Learning to Avoid Obstacles With Minimal Intervention Control von Duan, Anqing, Camoriano, Raffaello, Ferigo, Diego, Huang, Yanlong, Calandriello, Daniele, Rosasco, Lorenzo, Pucci, Daniele

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On the Emergence of Whole-Body Strategies From Humanoid Robot Push-Recovery Learning von Ferigo, Diego, Camoriano, Raffaello, Viceconte, Paolo Maria, Calandriello, Daniele, Traversaro, Silvio, Rosasco, Lorenzo, Pucci, Daniele

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Safe Policy Iteration: A Monotonically Improving Approximate Policy Iteration Approach von Metelli, Alberto Maria, Pirotta, Matteo, Calandriello, Daniele, Restelli, Marcello

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Physically Interactive Robogames: Definition and design guidelines von Martinoia, Diego, Calandriello, Daniele, Bonarini, Andrea

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Semi-supervised information-maximization clustering von Calandriello, Daniele, Niu, Gang, Sugiyama, Masashi

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Efficient sequential learning in structured and constrained environments von Calandriello, Daniele

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Statistical and Computational Trade-Offs in Kernel K-Means von Calandriello, Daniele, Rosasco, Lorenzo

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Information-theoretic Online Memory Selection for Continual Learning von Sun, Shengyang, Calandriello, Daniele, Hu, Huiyi, Li, Ang, Titsias, Michalis

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Sampling from a $k$-DPP without looking at all items von Calandriello, Daniele, Dereziński, Michał, Valko, Michal

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Demonstration-Regularized RL von Tiapkin, Daniil, Belomestny, Denis, Calandriello, Daniele, Moulines, Eric, Naumov, Alexey, Perrault, Pierre, Valko, Michal, Menard, Pierre

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A General Theoretical Paradigm to Understand Learning from Human Preferences von Azar, Mohammad Gheshlaghi, Rowland, Mark, Piot, Bilal, Guo, Daniel, Calandriello, Daniele, Valko, Michal, Munos, Rémi

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Scaling Gaussian Process Optimization by Evaluating a Few Unique Candidates Multiple Times von Calandriello, Daniele, Carratino, Luigi, Lazaric, Alessandro, Valko, Michal, Rosasco, Lorenzo

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One Pass ImageNet von Hu, Huiyi, Li, Ang, Calandriello, Daniele, Gorur, Dilan

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Decoding-time Realignment of Language Models von Liu, Tianlin, Guo, Shangmin, Bianco, Leonardo, Calandriello, Daniele, Berthet, Quentin, Llinares, Felipe, Hoffmann, Jessica, Dixon, Lucas, Valko, Michal, Blondel, Mathieu

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ParK: Sound and Efficient Kernel Ridge Regression by Feature Space Partitions von Carratino, Luigi, Vigogna, Stefano, Calandriello, Daniele, Rosasco, Lorenzo

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Model-free Posterior Sampling via Learning Rate Randomization von Tiapkin, Daniil, Belomestny, Denis, Calandriello, Daniele, Moulines, Eric, Munos, Remi, Naumov, Alexey, Perrault, Pierre, Valko, Michal, Menard, Pierre

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Building Math Agents with Multi-Turn Iterative Preference Learning von Xiong, Wei, Shi, Chengshuai, Shen, Jiaming, Rosenberg, Aviv, Qin, Zhen, Calandriello, Daniele, Khalman, Misha, Joshi, Rishabh, Piot, Bilal, Saleh, Mohammad, Jin, Chi, Zhang, Tong, Liu, Tianqi

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Exact sampling of determinantal point processes with sublinear time preprocessing von Dereziński, Michał, Calandriello, Daniele, Valko, Michal

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Multi-turn Reinforcement Learning from Preference Human Feedback von Shani, Lior, Rosenberg, Aviv, Cassel, Asaf, Lang, Oran, Calandriello, Daniele, Zipori, Avital, Noga, Hila, Keller, Orgad, Piot, Bilal, Szpektor, Idan, Hassidim, Avinatan, Matias, Yossi, Munos, Rémi

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Understanding the performance gap between online and offline alignment algorithms von Tang, Yunhao, Guo, Daniel Zhaohan, Zheng, Zeyu, Calandriello, Daniele, Cao, Yuan, Tarassov, Eugene, Munos, Rémi, Pires, Bernardo Ávila, Valko, Michal, Cheng, Yong, Dabney, Will

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