Achiya Dax - RankMe

26 papers Journal 25

Year	Rank	Type	Title / Venue / Authors
2024	J	`jnl`	A compact Heart iteration for low-rank approximations of large matrices. J. Comput. Appl. Math. Achiya Dax
2022	J	`jnl`	The Rate of Convergence of the SOR Method in the Positive Semidefinite Case. Comput. Math. Methods Achiya Dax
2022	J	`jnl`	The Smallest Singular Value Anomaly and the Condition Number Anomaly. Axioms Achiya Dax
2020	J	`jnl`	A cross-product approach for low-rank approximations of large matrices. J. Comput. Appl. Math. Achiya Dax
2019	J	`jnl`	A restarted Krylov method with inexact inversions. Numer. Linear Algebra Appl. Achiya Dax
2017	J	`jnl`	A gradual rank increasing process for matrix completion. Numer. Algorithms Achiya Dax
2010	J	`jnl`	A minimum norm approach for low-rank approximations of a matrix. J. Comput. Appl. Math. Achiya Dax
2009	J	`jnl`	A New Class of Minimum Norm Duality Theorems. SIAM J. Optim. Achiya Dax
2009	J	`jnl`	A hybrid algorithm for solving linear inequalities in a least squares sense. Numer. Algorithms Achiya Dax
2008	J	`jnl`	Orthogonalization Via Deflation: A Minimum Norm Approach for Low-Rank Approximations of a Matrix. SIAM J. Matrix Anal. Appl. Achiya Dax
2006	J	`jnl`	The Comput. Stat. Data Anal. Achiya Dax
2004	J	`jnl`	A Modified Iterative Refinement Scheme. SIAM J. Sci. Comput. Achiya Dax
2004	J	`jnl`	Computing projections via Householder transformations and Gram-Schmidt orthogonalizations. Numer. Linear Algebra Appl. Achiya Dax
1998	J	`jnl`	Approximating minimum norm solutions of rank-deficient least squares problems. Numer. Linear Algebra Appl. Achiya Dax, Lars Eldén
1997	J	`jnl`	Classroom Note: An Elementary Proof of Farkas' Lemma. SIAM Rev. Achiya Dax
1994	J	`jnl`	A row relaxation method for large ℓ Numer. Linear Algebra Appl. Achiya Dax
1993	J	`jnl`	On Row Relaxation Methods for Large Constrained Least Squares Problems. SIAM J. Sci. Comput. Achiya Dax
1993	J	`jnl`	The relationship between theorems of the alternative, least norm problems, steepest descent directions, and degeneracy: A review. Ann. Oper. Res. Achiya Dax
1992	J	`jnl`	On Regularized Least Norm Problems. SIAM J. Optim. Achiya Dax
1991	J	`jnl`	On computational aspects of bounded linear least squares problems. ACM Trans. Math. Softw. Achiya Dax
1990	J	`jnl`	A New Theorem of the Alternative. Math. Program. Achiya Dax
1990	J	`jnl`	Column Relaxation Methods for Least Norm Problems. SIAM J. Sci. Comput. Achiya Dax, Brian Berkowitz
1990	J	`jnl`	The Convergence of Linear Stationary Iterative Processes for Solving Singular Unstructured Systems of Linear Equations. SIAM Rev. Achiya Dax
1986	J	`jnl`	A note on optimality conditions for the Euclidean. Multifacility location problem. Math. Program. Achiya Dax
1982	J	`jnl`	Partial pivoting strategies for symmetric gaussian elimination. Math. Program. Achiya Dax
1978	—	`—`	הפרוק של מטריצה סימטרית ושימושים באופטימיזציה לא לינארית (The decomposition of a symmetric matrix and applications in nonlinear optimization.). Achiya Dax

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.