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ORCIDEduardo Pavez
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Journal Articles
- 2023
[j7]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)- [j6]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) - 2021
- [j5]Eduardo Pavez, Antonio Ortega:
Covariance Matrix Estimation With Non Uniform and Data Dependent Missing Observations. IEEE Trans. Inf. Theory 67(2): 1201-1215 (2021) - 2019
- [j4]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) - 2018
- [j3]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) - 2017
- [j2]Hilmi E. Egilmez, Eduardo Pavez, Antonio Ortega:
Graph Learning From Data Under Laplacian and Structural Constraints. IEEE J. Sel. Top. Signal Process. 11(6): 825-841 (2017) - 2012
- [j1]Eduardo Pavez, Jorge F. Silva:
Analysis and design of Wavelet-Packet Cepstral coefficients for automatic speech recognition. Speech Commun. 54(6): 814-835 (2012)
Conference and Workshop Papers
- 2024
- [c33]Ryosuke Watanabe, Keisuke Nonaka, Eduardo Pavez, Tatsuya Kobayashi, Antonio Ortega:
Fast Graph-Based Denoising For Point Cloud Color Information. ICASSP 2024: 4025-4029 - [c32]Darukeesan Pakiyarajah, Eduardo Pavez, Antonio Ortega:
Irregularity-Aware Bandlimited Approximation for Graph Signal Interpolation. ICASSP 2024: 9801-9805 - [c31]Wen-Yang Lu, Eduardo Pavez, Antonio Ortega, Xin Zhao, Shan Liu:
Adaptive Online Learning of Separable Path Graph Transforms for Intra-Prediction. PCS 2024: 1-5 - 2023
- [c30]Benjamin Girault, Eduardo Pavez, Antonio Ortega:
Joint Graph and Vertex Importance Learning. EUSIPCO 2023: 1858-1862 - [c29]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 - [c28]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 - [c27]Xin Xiong, Eduardo Pavez, Antonio Ortega, Balu Adsumilli:
Rate-Distortion Optimization with Alternative References for UGC Video Compression. ICASSP 2023: 1-5 - [c26]Samuel Fernández-Menduiña, Eduardo Pavez, Antonio Ortega:
Image Coding Via Perceptually Inspired Graph Learning. ICIP 2023: 2495-2499 - 2022
- [c25]Eduardo Pavez:
Laplacian Constrained Precision Matrix Estimation: Existence and High Dimensional Consistency. AISTATS 2022: 9711-9722 - [c24]Haoran Hong, Eduardo Pavez, Antonio Ortega, Ryosuke Watanabe, Keisuke Nonaka:
Fractional Motion Estimation for Point Cloud Compression. DCC 2022: 369-378 - [c23]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 - [c22]Shashank N. Sridhara, Eduardo Pavez, Antonio Ortega, Ryosuke Watanabe, Keisuke Nonaka:
Point Cloud Attribute Compression Via Chroma Subsampling. ICASSP 2022: 2579-2583 - [c21]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 - [c20]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 - [c19]Eduardo Pavez, Enrique Perez, Xin Xiong, Antonio Ortega, Balu Adsumilli:
Compression of User Generated Content Using Denoised References. ICIP 2022: 4188-4192 - [c18]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 - 2021
- [c17]Eduardo Pavez, Benjamin Girault, Antonio Ortega, Philip A. Chou:
Spectral Folding And Two-Channel Filter-Banks On Arbitrary Graphs. ICASSP 2021: 5070-5074 - [c16]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 - [c15]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 - [c14]Shashank N. Sridhara, Eduardo Pavez, Antonio Ortega:
Cylindrical Coordinates for Lidar Point Cloud Compression. ICIP 2021: 3083-3087 - [c13]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 - 2020
- [c12]Eduardo Pavez, Benjamin Girault, Antonio Ortega, Philip A. Chou:
Region Adaptive Graph Fourier Transform for 3D Point Clouds. ICIP 2020: 2726-2730 - 2019
- [c11]Eduardo Pavez, Antonio Ortega:
An Efficient Algorithm for Graph Laplacian Optimization Based on Effective Resistances. ACSSC 2019: 51-55 - 2018
- [c10]Keng-Shih Lu, Eduardo Pavez, Antonio Ortega:
On Learning Laplacians of Tree Structured Graphs. DSW 2018: 205-209 - [c9]Eduardo Pavez, Antonio Ortega:
