Publications
You can also find my papers on Google Scholar and arXiv
2026
S. Fernández-Menduina, H. Choi, F. Racapé, E. Pavez, A. Ortega. Wrapper-Aware Rate-Distortion Optimization in Feature Coding for Machines. IEEE ICASSP 2026
S. N. Sridhara, B. Kathariya, F. Pu, P. Yin, E. Pavez, A. Ortega. Region-Adaptive Learned Hierarchical Encoding for 3D Gaussian Splatting Data. DCC 2026
S. N. Sridhara, E. Pavez, A. Jayawant, A. Ortega, R. Watanabe, K. Nonaka. Graph-based Scalable Sampling of 3D Point Cloud Attributes. arXiv.
preprintX. Xiong, S. Fernández-Menduina, E. Pavez, A. Ortega, N. Birkbeck, B. Adsumilli. Avoiding Quality Saturation in UGC Compression Using Denoised References. arXiv.
preprint
2025
Journals
S. Fernández-Menduina, E. Pavez, A. Ortega. Image Coding for Machines via Feature-Preserving Rate-Distortion Optimization. IEEE Transactions on Multimedia, 2025
J. F. Silva, V. Faraggi, C. Ramírez, A. Egaña, E. Pavez. Understanding Encoder–Decoder Structures in Machine Learning Using Information Measures. Signal Processing, 2025
Conferences
S. Fernández-Menduina, E. Pavez, A. Ortega. INT-DTT+: Low-Complexity Data-Dependent Transforms for Video Coding. IEEE PCS 2025
Best Paper Award – 2nd placeC. Wang, S. N. Sridhara, E. Pavez, A. Ortega, C. Chang. Adaptive Voxelization for Transform Coding of 3D Gaussian Splatting Data. IEEE ICIP 2025
S. Fernández-Menduina, X. Xiong, E. Pavez, A. Ortega, N. Birkbeck, B. Adsumilli. Rate-Distortion Optimization with Non-Reference Metrics for UGC Compression. IEEE ICIP 2025
D. Pakiyarajah, E. Pavez, A. Ortega, D. Mukherjee, O. Guleryuz, W.-Y. Lu, K. K. Sivakumar. Joint Optimization of Primary and Secondary Transforms Using Rate-Distortion Optimized Transform Design. IEEE ICIP 2025
Spotlight PaperS. Fernández-Menduina, E. Pavez, A. Ortega. Fast DCT+: A Family of Fast Transforms Based on Rank-One Updates of the Path Graph. IEEE ICASSP 2025
D. Pakiyarajah, E. Pavez, A. Ortega. Graph-Based Signal Sampling with Adaptive Subspace Reconstruction. IEEE ICASSP 2025
R. Watanabe, K. Nonaka, E. Pavez, T. Kobayashi, A. Ortega. No-Reference Point Cloud Quality Assessment Based on Graph Signal Variation. IEEE ICASSP 2025
2024
Journals
- R. Watanabe, S. N. Sridhara, H. Hong, E. Pavez, A. Ortega. Full Reference Point Cloud Quality Assessment Using Support Vector Regression. Signal Processing: Image Communication, 2024
Conferences
S. N. Sridhara, E. Pavez, A. Ortega. Joint Graph Learning and Sampling Set Selection from Data. Asilomar 2024 (Invited)
V. Faraggi, J. Silva, C. Ramírez, E. Pavez. Characterizing Probabilistic Structure in Learning Using Information Sufficiency. IEEE MLSP 2024
W.-Y. Lu, E. Pavez, A. Ortega, X. Zhao, S. Liu. Online-Learned Graph Transforms for Adaptive Blocksize Intra-Predictive Coding. SPIE 2024
S. Fernández-Menduina, E. Pavez, A. Ortega. Feature-Preserving Rate-Distortion Optimization in Image Coding for Machines. IEEE MMSP 2024
Best Paper AwardE. Vasudevan, S. N. Sridhara, E. Pavez, A. Ortega, S. Kalluri, R. Singh. Color-Guided Flying Pixel Correction in Depth Images. IEEE MMSP 2024
R. Watanabe, K. Nonaka, E. Pavez, T. Kobayashi, A. Ortega. Full-Reference Point Cloud Quality Assessment Using Spectral Graph Wavelets. IEEE ICIP 2024
Best Paper AwardW.-Y. Lu, E. Pavez, A. Ortega, X. Zhao, S. Liu. Adaptive Online Learning of Separable Path Graph Transforms. PCS 2024
D. Pakiyarajah, E. Pavez, A. Ortega. Irregularity-Aware Band-Limited Approximation for Graph Signal Interpolation. IEEE ICASSP 2024
R. Watanabe, K. Nonaka, E. Pavez, T. Kobayashi, A. Ortega. Fast Graph-Based Denoising for Point Cloud Color Information. IEEE ICASSP 2024
2023
Journals
- E. Pavez, B. Girault, A. Ortega, P. A. Chou. Two-Channel Filter Banks on Arbitrary Graphs with Positive Semi-Definite Variation Operators. IEEE Transactions on Signal Processing, 2023
Conferences
R. Watanabe, S. N. Sridhara, H. Hong, E. Pavez, A. Ortega. ICIP 2023 Challenge on Point Cloud Quality Assessment. IEEE ICIP 2023
S. Fernández-Menduina, E. Pavez, A. Ortega. Image Coding via Perceptually Inspired Graph Learning. IEEE ICIP 2023
B. Girault, E. Pavez, A. Ortega. Joint Graph and Vertex Importance Learning. EUSIPCO 2023
