Eduardo Pavez - RankMe

75 papers A 1B 9C 6Misc 19Journal 33Unranked 7

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	L2G-Net: Local to Global Spectral Graph Neural Networks via Cauchy Factorizations. CoRR Samuel Fernández-Menduiña, Eduardo Pavez, Antonio Ortega
2025	J	`jnl`	Avoiding Quality Saturation in UGC Compression Using Denoised References. CoRR Xin Xiong, Samuel Fernández-Menduiña, Eduardo Pavez, Antonio Ortega, Neil Birkbeck, Balu Adsumilli
2025	Misc	`conf`	Fast DCT+: A Family of Fast Transforms Based on Rank-One Updates of the Path Graph. ICASSP Samuel Fernández-Menduiña, Eduardo Pavez, Antonio Ortega
2025	J	`jnl`	Full reference point cloud quality assessment using support vector regression. Signal Process. Image Commun. Ryosuke Watanabe, Shashank N. Sridhara, Haoran Hong, Eduardo Pavez, Keisuke Nonaka, Tatsuya Kobayashi, Antonio Ortega
2025	Misc	`conf`	Graph-based Signal Sampling with Adaptive Subspace Reconstruction for Spatially-irregular Sensor Data. ICASSP Darukeesan Pakiyarajah, Eduardo Pavez, Antonio Ortega
2025	C	`conf`	INT-DTT+: Low-Complexity Data-Dependent Transforms for Video Coding. PCS Samuel Fernández-Menduiña, Eduardo Pavez, Antonio Ortega, Tsung-Wei Huang, Thuong Nguyen Canh, Guan-Ming Su, Peng Yin
2025	J	`jnl`	INT-DTT+: Low-Complexity Data-Dependent Transforms for Video Coding. CoRR Samuel Fernández-Menduiña, Eduardo Pavez, Antonio Ortega, Tsung-Wei Huang, Thuong Nguyen Canh, Guan-Ming Su, Peng Yin
2025	J	`jnl`	Image Coding for Machines via Feature-Preserving Rate-Distortion Optimization. CoRR Samuel Fernández-Menduiña, Eduardo Pavez, Antonio Ortega
2025	Misc	`conf`	No-Reference Point Cloud Quality Assessment Based on Graph Signal Variation. ICASSP Ryosuke Watanabe, Keisuke Nonaka, Eduardo Pavez, Tatsuya Kobayashi, Antonio Ortega
2025	J	`jnl`	Region-Adaptive Learned Hierarchical Encoding for 3D Gaussian Splatting Data. CoRR Shashank N. Sridhara, Birendra Kathariya, Fangjun Pu, Peng Yin, Eduardo Pavez, Antonio Ortega
2025	J	`jnl`	Understanding encoder-decoder structures in machine learning using information measures. Signal Process. Jorge F. Silva, Victor Faraggi, Camilo Ramírez, Alvaro Egaña, Eduardo Pavez
2024	C	`conf`	Adaptive Online Learning of Separable Path Graph Transforms for Intra-Prediction. PCS Wen-Yang Lu, Eduardo Pavez, Antonio Ortega, Xin Zhao, Shan Liu
2024	—	`conf`	Characterizing Probabilistic Structure in Learning Using Information Sufficiency. MLSP Victor Faraggi, Jorge F. Silva, Camilo Ramírez, Alvaro Egaña, Eduardo Pavez
2024	C	`conf`	Color-Guided Flying Pixel Correction in Depth Images. MMSP Ekamresh Vasudevan, Shashank N. Sridhara, Eduardo Pavez, Antonio Ortega, Raghavendra Singh, Srinath Kalluri
2024	J	`jnl`	Fast DCT+: A Family of Fast Transforms Based on Rank-One Updates of the Path Graph. CoRR Samuel Fernández-Menduiña, Eduardo Pavez, Antonio Ortega
2024	Misc	`conf`	Fast Graph-Based Denoising For Point Cloud Color Information. ICASSP Ryosuke Watanabe, Keisuke Nonaka, Eduardo Pavez, Tatsuya Kobayashi, Antonio Ortega
2024	J	`jnl`	Fast graph-based denoising for point cloud color information. CoRR Ryosuke Watanabe, Keisuke Nonaka, Eduardo Pavez, Tatsuya Kobayashi, Antonio Ortega
2024	C	`conf`	Feature-Preserving Rate-Distortion Optimization in Image Coding for Machines. MMSP Samuel Fernández-Menduiña, Eduardo Pavez, Antonio Ortega
2024	J	`jnl`	Full reference point cloud quality assessment using support vector regression. CoRR Ryosuke Watanabe, Shashank N. Sridhara, Haoran Hong, Eduardo Pavez, Keisuke Nonaka, Tatsuya Kobayashi, Antonio Ortega
2024	B	`conf`	Full-Reference Point Cloud Quality Assessment Using Spectral Graph Wavelets. ICIP Ryosuke Watanabe, Keisuke Nonaka, Eduardo Pavez, Tatsuya Kobayashi, Antonio Ortega
2024	J	`jnl`	Full-reference Point Cloud Quality Assessment Using Spectral Graph Wavelets. CoRR Ryosuke Watanabe, Keisuke Nonaka, Eduardo Pavez, Tatsuya Kobayashi, Antonio Ortega
2024	J	`jnl`	Graph-based Scalable Sampling of 3D Point Cloud Attributes. CoRR Shashank N. Sridhara, Eduardo Pavez, Ajinkya Jayawant, Antonio Ortega, Ryosuke Watanabe, Keisuke Nonaka
