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Research

  • The Grind Behind the Epiphany: A Short Story of a Research Project

    The Grind Behind the Epiphany: A Short Story of a Research Project

    From ideation to outcome, this is the story of a privacy-preserving research project. It tells how research can generate innovations but also joy and despair. Early 2024: The “Hammer” Phase Two research leads who pioneered Criteo’s early privacy initiatives, as part of the Criteo multi-year research program, introduced me to a challenge born from the Privacy…

  • Agentic AI Symposium 2026

    Agentic AI Symposium 2026

    A science‑fueled, multidisciplinary approach to Agentic AI Authors: Jean-Yves Franceschi & Mariia Vladimirova At the Criteo AI Lab, we believe that making AI both trustworthy and useful requires a continuous and open dialogue between scientists, engineers, policymakers, regulators, and industry leaders. As AI systems evolve from passive predictors to agentic systems capable of planning, using tools,…

  • Off-Policy Learning in Large Action Spaces

    Off-Policy Learning in Large Action Spaces

    Optimization Matters More Than Estimation This Research Card shows that in large-scale recommendation systems, like those used at Criteo, focusing on how we optimize algorithms is more impactful than trying to perfectly estimate outcomes. By using simpler, more stable training objectives, we can achieve better click-through rates, faster experimentation, and more scalable performance across millions…

  • Pareto-Optimality, Smoothness, and Stochasticity in Learning-Augmented One-Max-Search

    Pareto-Optimality, Smoothness, and Stochasticity in Learning-Augmented One-Max-Search

    A rule for choosing when to sell/buy an asset when facing a sequence of prices This Research Card explains a rule for choosing when to sell/buy an asset when facing a sequence of prices. The key feature is that the algorithm has access to “predictions” on the optimal price. The objectives are to take “safe” decisions,…

  • Improving Consistency Models with Generator-Augmented Flows

    Improving Consistency Models with Generator-Augmented Flows

    Delivering more personalized ads in real-time — boosting engagement and cutting infrastructure costs. This Research Card presents Generator-Augmented Flows (GC), a technique improving consistency models, which are state-of-the-art models for fast image and video generation. For Criteo, this could mean delivering more personalized ads in real time — boosting engagement and cutting infrastructure costs. Title: Improving Consistency Models with…

  • Our Experience at ALT 2025

    Our Experience at ALT 2025

    A Journey into Algorithmic Learning Theory Authors: Marc Abeille, Julien Zhou & Corentin Pla. The Algorithmic Learning Theory (ALT) 2025 conference, held in Milan at the end of February, was a significant event in the field of machine learning and theoretical computer science. This one-track conference brought together hundred researchers and practitioners to discuss the latest…

  • Bringing NeRFs to the Latent Space: Inverse Graphics Autoencoder

    Bringing NeRFs to the Latent Space: Inverse Graphics Autoencoder

    A novel IG-AE that creates a 3D-aware latent space compatible with Neural Radiance Fields This Research Card introduces a novel Inverse Graphics Autoencoder (IG-AE) that creates a 3D-aware latent space compatible with Neural Radiance Fields (NeRFs), enabling efficient 3D object reconstruction from 2D images and facilitating high-quality 3D ads. Title: Bringing NeRFs to the Latent Space:…

  • Differentially Private Gradient Flow based on the Sliced Wasserstein Distance

    Differentially Private Gradient Flow based on the Sliced Wasserstein Distance

    Novel differentially private model using gradient flows defined on an optimal transport metric. This Research Card introduces a novel, theoretically grounded method for differentially private generative modeling by leveraging a smooth mathematical process, achieving high-fidelity data generation with strong privacy guarantees and lower computational costs compared to traditional approaches. Title: Differentially Private Gradient Flow based…

  • All our contributions at NeurIPS 2024

    All our contributions at NeurIPS 2024

    This year, our research team got a record of 15 papers accepted at the major ML conference. The 38th annual edition of the prestigious international conference NeurIPS 2024 (Neural Information Processing Systems) took place in Vancouver. 𝗥𝗲𝘀𝗲𝗮𝗿𝗰𝗵𝗲𝗿𝘀 𝗳𝗿𝗼𝗺 𝘁𝗵𝗲 𝗖𝗿𝗶𝘁𝗲𝗼 𝗔𝗜 𝗟𝗮𝗯 were there to present their latest ML papers (𝟭𝟯 𝗽𝗮𝗽𝗲𝗿𝘀 — 𝗮𝗺𝗼𝗻𝗴 𝘄𝗵𝗶𝗰𝗵 𝗼𝗻𝗲 𝘀𝗽𝗼𝘁𝗹𝗶𝗴𝗵𝘁 — ,…

  • Trustworthy AI Symposium Highlights

    Trustworthy AI Symposium Highlights

    In the wake of the AI Action Summit, Criteo organized a symposium on Trustworthy AI labeled as an AI Action Summit event. As the international AI Action Summit is set to take place in Paris next Feb. 10 & 11, Criteo leveraged this opportunity to contribute to one of the themes of the summit, Trust in…