Publications



105 documents

  • 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, 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. ICAPS Workshop on Planning for Financial Services (FinPlan 2020), Oct 2020, Online, France. ⟨hal-02977533⟩
  • Eric Benhamou, David Saltiel, Sandrine Ungari, Abhishek Mukhopadhyay. Bridging the gap between Markowitz planning and deep reinforcement learning. ICAPS PRL, 30th International Conference on Automated Planning and Scheduling - ICAPS PRL 2020, Oct 2020, Nancy (Online), France. ⟨hal-02977530⟩
  • 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. pp.73-82, ⟨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⟩
  • 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⟩
  • Alexandre Araujo, Benjamin Negrevergne, Yann Chevaleyre, Jamal Atif. Understanding and Training Deep Diagonal Circulant Neural Networks. 24th European Conference on Artificial Intelligence (ECAI), Jul 2020, Santiago, Spain. ⟨hal-03916848⟩
  • 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. pp.7717-7727. ⟨hal-02892161⟩
  • Alexandre Araujo, Laurent Meunier, Rafael Pinot, Benjamin Negrevergne. Robust Neural Networks using Randomized Adversarial Training. 2020. ⟨hal-02380184v2⟩