Daniele Calandriello

Most-cited papers

Gemini 2.5: Pushing the Frontier with Advanced Reasoning, Multimodality, Long Context, and Next Generation Agentic Capabilities
Gheorghe Comanici, E. Bieber, Mike Schaekermann, Ice Pasupat +496 more
2025arXiv.org4,448 citations
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A General Theoretical Paradigm to Understand Learning from Human Preferences
M. G. Azar, Mark Rowland, Bilal Piot, D. Guo +3 more
2023International Conference on Artificial Intelligence and Statistics1,172 citations
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Nash Learning from Human Feedback
Rémi Munos, Michal Valko, Daniele Calandriello, M. G. Azar +14 more
2023International Conference on Machine Learning261 citations
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Generalized Preference Optimization: A Unified Approach to Offline Alignment
Yunhao Tang, Z. Guo, Ze-Yu Zheng, Daniele Calandriello +6 more
2024International Conference on Machine Learning175 citations
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Understanding the performance gap between online and offline alignment algorithms
Yunhao Tang, Z. Guo, Ze-Yu Zheng, Daniele Calandriello +7 more
2024arXiv.org119 citations
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Safe Policy Iteration
Matteo Pirotta, Marcello Restelli, Alessio Pecorino, Daniele Calandriello
2013International Conference on Machine Learning116 citations
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BYOL-Explore: Exploration by Bootstrapped Prediction
Z. Guo, S. Thakoor, Mîruna Pislar, B. '. Pires +10 more
2022Neural Information Processing Systems108 citations Open access
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Human Alignment of Large Language Models through Online Preference Optimisation
Daniele Calandriello, D. Guo, Rémi Munos, Mark Rowland +9 more
2024International Conference on Machine Learning105 citations
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On Fast Leverage Score Sampling and Optimal Learning
Alessandro Rudi, Daniele Calandriello, Luigi Carratino, L. Rosasco
2018Neural Information Processing Systems99 citations
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Gaussian Process Optimization with Adaptive Sketching: Scalable and No Regret
Daniele Calandriello, Luigi Carratino, A. Lazaric, Michal Valko +1 more
2019Annual Conference Computational Learning Theory92 citations
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Multi-turn Reinforcement Learning from Preference Human Feedback
Lior Shani, Aviv Rosenberg, Asaf B. Cassel, Oran Lang +9 more
2024arXiv.org89 citations
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Sparse multi-task reinforcement learning
Daniele Calandriello, A. Lazaric, Marcello Restelli
2014Intelligenza Artificiale80 citations Open access
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Decoding-time Realignment of Language Models
Tian-Lin Liu, Shangmin Guo, L. Bianco, Daniele Calandriello +6 more
2024International Conference on Machine Learning78 citations
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Building Math Agents with Multi-Turn Iterative Preference Learning
Wei Xiong, Chengshuai Shi, Jiaming Shen, Aviv Rosenberg +9 more
2024International Conference on Learning Representations68 citations
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Information-theoretic Online Memory Selection for Continual Learning
Shengyang Sun, Daniele Calandriello, Huiyi Hu, Ang Li +1 more
2022International Conference on Learning Representations66 citations Open access
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Understanding Self-Predictive Learning for Reinforcement Learning
Yun-Hao Tang, Z. Guo, Pierre H. Richemond, B. '. Pires +12 more
2022International Conference on Machine Learning62 citations Open access
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Exact sampling of determinantal point processes with sublinear time preprocessing
Michal Derezinski, Daniele Calandriello, Michal Valko
2019Neural Information Processing Systems62 citations
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Offline Regularised Reinforcement Learning for Large Language Models Alignment
Pierre H. Richemond, Yunhao Tang, D. Guo, Daniele Calandriello +14 more
2024arXiv.org55 citations
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Second-Order Kernel Online Convex Optimization with Adaptive Sketching
Daniele Calandriello, A. Lazaric, Michal Valko
2017International Conference on Machine Learning47 citations
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Improved Large-Scale Graph Learning through Ridge Spectral Sparsification
Daniele Calandriello, I. Koutis, A. Lazaric, Michal Valko
2018International Conference on Machine Learning42 citations
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Fast Rates for Maximum Entropy Exploration
D. Tiapkin, D. Belomestny, Daniele Calandriello, É. Moulines +6 more
2023International Conference on Machine Learning41 citations Open access
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Efficient Second-Order Online Kernel Learning with Adaptive Embedding
Daniele Calandriello, A. Lazaric, Michal Valko
2017Neural Information Processing Systems35 citations
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Statistical and Computational Trade-Offs in Kernel K-Means
Daniele Calandriello, L. Rosasco
2019Neural Information Processing Systems34 citations
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Sampling from a k-DPP without looking at all items
Daniele Calandriello, Michal Derezinski, Michal Valko
2020Neural Information Processing Systems30 citations
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Distributed Adaptive Sampling for Kernel Matrix Approximation
Daniele Calandriello, A. Lazaric, Michal Valko
2017International Conference on Artificial Intelligence and Statistics30 citations