X. Xiong, E. Pavez, A. Ortega, B. Adsumilli. Rate-Distortion Optimization for UGC Video Compression. IEEE ICASSP 2023
R. Watanabe, K. Nonaka, E. Pavez, T. Kobayashi, A. Ortega. Graph-Based Point Cloud Color Denoising. IEEE ICASSP 2023
R. Watanabe, K. Nonaka, E. Pavez, T. Kobayashi, A. Ortega. Graph Wavelet-Based Geometry Denoising for Point Clouds. IEEE ICASSP 2023
Top 3% Paper
2022
Journals
- T. Koyakumaru, M. Yukawa, E. Pavez, A. Ortega. Learning Sparse Graphs with Minimax Concave Penalty. IEICE Transactions, 2022
Conferences
H. Hong, E. Pavez, A. Ortega, R. Watanabe, K. Nonaka. Motion Estimation and Filtered Prediction. PCS 2022
E. Pavez, E. Perez, X. Xiong, A. Ortega, B. Adsumilli. Compression of User Generated Content Using Denoised References. IEEE ICIP 2022
Best Paper Award – 2nd Runner-UpW.-Y. Lu, E. Pavez, A. Ortega, D. Mukherjee, O. Guleryuz, K.-S. Lu. Intra Prediction via Graph-Based Inpainting. IEEE ICIP 2022
E. Pavez. Laplacian Constrained Precision Matrix Estimation. AISTATS 2022
H. Hong, E. Pavez, A. Ortega, R. Watanabe, K. Nonaka. Fractional Motion Estimation. DCC 2022
S. N. Sridhara, E. Pavez, R. Watanabe, K. Nonaka, A. Ortega. Point Cloud Attribute Compression via Chroma Subsampling. IEEE ICASSP 2022
R. Watanabe, K. Nonaka, H. Kato, E. Pavez, T. Kobayashi, A. Ortega. Point Cloud Denoising via Graph Wavelets. IEEE ICASSP 2022
K. Nonaka, R. Watanabe, T. Kobayashi, E. Pavez, A. Ortega. Graph-Based Point Cloud Denoising via Shape Consistency. IEEE ICASSP 2022
2021
Journals
- E. Pavez, A. Ortega. Covariance Matrix Estimation with Non-Uniform and Data-Dependent Missing Observations. IEEE Transactions on Information Theory, 2021
Conferences
E. Pavez, A. L. Souto, R. L. De Queiroz, A. Ortega. Multi-Resolution Intra-Predictive Coding. IEEE ICIP 2021
S. N. Sridhara, E. Pavez, A. Ortega. Cylindrical Coordinates for Lidar Point Cloud Compression. IEEE ICIP 2021
E. Pavez, B. Girault, A. Ortega, P. A. Chou. Spectral Folding and Graph Filter Banks. IEEE ICASSP 2021
D. E. O. Tzamarias et al. Biorthogonal Graph Filterbanks. IEEE ICASSP 2021
T. Koyakumaru et al. Graph Learning via MCP. IEEE ICASSP 2021
2020
- E. Pavez, B. Girault, A. Ortega, P. A. Chou. Region Adaptive Graph Fourier Transform for 3D Point Clouds. IEEE ICIP 2020
Best Paper Award
2019
- E. Pavez, A. Ortega. Efficient Algorithm for Graph Laplacian Optimization. Asilomar 2019 (Invited)
2018
Journals
E. Pavez, H. E. Egilmez, A. Ortega. Learning Graphs with Monotone Topology Properties and Multiple Connected Components. IEEE Transactions on Signal Processing, 2018
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preprintE. Pavez, P. A. Chou, R. L. De Queiroz, A. Ortega. Dynamic Polygon Clouds: Representation and Compression for VR/AR. APSIPA Transactions, 2018
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Conferences
K.-S. Lu, E. Pavez, A. Ortega. On Learning Laplacians of Tree Structured Graphs. IEEE DSW 2018
paperE. Pavez, A. Ortega. Active Covariance Estimation by Random Sub-Sampling of Variables. IEEE ICASSP 2018
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preprint
2017
Journals
- H. E. Egilmez, E. Pavez, A. Ortega. Graph Learning from Data under Laplacian and Structural Constraints. IEEE JSTSP, 2017
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preprint
Conferences
E. Pavez, H. E. Egilmez, A. Ortega. Learning Graphs with Monotone Topology Properties. GlobalSIP 2017
paperE. Pavez, A. Ortega, D. Mukherjee. Learning Separable Transforms by Inverse Covariance Estimation. IEEE ICIP 2017
paperE. Pavez, P. A. Chou. Dynamic Polygon Cloud Compression. IEEE ICASSP 2017
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2016
H. E. Egilmez, E. Pavez, A. Ortega. Graph Learning with Laplacian Constraints. Asilomar 2016
paperE. Pavez, A. Ortega. Generalized Laplacian Precision Matrix Estimation. IEEE ICASSP 2016
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2015
E. Pavez, N. Michelusi, A. Anis, U. Mitra, A. Ortega. Markov Chain Sparsification with Independent Sets for Approximate Value Iteration. Allerton 2015
paperE. Pavez, H. E. Egilmez, Y. Wang, A. Ortega. GTT: Graph Template Transforms with Applications to Image Coding. PCS 2015
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Best Student Paper Runner-Up
