil Moisture with Ecostress Products using a Graph-Based Interpolation Method. IGARSS 2022: 6169-6172 - [c282]Haoran Hong, Eduardo Pavez, Antonio Ortega, Ryosuke Watanabe, Keisuke Nonaka:
Motion Estimation And Filtered Prediction For Dynamic Point Cloud Attribute Compression. PCS 2022: 139-143 - [i53]Haoran Hong, Eduardo Pavez, Antonio Ortega, Ryosuke Watanabe, Keisuke Nonaka:
Fractional Motion Estimation for Point Cloud Compression. CoRR abs/2202.00172 (2022) - [i52]Saghar Bagheri, Tam Thuc Do, Gene Cheung, Antonio Ortega:
Hybrid Model-based / Data-driven Graph Transform for Image Coding. CoRR abs/2203.01186 (2022) - [i51]Eduardo Pavez, Enrique Perez, Xin Xiong, Antonio Ortega, Balu Adsumilli:
Compression of user generated content using denoised references. CoRR abs/2203.03553 (2022) - [i50]Romain Cosentino, Anirvan M. Sengupta, Salman Avestimehr, Mahdi Soltanolkotabi, Antonio Ortega, Theodore L. Willke, Mariano Tepper:
Toward a Geometrical Understanding of Self-supervised Contrastive Learning. CoRR abs/2205.06926 (2022) - [i49]Romain Cosentino, Sarath Shekkizhar, Mahdi Soltanolkotabi, Salman Avestimehr, Antonio Ortega:
The Geometry of Self-supervised Learning Models and its Impact on Transfer Learning. CoRR abs/2209.08622 (2022) - [i48]Haoran Hong, Eduardo Pavez, Antonio Ortega, Ryosuke Watanabe, Keisuke Nonaka:
Motion estimation and filtered prediction for dynamic point cloud attribute compression. CoRR abs/2210.08262 (2022) - [i47]Carlos Hurtado, Sarath Shekkizhar, Javier Ruiz Hidalgo, Antonio Ortega:
Study of Manifold Geometry using Multiscale Non-Negative Kernel Graphs. CoRR abs/2210.17475 (2022) - 2021
- [j83]Carlos Lassance, Vincent Gripon, Antonio Ortega:
Representing Deep Neural Networks Latent Space Geometries with Graphs. Algorithms 14(2): 39 (2021) - [j82]Nagahara Nagahara, Bhaskar Krishnamachari, Masaki Ogura, Antonio Ortega, Yuichi Tanaka, Yoshiaki Ushifusa, Thomas W. Valente:
Control, intervention, and behavioral economics over human social networks against COVID-19. Adv. Robotics 35(11): 733-739 (2021) - [j81]Carlos Baquero, Paolo Casari, Antonio Fernández Anta, Amanda García-García, Davide Frey, Augusto Garcia-Agundez, Chryssis Georgiou, Benjamin Girault, Antonio Ortega, Mathieu Goessens, Harold A. Hernández-Roig, Nicolas Nicolaou, Efstathios Stavrakis, Oluwasegun Ojo, Julian C. Roberts, Ignacio Sanchez:
The CoronaSurveys System for COVID-19 Incidence Data Collection and Processing. Frontiers Comput. Sci. 3: 641237 (2021) - [j80]Eduardo Pavez, Antonio Ortega:
Covariance Matrix Estimation With Non Uniform and Data Dependent Missing Observations. IEEE Trans. Inf. Theory 67(2): 1201-1215 (2021) - [c281]Sarath Shekkizhar, Antonio Ortega:
Model selection and explainability in neural networks using a polytope interpolation framework. ACSCC 2021: 177-181 - [c280]David Bonet, Antonio Ortega, Javier Ruiz Hidalgo, Sarath Shekkizhar:
Channel-Wise Early Stopping without a Validation Set via NNK Polytope Interpolation. APSIPA ASC 2021: 351-358 - [c279]Pratyusha Das, Antonio Ortega:
Symmetric Sub-graph Spatio-Temporal Graph Convolution and its application in Complex Activity Recognition. ICASSP 2021: 3215-3219 - [c278]Eduardo Pavez, Benjamin Girault, Antonio Ortega, Philip A. Chou:
Spectral Folding And Two-Channel Filter-Banks On Arbitrary Graphs. ICASSP 2021: 5070-5074 - [c277]Saghar Bagheri, Gene Cheung, Antonio Ortega, Fen Wang:
Learning Sparse Graph Laplacian with K Eigenvector Prior via Iterative Glasso and Projection. ICASSP 2021: 5365-5369 - [c276]Tatsuya Koyakumaru, Masahiro Yukawa, Eduardo Pavez, Antonio Ortega:
A Graph Learning Algorithm Based On Gaussian Markov Random Fields And Minimax Concave Penalty. ICASSP 2021: 5410-5414 - [c275]Dion Eustathios Olivier Tzamarias, Eduardo Pavez, Benjamin Girault, Antonio Ortega, Ian Blanes, Joan Serra-Sagristà:
Orthogonality and Zero DC Tradeoffs in Biorthogonal Graph Filterbanks. ICASSP 2021: 5509-5513 - [c274]Pratyusha Das, Antonio Ortega, Siheng Chen, Hassan Mansour, Anthony Vetro:
Application-Agnostic Spatio-Temporal Hand Graph Representations For Stable Activity Understanding. ICIP 2021: 1074-1078 - [c273]Alessandro Gnutti, Fabrizio Guerrini, Riccardo Leonardi, Antonio Ortega:
Symmetry-Based Graph Fourier Transforms: Are They Optimal For Image Compression? ICIP 2021: 1594-1598 - [c272]Shashank N. Sridhara, Eduardo Pavez, Antonio Ortega:
Cylindrical Coordinates for Lidar Point Cloud Compression. ICIP 2021: 3083-3087 - [c271]Eduardo Pavez, André L. Souto, Ricardo L. de Queiroz, Antonio Ortega:
Multi-Resolution Intra-Predictive Coding Of 3d Point Cloud Attributes. ICIP 2021: 3393-3397 - [c270]Chao Pan, Siheng Chen, Antonio Ortega:
Spatio-Temporal Graph Scattering Transform. ICLR 2021 - [i46]Eduardo Pavez, André L. Souto, Ricardo L. de Queiroz, Antonio Ortega:
Multi-resolution intra-predictive coding of 3D point cloud attributes. CoRR abs/2106.08562 (2021) - [i45]David Bonet, Antonio Ortega, Javier Ruiz Hidalgo, Sarath Shekkizhar:
Channel-Wise Early Stopping without a Validation Set via NNK Polytope Interpolation. CoRR abs/2107.12972 (2021) - [i44]Javier Álvarez, Carlos Baquero, Elisa Cabana, Jaya Prakash Champati, Antonio Fernández Anta, Davide Frey, Augusto García-Agundez, Chryssis Georgiou, Mathieu Goessens, Harold Hernández, Rosa E. Lillo, Raquel Menezes, Raúl Moreno, Nicolas Nicolaou, Oluwasegun Ojo, Antonio Ortega, Jesús Rufino, Efstathios Stavrakis, Govind Jeevan, Christin Glorioso:
Estimating Active Cases of COVID-19. CoRR abs/2108.03284 (2021) - [i43]Tatsuya Koyakumaru, Masahiro Yukawa, Eduardo Pavez, Antonio Ortega:
Learning Sparse Graph with Minimax Concave Penalty under Gaussian Markov Random Fields. CoRR abs/2109.08666 (2021) - [i42]Sarath Shekkizhar, Antonio Ortega:
NNK-Means: Dictionary Learning using Non-Negative Kernel regression. CoRR abs/2110.08212 (2021) - [i41]David Bonet, Antonio Ortega, Javier Ruiz Hidalgo, Sarath Shekkizhar:
Channel redundancy and overlap in convolutional neural networks with channel-wise NNK graphs. CoRR abs/2110.11400 (2021) - 2020