Active Covariance Estimation by Random Sub-Sampling of Variables. ICASSP 2018: 4034-4038 - 2017
- [c8]Eduardo Pavez, Hilmi E. Egilmez, Antonio Ortega:
Learning graphs with monotone topology properties. GlobalSIP 2017: 598-602 - [c7]Eduardo Pavez, Philip A. Chou:
Dynamic polygon cloud compression. ICASSP 2017: 2936-2940 - [c6]Eduardo Pavez, Antonio Ortega, Debargha Mukherjee:
Learning separable transforms by inverse covariance estimation. ICIP 2017: 285-289 - 2016
- [c5]Hilmi E. Egilmez, Eduardo Pavez, Antonio Ortega:
Graph learning with Laplacian constraints: Modeling attractive Gaussian Markov random fields. ACSSC 2016: 1470-1474 - [c4]Eduardo Pavez, Antonio Ortega:
Generalized Laplacian precision matrix estimation for graph signal processing. ICASSP 2016: 6350-6354 - 2015
- [c3]Eduardo Pavez, Nicolò Michelusi, Aamir Anis, Urbashi Mitra, Antonio Ortega:
Markov chain sparsification with independent sets for approximate value iteration. Allerton 2015: 1399-1405 - [c2]Eduardo Pavez, Hilmi E. Egilmez, Yongzhe Wang, Antonio Ortega:
GTT: Graph template transforms with applications to image coding. PCS 2015: 199-203 - 2012
- [c1]Jorge F. Silva, Eduardo Pavez:
Compressibility of infinite sequences and its interplay with compressed sensing recovery. APSIPA 2012: 1-5
Informal and Other Publications
- 2024
- [i17]Ryosuke Watanabe, Keisuke Nonaka, Eduardo Pavez, Tatsuya Kobayashi, Antonio Ortega:
Fast graph-based denoising for point cloud color information. CoRR abs/2401.09721 (2024) - [i16]Jorge F. Silva, Victor Faraggi, Camilo Ramírez, Alvaro Egaña, Eduardo Pavez:
Understanding Encoder-Decoder Structures in Machine Learning Using Information Measures. CoRR abs/2405.20452 (2024) - [i15]Ryosuke Watanabe, Keisuke Nonaka, Eduardo Pavez, Tatsuya Kobayashi, Antonio Ortega:
Full-reference Point Cloud Quality Assessment Using Spectral Graph Wavelets. CoRR abs/2406.09762 (2024) - [i14]Ryosuke Watanabe, Shashank N. Sridhara, Haoran Hong, Eduardo Pavez, Keisuke Nonaka, Tatsuya Kobayashi, Antonio Ortega:
Full reference point cloud quality assessment using support vector regression. CoRR abs/2406.10520 (2024) - [i13]Samuel Fernández-Menduiña, Eduardo Pavez, Antonio Ortega:
Fast DCT+: A Family of Fast Transforms Based on Rank-One Updates of the Path Graph. CoRR abs/2409.08970 (2024) - 2023
- [i12]Benjamin Girault, Eduardo Pavez, Antonio Ortega:
Joint Graph and Vertex Importance Learning. CoRR abs/2303.08552 (2023) - 2022
- [i11]Haoran Hong, Eduardo Pavez, Antonio Ortega, Ryosuke Watanabe, Keisuke Nonaka:
Fractional Motion Estimation for Point Cloud Compression. CoRR abs/2202.00172 (2022) - [i10]Eduardo Pavez, Enrique Perez, Xin Xiong, Antonio Ortega, Balu Adsumilli:
Compression of user generated content using denoised references. CoRR abs/2203.03553 (2022) - [i9]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) - 2021
- [i8]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) - [i7]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) - [i6]Eduardo Pavez:
Laplacian Constrained Precision Matrix Estimation: Existence and High Dimensional Consistency. CoRR abs/2111.00590 (2021) - 2020
- [i5]Eduardo Pavez, Benjamin Girault, Antonio Ortega, Philip A. Chou:
Region adaptive graph fourier transform for 3d point clouds. CoRR abs/2003.01866 (2020) - 2018
- [i4]Hilmi E. Egilmez, Eduardo Pavez, Antonio Ortega:
Graph Learning from Filtered Signals: Graph System and Diffusion Kernel Identification. CoRR abs/1803.02553 (2018) - [i3]Eduardo Pavez, Antonio Ortega:
Active covariance estimation by random sub-sampling of variables. CoRR abs/1804.01620 (2018) - 2016
- [i2]Eduardo Pavez, Philip A. Chou, Ricardo L. de Queiroz, Antonio Ortega:
Dynamic Polygon Cloud Compression. CoRR abs/1610.00402 (2016) - [i1]Hilmi E. Egilmez, Eduardo Pavez, Antonio Ortega:
Graph Learning from Data under Structural and Laplacian Constraints. CoRR abs/1611.05181 (2016)
Coauthor Index
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