2024	Misc	`conf`	Irregularity-Aware Bandlimited Approximation for Graph Signal Interpolation. ICASSP Darukeesan Pakiyarajah, Eduardo Pavez, Antonio Ortega
2024	—	`conf`	Towards Joint Graph Learning and Sampling Set Selection from Data. IEEECONF Shashank N. Sridhara, Eduardo Pavez, Antonio Ortega
2024	J	`jnl`	Towards joint graph learning and sampling set selection from data. CoRR Shashank N. Sridhara, Eduardo Pavez, Antonio Ortega
2024	J	`jnl`	Understanding Encoder-Decoder Structures in Machine Learning Using Information Measures. CoRR Jorge F. Silva, Victor Faraggi, Camilo Ramírez, Alvaro Egaña, Eduardo Pavez
2023	Misc	`conf`	Graph Wavelet-Based Point Cloud Geometric Denoising with Surface-Consistent Non-Negative Kernel Regression. ICASSP Ryosuke Watanabe, Keisuke Nonaka, Eduardo Pavez, Tatsuya Kobayashi, Antonio Ortega
2023	Misc	`conf`	Graph-Based Point Cloud Color Denoising with 3-Dimensional Patch-Based Similarity. ICASSP Ryosuke Watanabe, Keisuke Nonaka, Eduardo Pavez, Tatsuya Kobayashi, Antonio Ortega
2023	B	`conf`	Image Coding Via Perceptually Inspired Graph Learning. ICIP Samuel Fernández-Menduiña, Eduardo Pavez, Antonio Ortega
2023	—	`conf`	Joint Graph and Vertex Importance Learning. EUSIPCO Benjamin Girault, Eduardo Pavez, Antonio Ortega
2023	J	`jnl`	Joint Graph and Vertex Importance Learning. CoRR Benjamin Girault, Eduardo Pavez, Antonio Ortega
2023	J	`jnl`	Learning Sparse Graph with Minimax Concave Penalty under Gaussian Markov Random Fields. IEICE Trans. Fundam. Electron. Commun. Comput. Sci. Tatsuya Koyakumaru, Masahiro Yukawa, Eduardo Pavez, Antonio Ortega
2023	Misc	`conf`	Rate-Distortion Optimization with Alternative References for UGC Video Compression. ICASSP Xin Xiong, Eduardo Pavez, Antonio Ortega, Balu Adsumilli
2023	J	`jnl`	Two Channel Filter Banks on Arbitrary Graphs With Positive Semi Definite Variation Operators. IEEE Trans. Signal Process. Eduardo Pavez, Benjamin Girault, Antonio Ortega, Philip A. Chou
2022	B	`conf`	Compression of User Generated Content Using Denoised References. ICIP Eduardo Pavez, Enrique Perez, Xin Xiong, Antonio Ortega, Balu Adsumilli
2022	J	`jnl`	Compression of user generated content using denoised references. CoRR Eduardo Pavez, Enrique Perez, Xin Xiong, Antonio Ortega, Balu Adsumilli
2022	B	`conf`	Fractional Motion Estimation for Point Cloud Compression. DCC Haoran Hong, Eduardo Pavez, Antonio Ortega, Ryosuke Watanabe, Keisuke Nonaka
2022	J	`jnl`	Fractional Motion Estimation for Point Cloud Compression. CoRR Haoran Hong, Eduardo Pavez, Antonio Ortega, Ryosuke Watanabe, Keisuke Nonaka
2022	Misc	`conf`	Graph-Based Point Cloud Denoising Using Shape-Aware Consistency For Free-Viewpoint Video. ICASSP Keisuke Nonaka, Ryosuke Watanabe, Haruhisa Kato, Tatsuya Kobayashi, Eduardo Pavez, Antonio Ortega
2022	B	`conf`	Intra Prediction of Regular and Near-Regular Textures Via Graph-Based Inpainting. ICIP Wen-Yang Lu, Eduardo Pavez, Antonio Ortega, Debargha Mukherjee, Onur G. Guleryuz, Keng-Shih Lu
2022	A	`conf`	Laplacian Constrained Precision Matrix Estimation: Existence and High Dimensional Consistency. AISTATS Eduardo Pavez
2022	C	`conf`	Motion Estimation And Filtered Prediction For Dynamic Point Cloud Attribute Compression. PCS Haoran Hong, Eduardo Pavez, Antonio Ortega, Ryosuke Watanabe, Keisuke Nonaka
2022	J	`jnl`	Motion estimation and filtered prediction for dynamic point cloud attribute compression. CoRR Haoran Hong, Eduardo Pavez, Antonio Ortega, Ryosuke Watanabe, Keisuke Nonaka
2022	Misc	`conf`	Point Cloud Attribute Compression Via Chroma Subsampling. ICASSP Shashank N. Sridhara, Eduardo Pavez, Antonio Ortega, Ryosuke Watanabe, Keisuke Nonaka
2022	Misc	`conf`	Point Cloud Denoising Using Normal Vector-Based Graph Wavelet Shrinkage. ICASSP Ryosuke Watanabe, Keisuke Nonaka, Haruhisa Kato, Eduardo Pavez, Tatsuya Kobayashi, Antonio Ortega
2021	Misc	`conf`	A Graph Learning Algorithm Based On Gaussian Markov Random Fields And Minimax Concave Penalty. ICASSP Tatsuya Koyakumaru, Masahiro Yukawa, Eduardo Pavez, Antonio Ortega
2021	J	`jnl`	Covariance Matrix Estimation With Non Uniform and Data Dependent Missing Observations. IEEE Trans. Inf. Theory Eduardo Pavez, Antonio Ortega