- [j79]Yuichi Tanaka, Yonina C. Eldar, Antonio Ortega, Gene Cheung:
Sampling Signals on Graphs: From Theory to Applications. IEEE Signal Process. Mag. 37(6): 14-30 (2020) - [j78]Hilmi E. Egilmez, Yung-Hsuan Chao, Antonio Ortega:
Graph-Based Transforms for Video Coding. IEEE Trans. Image Process. 29: 9330-9344 (2020) - [j77]Basak Güler, Amir Salman Avestimehr, Antonio Ortega:
TACC: Topology-Aware Coded Computing for Distributed Graph Processing. IEEE Trans. Signal Inf. Process. over Networks 6: 508-525 (2020) - [c269]Hong-Ming Chiu, Carrson C. Fung, Antonio Ortega:
Graph Learning and Augmentation Based Interpolation of Signal Strength for Location-Aware Communications. EUSIPCO 2020: 2150-2154 - [c268]Sarath Shekkizhar, Antonio Ortega:
Graph Construction from Data by Non-Negative Kernel Regression. ICASSP 2020: 3892-3896 - [c267]Benjamin Girault, Antonio Ortega, Shrikanth S. Narayayan:
Graph Vertex Sampling with Arbitrary Graph Signal Hilbert Spaces. ICASSP 2020: 5670-5674 - [c266]Carlos Lassance, Myriam Bontonou, Ghouthi Boukli Hacene, Vincent Gripon, Jian Tang, Antonio Ortega:
Deep Geometric Knowledge Distillation with Graphs. ICASSP 2020: 8484-8488 - [c265]Sarath Shekkizhar, Antonio Ortega:
Efficient Graph Construction For Image Representation. ICIP 2020: 1956-1960 - [c264]Eduardo Pavez, Benjamin Girault, Antonio Ortega, Philip A. Chou:
Region Adaptive Graph Fourier Transform for 3D Point Clouds. ICIP 2020: 2726-2730 - [c263]Keng-Shih Lu, Antonio Ortega, Debargha Mukherjee, Yue Chen:
Perceptually Inspired Weighted MSE Optimization Using Irregularity-Aware Graph Fourier Transform. ICIP 2020: 3384-3388 - [c262]Pratyusha Das, Antonio Ortega:
Graph-based skeleton data compression. MMSP 2020: 1-6 - [c261]Keisuke Nonaka, Sarath Shekkizhar, Antonio Ortega:
Graph-based Deep Learning Analysis and Instance Selection. MMSP 2020: 1-6 - [i40]Koki Yamada, Yuichi Tanaka, Antonio Ortega:
Time-Varying Graph Learning with Constraints on Graph Temporal Variation. CoRR abs/2001.03346 (2020) - [i39]Eduardo Pavez, Benjamin Girault, Antonio Ortega, Philip A. Chou:
Region adaptive graph fourier transform for 3d point clouds. CoRR abs/2003.01866 (2020) - [i38]Yuichi Tanaka, Yonina C. Eldar, Antonio Ortega, Gene Cheung:
Sampling on Graphs: From Theory to Applications. CoRR abs/2003.03957 (2020) - [i37]Oluwasegun Ojo, Augusto García-Agundez, Benjamin Girault, Harold Hernández, Elisa Cabana, Amanda García-García, Payman Arabshahi, Carlos Baquero, Paolo Casari, Ednaldo José Ferreira, Davide Frey, Chryssis Georgiou, Mathieu Goessens, Anna Ishchenko, Ernesto Jiménez, Oleksiy Kebkal, Rosa E. Lillo, Raquel Menezes, Nicolas Nicolaou, Antonio Ortega, Paul Patras, Julian C. Roberts, Efstathios Stavrakis, Yuichi Tanaka, Antonio Fernández Anta:
CoronaSurveys: Using Surveys with Indirect Reporting to Estimate the Incidence and Evolution of Epidemics. CoRR abs/2005.12783 (2020) - [i36]Sarath Shekkizhar, Antonio Ortega:
DeepNNK: Explaining deep models and their generalization using polytope interpolation. CoRR abs/2007.10505 (2020) - [i35]Saghar Bagheri, Gene Cheung, Antonio Ortega, Fen Wang:
Learning Sparse Graph Laplacian with K Eigenvector Prior via Iterative GLASSO and Projection. CoRR abs/2010.13179 (2020) - [i34]Carlos Lassance, Vincent Gripon, Antonio Ortega:
Representing Deep Neural Networks Latent Space Geometries with Graphs. CoRR abs/2011.07343 (2020) - [i33]Chao Pan, Siheng Chen, Antonio Ortega:
Spatio-Temporal Graph Scattering Transform. CoRR abs/2012.03363 (2020)
2010 – 2019
- 2019
- [j76]David B. H. Tay, Antonio Ortega:
M-Channel Graph Filter Banks: Polyphase Analysis and Structures. IEEE Signal Process. Lett. 26(5): 730-734 (2019) - [j75]Yoon Hak Kim, Antonio Ortega:
Toward Optimal Rate Allocation to Sampling Sets for Bandlimited Graph Signals. IEEE Signal Process. Lett. 26(9): 1364-1368 (2019) - [j74]Aamir Anis, Aly El Gamal, Amir Salman Avestimehr, Antonio Ortega:
A Sampling Theory Perspective of Graph-Based Semi-Supervised Learning. IEEE Trans. Inf. Theory 65(4): 2322-2342 (2019) - [j73]Hilmi E. Egilmez, Eduardo Pavez, Antonio Ortega:
Graph Learning From Filtered Signals: Graph System and Diffusion Kernel Identification. IEEE Trans. Signal Inf. Process. over Networks 5(2): 360-374 (2019) - [j72]Akie Sakiyama, Kana Watanabe, Yuichi Tanaka, Antonio Ortega:
Two-Channel Critically Sampled Graph Filter Banks With Spectral Domain Sampling. IEEE Trans. Signal Process. 67(6): 1447-1460 (2019) - [j71]Akie Sakiyama, Yuichi Tanaka, Toshihisa Tanaka, Antonio Ortega:
Eigendecomposition-Free Sampling Set Selection for Graph Signals. IEEE Trans. Signal Process. 67(10): 2679-2692 (2019) - [j70]Keng-Shih Lu, Antonio Ortega:
Fast Graph Fourier Transforms Based on Graph Symmetry and Bipartition. IEEE Trans. Signal Process. 67(18): 4855-4869 (2019) - [c260]Eduardo Pavez, Antonio Ortega:
An Efficient Algorithm for Graph Laplacian Optimization Based on Effective Resistances. ACSSC 2019: 51-55 - [c259]Carlos Eduardo Rosar Kós Lassance, Vincent Gripon, Jian Tang, Antonio Ortega:
Structural Robustness for Deep Learning Architectures. DSW 2019: 125-129 - [c258]Myriam Bontonou, Carlos Eduardo Rosar Kós Lassance, Ghouthi Boukli Hacene, Vincent Gripon, Jian Tang, Antonio Ortega:
Introducing Graph Smoothness Loss for Training Deep Learning Architectures. DSW 2019: 160-164 - [c257]Pratyusha Das, Jiun-Yu Kao, Antonio Ortega, Tomoya Sawada, Hassan Mansour, Anthony Vetro, Akira Minezawa:
Hand Graph Representations for Unsupervised Segmentation of Complex Activities. ICASSP 2019: 4075-4079 - [c256]Keng-Shih Lu, Antonio Ortega:
Lapped Transforms: A Graph-based Extension. ICASSP 2019: 5401-5405 - [c255]Koki Yamada, Yuichi Tanaka, Antonio Ortega:
Time-varying Graph Learning Based on Sparseness of Temporal Variation. ICASSP 2019: 5411-5415 - [c254]Basak Güler, Ajinkya Jayawant, Amir Salman Avestimehr, Antonio Ortega:
Robust Graph Signal Sampling. ICASSP 2019: 7520-7524 - [c253]Bagak Güler, Amir Salman Avestimehr, Antonio Ortega:
