Elisabeth Gassiat

33 papers A* 1Misc 1Journal 31

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	Frontiers to the learning of nonparametric hidden Markov models. J. Mach. Learn. Res. Kweku Abraham, Elisabeth Gassiat, Zacharie Naulet
2025	J	`jnl`	Fundamental Limits of Membership Inference Attacks on Machine Learning Models. J. Mach. Learn. Res. Eric Aubinais, Elisabeth Gassiat, Pablo Piantanida
2025	J	`jnl`	Membership Inference Risks in Quantized Models: A Theoretical and Empirical Study. CoRR Eric Aubinais, Philippe Formont, Pablo Piantanida, Elisabeth Gassiat
2025	J	`jnl`	Tree-based variational inference for Poisson log-normal models. Stat. Comput. Alexandre Chaussard, Anna Bonnet, Elisabeth Gassiat, Sylvain Le Corff
2024	J	`jnl`	Additive smoothing error in backward variational inference for general state-space models. J. Mach. Learn. Res. Mathis Chagneux, Elisabeth Gassiat, Pierre Gloaguen, Sylvain Le Corff
2024	J	`jnl`	Variational excess risk bound for general state space models. Trans. Mach. Learn. Res. Elisabeth Gassiat, Sylvain Le Corff
2023	J	`jnl`	Fundamental Limits for Learning Hidden Markov Model Parameters. IEEE Trans. Inf. Theory Kweku Abraham, Elisabeth Gassiat, Zacharie Naulet
2023	J	`jnl`	Fundamental Limits of Membership Inference Attacks on Machine Learning Models. CoRR Eric Aubinais, Elisabeth Gassiat, Pablo Piantanida
2022	J	`jnl`	Multiple Testing in Nonparametric Hidden Markov Models: An Empirical Bayes Approach. J. Mach. Learn. Res. Kweku Abraham, Ismael Castillo, Elisabeth Gassiat
2021	A*	`conf`	Disentangling Identifiable Features from Noisy Data with Structured Nonlinear ICA. NeurIPS Hermanni Hälvä, Sylvain Le Corff, Luc Lehéricy, Jonathan So, Yongjie Zhu, Elisabeth Gassiat, Aapo Hyvärinen
2021	J	`jnl`	Disentangling Identifiable Features from Noisy Data with Structured Nonlinear ICA. CoRR Hermanni Hälvä, Sylvain Le Corff, Luc Lehéricy, Jonathan So, Yongjie Zhu, Elisabeth Gassiat, Aapo Hyvärinen
2021	J	`jnl`	Fundamental limits for learning hidden Markov model parameters. CoRR Kweku Abraham, Zacharie Naulet, Elisabeth Gassiat
2021	J	`jnl`	Joint self-supervised blind denoising and noise estimation. CoRR Jean Ollion, Charles Ollion, Elisabeth Gassiat, Luc Lehéricy, Sylvain Le Corff
2020	J	`jnl`	Identifiability and Consistent Estimation of Nonparametric Translation Hidden Markov Models with General State Space. J. Mach. Learn. Res. Elisabeth Gassiat, Sylvain Le Corff, Luc Lehéricy
2017	J	`jnl`	Consistent Estimation of the Filtering and Marginal Smoothing Distributions in Nonparametric Hidden Markov Models. IEEE Trans. Inf. Theory Yohann de Castro, Elisabeth Gassiat, Sylvain Le Corff
2016	J	`jnl`	Inference in finite state space non parametric Hidden Markov Models and applications. Stat. Comput. Elisabeth Gassiat, Alice Cleynen, Stéphane Robin
2016	J	`jnl`	Minimax Adaptive Estimation of Nonparametric Hidden Markov Models. J. Mach. Learn. Res. Yohann de Castro, Elisabeth Gassiat, Claire Lacour
2016	J	`jnl`	Pattern Coding Meets Censoring: (almost) Adaptive Coding on Countable Alphabets. CoRR Anna Ben-Hamou, Stéphane Boucheron, Elisabeth Gassiat
2015	J	`jnl`	About Adaptive Coding on Countable Alphabets: Max-Stable Envelope Classes. IEEE Trans. Inf. Theory Stéphane Boucheron, Elisabeth Gassiat, Mesrob I. Ohannessian
2014	J	`jnl`	About Adaptive Coding on Countable Alphabets. IEEE Trans. Inf. Theory Dominique Bontemps, Stéphane Boucheron, Elisabeth Gassiat
2014	J	`jnl`	About Adaptive Coding on Countable Alphabets: Max-Stable Envelope Classes. CoRR Stéphane Boucheron, Elisabeth Gassiat, Mesrob I. Ohannessian
2013	J	`jnl`	Consistent Order Estimation and Minimal Penalties. IEEE Trans. Inf. Theory Elisabeth Gassiat, Ramon van Handel
2009	J	`jnl`	Coding on Countably Infinite Alphabets. IEEE Trans. Inf. Theory Stéphane Boucheron, Aurélien Garivier, Elisabeth Gassiat
2009	J	`jnl`	Variable selection in model-based clustering using multilocus genotype data. Adv. Data Anal. Classif. Wilson Toussile, Elisabeth Gassiat
2006	J	`jnl`	Error exponents for AR order testing. IEEE Trans. Inf. Theory Stéphane Boucheron, Elisabeth Gassiat
2005	J	`jnl`	A Pairwise Alignment Algorithm Which Favors Clusters of Blocks. J. Comput. Biol. Elodie Nédélec, Thomas Moncion, Elisabeth Gassiat, Bruno Bossard, Guillemette Duchateau-Nguyen, Alain Denise, Michel Termier
2003	J	`jnl`	Optimal error exponents in hidden Markov models order estimation. IEEE Trans. Inf. Theory Elisabeth Gassiat, Stéphane Boucheron
1999	J	`jnl`	MEM pixel correlated solutions for generalized moment and interpolation problems. IEEE Trans. Inf. Theory Imre Csiszár, Fabrice Gamboa, Elisabeth Gassiat
1998	J	`jnl`	Identification of Noisy Linear Systems with Discrete Random Input. IEEE Trans. Inf. Theory Elisabeth Gassiat, Emmanuelle Gautherat
1997	Misc	`conf`	Maximum likelihood for blind separation and deconvolution of noisy signals using mixture models. ICASSP Eric Moulines, Jean-François Cardoso, Elisabeth Gassiat
1997	J	`jnl`	Source separation when the input sources are discrete or have constant modulus. IEEE Trans. Signal Process. Fabrice Gamboa, Elisabeth Gassiat
1994	J	`jnl`	The maximum entropy method on the mean: Applications to linear programming and superresolution. Math. Program. Fabrice Gamboa, Elisabeth Gassiat
1992	J	`jnl`	On simultaneous signal estimation and parameter identification using a generalized likelihood approach. IEEE Trans. Inf. Theory Elisabeth Gassiat, Fabrice Monfront, Yves Goussard

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.