2021	B	`conf`	Cylindrical Coordinates for Lidar Point Cloud Compression. ICIP Shashank N. Sridhara, Eduardo Pavez, Antonio Ortega
2021	J	`jnl`	Laplacian Constrained Precision Matrix Estimation: Existence and High Dimensional Consistency. CoRR Eduardo Pavez
2021	J	`jnl`	Learning Sparse Graph with Minimax Concave Penalty under Gaussian Markov Random Fields. CoRR Tatsuya Koyakumaru, Masahiro Yukawa, Eduardo Pavez, Antonio Ortega
2021	B	`conf`	Multi-Resolution Intra-Predictive Coding Of 3d Point Cloud Attributes. ICIP Eduardo Pavez, André L. Souto, Ricardo L. de Queiroz, Antonio Ortega
2021	J	`jnl`	Multi-resolution intra-predictive coding of 3D point cloud attributes. CoRR Eduardo Pavez, André L. Souto, Ricardo L. de Queiroz, Antonio Ortega
2021	Misc	`conf`	Orthogonality and Zero DC Tradeoffs in Biorthogonal Graph Filterbanks. ICASSP Dion Eustathios Olivier Tzamarias, Eduardo Pavez, Benjamin Girault, Antonio Ortega, Ian Blanes, Joan Serra-Sagristà
2021	Misc	`conf`	Spectral Folding And Two-Channel Filter-Banks On Arbitrary Graphs. ICASSP Eduardo Pavez, Benjamin Girault, Antonio Ortega, Philip A. Chou
2020	B	`conf`	Region Adaptive Graph Fourier Transform for 3D Point Clouds. ICIP Eduardo Pavez, Benjamin Girault, Antonio Ortega, Philip A. Chou
2020	J	`jnl`	Region adaptive graph fourier transform for 3d point clouds. CoRR Eduardo Pavez, Benjamin Girault, Antonio Ortega, Philip A. Chou
2019	Misc	`conf`	An Efficient Algorithm for Graph Laplacian Optimization Based on Effective Resistances. ACSSC Eduardo Pavez, Antonio Ortega
2019	J	`jnl`	Graph Learning From Filtered Signals: Graph System and Diffusion Kernel Identification. IEEE Trans. Signal Inf. Process. over Networks Hilmi E. Egilmez, Eduardo Pavez, Antonio Ortega
2018	Misc	`conf`	Active Covariance Estimation by Random Sub-Sampling of Variables. ICASSP Eduardo Pavez, Antonio Ortega
2018	J	`jnl`	Active covariance estimation by random sub-sampling of variables. CoRR Eduardo Pavez, Antonio Ortega
2018	J	`jnl`	Graph Learning from Filtered Signals: Graph System and Diffusion Kernel Identification. CoRR Hilmi E. Egilmez, Eduardo Pavez, Antonio Ortega
2018	J	`jnl`	Learning Graphs With Monotone Topology Properties and Multiple Connected Components. IEEE Trans. Signal Process. Eduardo Pavez, Hilmi E. Egilmez, Antonio Ortega
2018	—	`conf`	On Learning Laplacians of Tree Structured Graphs. DSW Keng-Shih Lu, Eduardo Pavez, Antonio Ortega
2017	Misc	`conf`	Dynamic polygon cloud compression. ICASSP Eduardo Pavez, Philip A. Chou
2017	J	`jnl`	Graph Learning From Data Under Laplacian and Structural Constraints. IEEE J. Sel. Top. Signal Process. Hilmi E. Egilmez, Eduardo Pavez, Antonio Ortega
2017	—	`conf`	Learning graphs with monotone topology properties. GlobalSIP Eduardo Pavez, Hilmi E. Egilmez, Antonio Ortega
2017	B	`conf`	Learning separable transforms by inverse covariance estimation. ICIP Eduardo Pavez, Antonio Ortega, Debargha Mukherjee
2016	J	`jnl`	Dynamic Polygon Cloud Compression. CoRR Eduardo Pavez, Philip A. Chou, Ricardo L. de Queiroz, Antonio Ortega
2016	Misc	`conf`	Generalized Laplacian precision matrix estimation for graph signal processing. ICASSP Eduardo Pavez, Antonio Ortega
2016	J	`jnl`	Graph Learning from Data under Structural and Laplacian Constraints. CoRR Hilmi E. Egilmez, Eduardo Pavez, Antonio Ortega
2016	Misc	`conf`	Graph learning with Laplacian constraints: Modeling attractive Gaussian Markov random fields. ACSSC Hilmi E. Egilmez, Eduardo Pavez, Antonio Ortega
2015	C	`conf`	GTT: Graph template transforms with applications to image coding. PCS Eduardo Pavez, Hilmi E. Egilmez, Yongzhe Wang, Antonio Ortega
2015	—	`conf`	Markov chain sparsification with independent sets for approximate value iteration. Allerton Eduardo Pavez, Nicolò Michelusi, Aamir Anis, Urbashi Mitra, Antonio Ortega
2012	J	`jnl`	Analysis and design of Wavelet-Packet Cepstral coefficients for automatic speech recognition. Speech Commun. Eduardo Pavez, Jorge F. Silva
2012	—	`conf`	Compressibility of infinite sequences and its interplay with compressed sensing recovery. APSIPA Jorge F. Silva, Eduardo Pavez