A Topology-aware Coding Framework for Distributed Graph Processing. ICASSP 2019: 8182-8186 - [c252]Alessandro Gnutti, Fabrizio Guerrini, Riccardo Leonardi, Antonio Ortega:
Coding of Image Intra Prediction Residuals Using Symmetric Graphs. ICIP 2019: 131-135 - [c251]Jiun-Yu Kao, Antonio Ortega, Dong Tian, Hassan Mansour, Anthony Vetro:
Graph Based Skeleton Modeling for Human Activity Analysis. ICIP 2019: 2025-2029 - [c250]Víctor González, Antonio Ortega:
Multi-Resolution Spectral Graph Matching. ICIP 2019: 2319-2323 - [c249]Basak Güler, Amir Salman Avestimehr, Antonio Ortega:
Privacy-Aware Distributed Graph-Based Semi-Supervised Learning. MLSP 2019: 1-6 - [i32]Myriam Bontonou, Carlos Eduardo Rosar Kós Lassance, Ghouthi Boukli Hacene, Vincent Gripon, Jian Tang, Antonio Ortega:
Introducing Graph Smoothness Loss for Training Deep Learning Architectures. CoRR abs/1905.00301 (2019) - [i31]Hilmi E. Egilmez, Yung Hsuan Chao, Antonio Ortega:
Graph-based Transforms for Video Coding. CoRR abs/1909.00952 (2019) - [i30]Carlos Eduardo Rosar Kós Lassance, Vincent Gripon, Jian Tang, Antonio Ortega:
Structural Robustness for Deep Learning Architectures. CoRR abs/1909.05095 (2019) - [i29]Sarath Shekkizhar, Antonio Ortega:
Graph Construction from Data using Non Negative Kernel regression (NNK Graphs). CoRR abs/1910.09383 (2019) - [i28]Carlos Eduardo Rosar Kós Lassance, Myriam Bontonou, Ghouthi Boukli Hacene, Vincent Gripon, Jian Tang, Antonio Ortega:
Deep geometric knowledge distillation with graphs. CoRR abs/1911.03080 (2019) - [i27]Xing Xu, Zahaib Akhtar, Wyatt Lloyd, Antonio Ortega, Ramesh Govindan:
Reducing Storage in Large-Scale Photo Sharing Services using Recompression. CoRR abs/1912.11145 (2019) - 2018
- [j69]Tülay Adali, Antonio Ortega:
Applications of Graph Theory. Proc. IEEE 106(5): 784-786 (2018) - [j68]Antonio Ortega, Pascal Frossard, Jelena Kovacevic, José M. F. Moura, Pierre Vandergheynst:
Graph Signal Processing: Overview, Challenges, and Applications. Proc. IEEE 106(5): 808-828 (2018) - [j67]Eduardo Martínez-Enríquez, Jesús Cid-Sueiro, Fernando Díaz-de-María, Antonio Ortega:
Directional Transforms for Video Coding Based on Lifting on Graphs. IEEE Trans. Circuits Syst. Video Technol. 28(4): 933-946 (2018) - [j66]Eduardo Martínez-Enríquez, Jesús Cid-Sueiro, Fernando Díaz-de-María, Antonio Ortega:
Optimized Update/Prediction Assignment for Lifting Transforms on Graphs. IEEE Trans. Signal Process. 66(8): 2098-2111 (2018) - [j65]Eduardo Pavez, Hilmi E. Egilmez, Antonio Ortega:
Learning Graphs With Monotone Topology Properties and Multiple Connected Components. IEEE Trans. Signal Process. 66(9): 2399-2413 (2018) - [j64]Benjamin Girault, Antonio Ortega, Shrikanth S. Narayanan:
Irregularity-Aware Graph Fourier Transforms. IEEE Trans. Signal Process. 66(21): 5746-5761 (2018) - [c248]David B. H. Tay, Antonio Ortega, Aamir Anis:
Cascade and Lifting Structures in the Spectral Domain for Bipartite Graph Filter Banks. APSIPA 2018: 1141-1147 - [c247]Keng-Shih Lu, Eduardo Pavez, Antonio Ortega:
On Learning Laplacians of Tree Structured Graphs. DSW 2018: 205-209 - [c246]