Fabien Lauer - RankMe

48 papers A* 1A 1B 1C 2Journal 31Unranked 10

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Uniform error bounds for quantized dynamical models. CoRR Abdelkader Metakalard, Fabien Lauer, Kévin Colin, Marion Gilson
2026	J	`jnl`	Uniform error bounds for quantized dynamical models. IFAC J. Syst. Control. Abdelkader Metakalard, Fabien Lauer, Kévin Colin, Marion Gilson
2024	J	`jnl`	Margin-Based Scenario Approach to Robust Optimization in High Dimension. IEEE Trans. Autom. Control. Fabien Lauer
2023	J	`jnl`	Uniform Risk Bounds for Learning with Dependent Data Sequences. CoRR Fabien Lauer
2022	J	`jnl`	A statistical learning perspective on switched linear system identification. Autom. Louis Massucci, Fabien Lauer, Marion Gilson
2021	—	`conf`	Regularized Switched System Identification: a Statistical Learning Perspective. ADHS Louis Massucci, Fabien Lauer, Marion Gilson
2020	J	`jnl`	Error Bounds for Piecewise Smooth and Switching Regression. IEEE Trans. Neural Networks Learn. Syst. Fabien Lauer
2020	A	`conf`	Risk Bounds for Learning Multiple Components with Permutation-Invariant Losses. AISTATS Fabien Lauer
2020	—	`conf`	Structural Risk Minimization for Switched System Identification. CDC Louis Massucci, Fabien Lauer, Marion Gilson
2019	—	`book`	Optimization and statistical learning theory for piecewise smooth and switching regression. (Optimisation et théorie statistique de l'apprentissage pour la régression douce par morceaux et à commutations). Fabien Lauer
2019	J	`jnl`	Rademacher complexity and generalization performance of multi-category margin classifiers. Neurocomputing Khadija Musayeva, Fabien Lauer, Yann Guermeur
2019	J	`jnl`	Risk Bounds for Learning Multiple Components with Permutation-Invariant Losses. CoRR Fabien Lauer
2018	B	`conf`	A sharper bound on the Rademacher complexity of margin multi-category classifiers. ESANN Khadija Musayeva, Fabien Lauer, Yann Guermeur
2018	J	`jnl`	Global optimization for low-dimensional switching linear regression and bounded-error estimation. Autom. Fabien Lauer
2018	J	`jnl`	MLweb: A toolkit for machine learning on the web. Neurocomputing Fabien Lauer
2018	J	`jnl`	On the exact minimization of saturated loss functions for robust regression and subspace estimation. CoRR Fabien Lauer
2018	J	`jnl`	On the exact minimization of saturated loss functions for robust regression and subspace estimation. Pattern Recognit. Lett. Fabien Lauer
2017	J	`jnl`	Error Bounds for Piecewise Smooth and Switching Regression. CoRR Fabien Lauer
2017	J	`jnl`	Global optimization for low-dimensional switching linear regression and bounded-error estimation. CoRR Fabien Lauer
2016	J	`jnl`	On the complexity of switching linear regression. Autom. Fabien Lauer
2015	—	`conf`	Efficient Optimization of Multi-class Support Vector Machines with MSVMpack. MCO (2) Emmanuel Didiot, Fabien Lauer
2015	J	`jnl`	Finding sparse solutions of systems of polynomial equations via group-sparsity optimization. J. Glob. Optim. Fabien Lauer, Henrik Ohlsson
2015	J	`jnl`	On the complexity of piecewise affine system identification. Autom. Fabien Lauer
2015	J	`jnl`	On the complexity of piecewise affine system identification. CoRR Fabien Lauer
2015	J	`jnl`	On the complexity of switching linear regression. CoRR Fabien Lauer
2014	J	`jnl`	A Difference of Convex Functions Algorithm for Switched Linear Regression. IEEE Trans. Autom. Control. Tao Pham Dinh, Le Hoai Minh, Hoai An Le Thi, Fabien Lauer
2014	—	`conf`	Piecewise smooth system identification in reproducing kernel Hilbert space. CDC Fabien Lauer, Gérard Bloch
2014	J	`jnl`	Selective ℓ IEEE Trans. Autom. Control. Van Luong Le, Fabien Lauer, Gérard Bloch
2014	J	`jnl`	Sparse phase retrieval via group-sparse optimization. CoRR Fabien Lauer, Henrik Ohlsson
2013	J	`jnl`	Finding sparse solutions of systems of polynomial equations via group-sparsity optimization. CoRR Fabien Lauer, Henrik Ohlsson
2013	C	`conf`	Identification of MIMO switched state-space models. ACC Laurent Bako, Van Luong Le, Fabien Lauer, Gérard Bloch
2013	C	`conf`	Identification of linear hybrid systems: A geometric approach. ACC Van Luong Le, Fabien Lauer, Gérard Bloch
2013	—	`conf`	Learning nonlinear hybrid systems: from sparse optimization to support vector regression. HSCC Van Luong Le, Fabien Lauer, Laurent Bako, Gérard Bloch
2012	—	`conf`	Cascading Discriminant and Generative Models for Protein Secondary Structure Prediction. PRIB Fabienne Thomarat, Fabien Lauer, Yann Guermeur
2012	—	`conf`	Learning smooth models of nonsmooth functions via convex optimization. MLSP Fabien Lauer, Van Luong Le, Gérard Bloch
2011	J	`jnl`	A continuous optimization framework for hybrid system identification. Autom. Fabien Lauer, Gérard Bloch, René Vidal
2011	J	`jnl`	MSVMpack: A Multi-Class Support Vector Machine Package. J. Mach. Learn. Res. Fabien Lauer, Yann Guermeur
2011	J	`jnl`	Reduced-Size Kernel Models for Nonlinear Hybrid System Identification. IEEE Trans. Neural Networks Van Luong Le, Gérard Bloch, Fabien Lauer
2010	—	`conf`	Nonlinear hybrid system identification with kernel models. CDC Fabien Lauer, Gérard Bloch, René Vidal
2009	A*	`conf`	Spectral clustering of linear subspaces for motion segmentation. ICCV Fabien Lauer, Christoph Schnörr
2008	J	`jnl`	Incorporating prior knowledge in support vector machines for classification: A review. Neurocomputing Fabien Lauer, Gérard Bloch
2008	J	`jnl`	Incorporating prior knowledge in support vector regression. Mach. Learn. Fabien Lauer, Gérard Bloch
2008	—	`ch.`	On Learning Machines for Engine Control. Computational Intelligence in Automotive Applications Gérard Bloch, Fabien Lauer, Guillaume Colin
2008	J	`jnl`	Support vector regression from simulation data and few experimental samples. Inf. Sci. Gérard Bloch, Fabien Lauer, Guillaume Colin, Yann Chamaillard
2008	—	`conf`	Switched and PieceWise Nonlinear Hybrid System Identification. HSCC Fabien Lauer, Gérard Bloch
2007	J	`jnl`	A trainable feature extractor for handwritten digit recognition. Pattern Recognit. Fabien Lauer, Ching Y. Suen, Gérard Bloch
2006	J	`jnl`	Ho-Kashyap classifier with early stopping for regularization. Pattern Recognit. Lett. Fabien Lauer, Gérard Bloch
2004	—	`conf`	Ho-Kashyap with Early Stopping Versus Soft Margin SVM for Linear Classifiers - An Application. ISNN (1) Fabien Lauer, Mohamed Bentoumi, Gérard Bloch, Gilles Millerioux, Patrice Aknin

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.