Publications



44 documents

Journal articles

  • Frank Curtis, Daniel Robinson, Clément Royer, Stephen Wright. Trust-Region Newton-CG with Strong Second-Order Complexity Guarantees for Nonconvex Optimization. SIAM Journal on Optimization, Society for Industrial and Applied Mathematics, 2021, 31 (1), pp.518-544. ⟨10.1137/19M130563X⟩. ⟨hal-03135526⟩
  • Alexandre Araujo, Benjamin Negrevergne, Yann Chevaleyre, Jamal Atif. Training compact deep learning models for video classification using circulant matrices. European Conference on Computer Vision, 2018, pp.271-286. ⟨10.1007/978-3-030-11018-5_25⟩. ⟨hal-02010093⟩
  • Fabien Labernia, Florian Yger, Brice Mayag, Jamal Atif. Query-based learning of acyclic conditional preference networks from noisy data. EURO journal on decision processes, Springer, 2018, 6 (1-2), ⟨10.1007/s40070-017-0070-3⟩. ⟨hal-02074081⟩
  • Eric Benhamou, Beatrice Guez. Incremental Sharpe and other performance ratios. Journal of Statistical and Econometric Methods, 2018, xx, pp.2241 - 0376. ⟨hal-02012443v2⟩
  • Adrian Lecoutre, Benjamin Negrevergne, Florian Yger. Recognizing Art Style Automatically with deep learning. Proceedings of Machine Learning Research, PMLR, 2017, 77, pp.327 - 342. ⟨hal-02004781⟩
  • Eric Benhamou. T-statistic for Autoregressive process. Journal of Statistical and Econometric Methods, 2011, pp.2241 - 0376. ⟨hal-02012459⟩
  • Eric Benhamou. Gram Charlier and Edgeworth expansion for sample variance. Theoretical Mathematics and Applications, 2011, x (4), pp.1792 - 6939. ⟨hal-02012464⟩

Conference papers

  • Linlin Jia, Benoit Gaüzère, Florian Yger, Paul Honeine. A Metric Learning Approach to Graph Edit Costs for Regression. Proceedings of IAPR Joint International Workshops on Statistical techniques in Pattern Recognition (SPR 2020) and Structural and Syntactic Pattern Recognition (SSPR 2020), Jan 2021, Venise, Italy. ⟨hal-03128664⟩
  • Florian Yger, Sylvain Chevallier, Quentin Barthélemy, Suvrit Sra. Geodesically-convex optimization for averaging partially observed covariance matrices. Asian Conference on Machine Learning (ACML), Nov 2020, Bangkok, Thailand. pp.417 - 432. ⟨hal-02984423⟩
  • Jing Zhang, Caroline Petitjean, Florian Yger, Samia Ainouz. Explainability for regression CNN in fetal head circumference estimation from ultrasound images. Workshop on Interpretability of Machine Intelligence in Medical Image Computing at MICCAI 2020, Oct 2020, Lima, Peru. ⟨10.1007/978-3-030-61166-8_8⟩. ⟨hal-02960164⟩
  • Alexandre Araujo, Laurent Meunier, Rafael Pinot, Benjamin Negrevergne. Advocating for Multiple Defense Strategies against Adversarial Examples. Workshop on Machine Learning for CyberSecurity (MLCS@ECML-PKDD), Sep 2020, Ghent, Belgium. ⟨hal-03118649⟩
  • Rafael Pinot, Raphael Ettedgui, Geovani Rizk, Yann Chevaleyre, Jamal Atif. Randomization matters How to defend against strong adversarial attacks. Thirty-seventh International Conference on Machine Learning, Jul 2020, Vienna, Austria. ⟨hal-02892161⟩
  • Nicolas Boria, Benjamin Negrevergne, Florian Yger. Fréchet Mean Computation in Graph Space through Projected Block Gradient Descent. ESANN 2020, 2020, Bruges, France. ⟨hal-02895832⟩
  • M. Riva, F. Yger, P. Gori, R. Cesar, Isabelle Bloch. Template-Based Graph Clustering. ECML-PKDD, Workshop on Graph Embedding and Mining (GEM), 2020, Ghent, Belgium. ⟨hal-02916167⟩
  • Matthieu Clertant, Nataliya Sokolovska, Yann Chevaleyre, Blaise Hanczar. Interpretable Cascade Classifiers with Abstention. 22nd International Conference on Artificial Intelligence and Statistics (AISTATS 2019), Apr 2019, Naha, Japan. ⟨hal-02006252⟩
  • Ikko Yamane, Florian Yger, Jamal Atif, Masashi Sugiyama. Uplift Modeling from Separate Labels. NeurIPS, Dec 2018, Montréal, Canada. ⟨hal-02010052⟩
  • Rafael Pinot, Anne Morvan, Florian Yger, Cedric Gouy-Pailler, Jamal Atif. Graph-based Clustering under Differential Privacy. Uncertainty in Artificial Intelligence (UAI 2018), Aug 2018, Monterley, California, United States. pp.132. ⟨hal-02010071⟩
  • Anne Morvan, Krzysztof Choromanski, Cedric Gouy-Pailler, Jamal Atif. Graph sketching-based Space-efficient Data Clustering. 2018 SIAM International Conference on Data Mining, Society for Industrial and Applied Mathematics, May 2018, San Diego, United States. ⟨10.1137/1.9781611975321.2⟩. ⟨cea-01838501⟩
  • Fabien Labernia, Bruno Zanuttini, Brice Mayag, Florian Yger, Jamal Atif. Online learning of acyclic conditional preference networks from noisy data. 17th IEEE International Conference on Data Mining (ICDM 2017), Nov 2017, New Orleans, United States. ⟨hal-01619969⟩
  • Mariusz Bojarski, Anna Choromanska, Krzysztof Choromanski, Francois Fagan, Cedric Gouy-Pailler, et al.. Structured adaptive and random spinners for fast machine learning computations. 20th International Conference on Artificial Intelligence and Statistics (AISTATS 2017), Apr 2017, Fort Lauderdale, Florida, United States. pp.1020-1029. ⟨hal-02010086⟩
  • Fabien Labernia, Bruno Zanuttini, Brice Mayag, Florian Yger, Jamal Atif. Online learning of acyclic conditional preference networks from noisy data. ICDM 2017, 2017, New Orleans, États-Unis. ⟨10.1109/ICDM.2017.34⟩. ⟨hal-02074110⟩
  • Quentin Brabant, Miguel Couceiro, Fabien Labernia, Amedeo Napoli. A dimensionality Reduction Approach for Qualitative Preference Aggregation. International Symposium on Aggregation and Structures (ISAS 2016), Jul 2016, Luxembourg, Luxembourg. ⟨hal-02074061⟩