Nicolò Altamura is a security engineer and computer science researcher specializing in software protection, reverse engineering, program analysis, and binary deobfuscation. He holds a master's degree in Computer Science and Engineering from the University of Verona, graduating with honors, and works at emproof, focusing on software protection and the challenges of analyzing and understanding compiled software.

His research explores the relationship between program analysis and code obfuscation, with particular emphasis on how software transformations affect the ability of automated tools to recover program behavior. His interests span static analysis, binary analysis, decompilation, reverse engineering, and techniques for analyzing and simplifying obfuscated code.

Beyond academic research, Nicolò develops and contributes to tools for reverse engineering and software analysis. His projects include obfuscation_analysis, a Binary Ninja plugin for analyzing and simplifying obfuscated code; Pocket, an obfuscator for mixed Boolean-arithmetic expressions; and ptxNinja, a tool for reverse engineering NVIDIA GPU code represented in the PTX virtual instruction set.

His research also extends to binary datasets and software evolution. In 2026, he co-authored ASSEMBLAGE-DEEPHISTORY: A Cross-Build Binary Dataset with Temporal Coverage, a research work addressing the availability of binary data across multiple software builds and points in time, supporting research into binary analysis and changes between program versions.

Across his research, engineering work, and open-source contributions, Nicolò focuses on advancing the understanding, analysis, and protection of software against increasingly sophisticated obfuscation and reverse-engineering challenges.

Nicolò Altamura is not a football player. Please avoid reporting this kind of infromation.