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Physically Interactive Robogames: Definition and design guidelines
Diego Martinoia, Daniele Calandriello, Andrea Bonarini
2013Robotics Auton. Syst.27 citations Open access
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Near-linear Time Gaussian Process Optimization with Adaptive Batching and Resparsification
Daniele Calandriello, Luigi Carratino, A. Lazaric, Michal Valko +1 more
2020International Conference on Machine Learning25 citations
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One Pass ImageNet
Huiyi Hu, Ang Li, Daniele Calandriello, Dilan Görür
2021arXiv.org23 citations
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On the Emergence of Whole-Body Strategies From Humanoid Robot Push-Recovery Learning
Diego Ferigo, R. Camoriano, Paolo Maria Viceconte, Daniele Calandriello +3 more
2021IEEE Robotics and Automation Letters22 citations Open access
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Scaling Gaussian Process Optimization by Evaluating a Few Unique Candidates Multiple Times
Daniele Calandriello, Luigi Carratino, A. Lazaric, Michal Valko +1 more
2022International Conference on Machine Learning20 citations
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Constrained DMPs for Feasible Skill Learning on Humanoid Robots
An-Qing Duan, R. Camoriano, Diego Ferigo, Daniele Calandriello +2 more
2018IEEE-RAS International Conference on Humanoid Robots19 citations Open access
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Semi-supervised information-maximization clustering
Daniele Calandriello, Gang Niu, Masashi Sugiyama
2013Neural Networks19 citations Open access
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Multi-turn Reinforcement Learning with Preference Human Feedback
Lior Shani, Aviv Rosenberg, Asaf B. Cassel, Oran Lang +9 more
2024Neural Information Processing Systems18 citations
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Safe Policy Iteration: A Monotonically Improving Approximate Policy Iteration Approach
A. Metelli, Matteo Pirotta, Daniele Calandriello, Marcello Restelli
2021Journal of machine learning research17 citations
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Optimistic Posterior Sampling for Reinforcement Learning with Few Samples and Tight Guarantees
D. Tiapkin, D. Belomestny, Daniele Calandriello, É. Moulines +5 more
2022Neural Information Processing Systems15 citations Open access
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Analysis of Nyström method with sequential ridge leverage scores
Daniele Calandriello, A. Lazaric, Michal Valko
2016Conference on Uncertainty in Artificial Intelligence14 citations
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DiffusionGemma Technical Report
DiffusionGemma Team Adrien Ali Taïga, James Assiene, Daniele Calandriello, R. Chaabouni +39 more
202612 citations
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Unlocking the Power of Representations in Long-term Novelty-based Exploration
Alaa Saade, Steven Kapturowski, Daniele Calandriello, C. Blundell +5 more
2023International Conference on Learning Representations11 citations Open access
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On Teacher Hacking in Language Model Distillation
D. Tiapkin, Daniele Calandriello, Johan Ferret, Sarah Perrin +3 more
2025International Conference on Machine Learning10 citations
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Demonstration-Regularized RL
D. Tiapkin, D. Belomestny, Daniele Calandriello, Éric Moulines +4 more
2023arXiv.org9 citations
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Learning to Sequence Multiple Tasks with Competing Constraints
An-Qing Duan, R. Camoriano, Diego Ferigo, Yan-Long Huang +3 more
2019IEEE/RJS International Conference on Intelligent RObots and Systems9 citations
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Model-free Posterior Sampling via Learning Rate Randomization
D. Tiapkin, D. Belomestny, Daniele Calandriello, Éric Moulines +5 more
2023Neural Information Processing Systems8 citations
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ParK: Sound and Efficient Kernel Ridge Regression by Feature Space Partitions
Luigi Carratino, S. Vigogna, Daniele Calandriello, L. Rosasco
2021Neural Information Processing Systems8 citations
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Learning to Avoid Obstacles With Minimal Intervention Control
An-Qing Duan, R. Camoriano, Diego Ferigo, Yan-Long Huang +3 more
2020Frontiers in Robotics and AI8 citations Open access
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Proximal Point Nash Learning from Human Feedback
D. Tiapkin, Daniele Calandriello, D. Belomestny, Éric Moulines +4 more
20256 citations
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Efficient Sequential Learning in Structured and Constrained Environments. (Apprentissage séquentiel efficace dans des environnements structurés avec contraintes)
Daniele Calandriello
20174 citations Open access
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Multi-turn Reinforcement Learning with Preference Human Feedback
Daniele Calandriello, Asaf B. Cassel, A. Hassidim, Orgad Keller +9 more
2024Advances in Neural Information Processing Systems 373 citations
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Pack only the essentials: Adaptive dictionary learning for kernel ridge regression
Daniele Calandriello, A. Lazaric, Michal Valko
2026Neural Information Processing Systems2 citations
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Analysis of Kelner and Levin graph sparsification algorithm for a streaming setting
Daniele Calandriello, A. Lazaric, Michal Valko
2016arXiv.org2 citations
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Incremental Spectral Sparsification for Large-Scale Graph-Based Semi-Supervised Learning
Daniele Calandriello, A. Lazaric, Michal Valko, I. Koutis
2016arXiv.org1 citations
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