Book sections

  • Laurent Meunier, Yann Chevaleyre, Jeremy Rapin, Clément Royer, Olivier Teytaud. On Averaging the Best Samples in Evolutionary Computation. Parallel Problem Solving from Nature – PPSN XVI. PPSN 2020, pp.661-674, 2020, ⟨10.1007/978-3-030-58115-2_46⟩. ⟨hal-03135540⟩

Preprints, Working Papers

  • Eric Benhamou, Jean Ohana, David Saltiel, Beatrice Guez. Detecting crisis event with Gradient Boosting Decision Trees. 2021. ⟨hal-03320297⟩
  • Eric Benhamou, Jean Ohana, David Saltiel, Beatrice Guez. Regime change detection with GBDT and Shapley values. 2021. ⟨hal-03320304⟩
  • J Ohana, S Ohana, Eric Benhamou, D Saltiel, B Guez. Shapley values for LightGBM model applied to regime detection. 2021. ⟨hal-03320300⟩
  • Eric Benhamou. Distribution and statistics of the Sharpe Ratio. 2021. ⟨hal-03207169⟩
  • Eric Benhamou, Beatrice Guez. Computation of the marginal contribution of Sharpe ratio and other performance ratios. 2021. ⟨hal-03189299v2⟩
  • Jean Jacques Ohana, Eric Benhamou, David Saltiel, Beatrice Guez. Is the Covid equity bubble rational? A machine learning answer. 2021. ⟨hal-03189799⟩
  • Eric Benhamou, David Saltiel, Rida Laraki, Jamal Atif. BCMA-ES: a conjugate prior Bayesian optimization view. 2020. ⟨hal-02977523⟩
  • Eric Benhamou, David Saltiel, Sandrine Ungari, Abhishek Mukhopadhyay. Bridging the gap between Markowitz planning and deep reinforcement learning. 2020. ⟨hal-02977530⟩
  • Eric Benhamou, David Saltiel, Sandrine Ungari, Abhishek Mukhopadhyay, Jamal Atif. AAMDRL: Augmented Asset Management with Deep Reinforcement Learning. 2020. ⟨hal-02977535⟩
  • Eric Benhamou, David Saltiel, Sandrine Ungari, Abhishek Mukhopadhyay. Time your hedge with Deep Reinforcement Learning. 2020. ⟨hal-02977533⟩
  • Alexandre Araujo, Laurent Meunier, Rafael Pinot, Benjamin Negrevergne. Robust Neural Networks using Randomized Adversarial Training. 2020. ⟨hal-02380184v2⟩
  • Eric Benhamou. Kalman filter demystified: from intuition to probabilistic graphical model to real case in financial markets. 2019. ⟨hal-02012471⟩
  • Eric Benhamou. Connecting Sharpe ratio and Student t-statistic, and beyond. 2019. ⟨hal-02012448⟩
  • Eric Benhamou, Jamal Atif, Rida Laraki. A new approach to learning in Dynamic Bayesian Networks (DBNs). 2019. ⟨hal-02011529v2⟩
  • Eric Benhamou. A few properties of sample variance. 2019. ⟨hal-02012458⟩
  • Eric Benhamou, Jamal Atif, Rida Laraki. A discrete version of CMA-ES. 2019. ⟨hal-02011531v2⟩
  • David Saltiel, Eric Benhamou. Trade Selection with Supervised Learning and OCA. 2019. ⟨hal-02012476⟩
  • David Saltiel, Eric Benhamou. Feature selection with optimal coordinate ascent (OCA). 2019. ⟨hal-02012473⟩
  • Eric Benhamou, Valentin Melot. Seven proofs of the Pearson Chi-squared independence test and its graphical interpretation. 2019. ⟨hal-02012452⟩

Reports

  • Marie-Constance Corsi, Florian Yger, Sylvain Chevallier, Camille Noûs. Clinical BCI Challenge-WCCI2020: RIGOLETTO -- RIemannian GeOmetry LEarning, applicaTion To cOnnectivity. [Technical Report] ARAMIS, LAMSADE, LISV. 2021. ⟨hal-03139990⟩

Theses

  • Fabien Labernia. Algorithmes efficaces pour l'apprentissage de réseaux de préférences conditionnelles à partir de données bruitées. Intelligence artificielle [cs.AI]. PSL Research University, 2018. Français. ⟨tel-02074097⟩