Daniele Calandriello
Publication record assembled from the DBLP archive of ranked conferences.
Papers indexed
21
Venues
6
Active years
2013–2025
Best venue rank
A*
Where they publish
Papers
21 indexed papers, newest first.
| Year | Venue | Title | Authors |
|---|---|---|---|
| 2025 | ICLR | Building Math Agents with Multi-Turn Iterative Preference Learning. | Wei Xiong, Chengshuai Shi, Jiaming Shen, Aviv Rosenberg, Zhen Qin, Daniele Calandriello, Misha Khalman, Rishabh Joshi, Bilal Piot, Mohammad Saleh, Chi Jin, Tong Zhang, Tianqi Liu |
| 2025 | ICML | On Teacher Hacking in Language Model Distillation. | Daniil Tiapkin, Daniele Calandriello, Johan Ferret, Sarah Perrin, Nino Vieillard, Alexandre Ram, Mathieu Blondel |
| 2024 | AISTATS | A General Theoretical Paradigm to Understand Learning from Human Preferences. | Mohammad Gheshlaghi Azar, Zhaohan Daniel Guo, Bilal Piot, Rmi Munos, Mark Rowland, Michal Valko, Daniele Calandriello |
| 2024 | ICLR | Unlocking the Power of Representations in Long-term Novelty-based Exploration. | Alaa Saade, Steven Kapturowski, Daniele Calandriello, Charles Blundell, Pablo Sprechmann, Leopoldo Sarra, Oliver Groth, Michal Valko, Bilal Piot |
| 2024 | ICLR | Demonstration-Regularized RL. | Daniil Tiapkin, Denis Belomestny, Daniele Calandriello, Eric Moulines, Alexey Naumov, Pierre Perrault, Michal Valko, Pierre Mnard |
| 2024 | ICML | Human Alignment of Large Language Models through Online Preference Optimisation. | Daniele Calandriello, Zhaohan Daniel Guo, Rmi Munos, Mark Rowland, Yunhao Tang, Bernardo vila Pires, Pierre Harvey Richemond, Charline Le Lan, Michal Valko, Tianqi Liu, Rishabh Joshi, Zeyu Zheng, Bilal Piot |
| 2024 | ICML | Decoding-time Realignment of Language Models. | Tianlin Liu, Shangmin Guo, Leonardo Bianco, Daniele Calandriello, Quentin Berthet, Felipe Llinares-Lpez, Jessica Hoffmann, Lucas Dixon, Michal Valko, Mathieu Blondel |
| 2024 | ICML | Nash Learning from Human Feedback. | Rmi Munos, Michal Valko, Daniele Calandriello, Mohammad Gheshlaghi Azar, Mark Rowland, Daniel Guo, Yunhao Tang, Matthieu Geist, Thomas Mesnard, Cme Fiegel, Andrea Michi, Marco Selvi, Sertan Girgin, Nikola Momchev, Olivier Bachem, Daniel J. Mankowitz, Doina Precup, Bilal Piot |
| 2024 | ICML | Generalized Preference Optimization: A Unified Approach to Offline Alignment. | Yunhao Tang, Zhaohan Daniel Guo, Zeyu Zheng, Daniele Calandriello, Rmi Munos, Mark Rowland, Pierre Harvey Richemond, Michal Valko, Bernardo vila Pires, Bilal Piot |
| 2023 | ICML | Understanding Self-Predictive Learning for Reinforcement Learning. | Yunhao Tang, Zhaohan Daniel Guo, Pierre Harvey Richemond, Bernardo vila Pires, Yash Chandak, Rmi Munos, Mark Rowland, Mohammad Gheshlaghi Azar, Charline Le Lan, Clare Lyle, Andrs Gyrgy, Shantanu Thakoor, Will Dabney, Bilal Piot, Daniele Calandriello, Michal Valko |
| 2023 | ICML | Fast Rates for Maximum Entropy Exploration. | Daniil Tiapkin, Denis Belomestny, Daniele Calandriello, Eric Moulines, Rmi Munos, Alexey Naumov, Pierre Perrault, Yunhao Tang, Michal Valko, Pierre Mnard |
| 2022 | ICLR | Information-theoretic Online Memory Selection for Continual Learning. | Shengyang Sun, Daniele Calandriello, Huiyi Hu, Ang Li, Michalis K. Titsias |
| 2022 | ICML | Scaling Gaussian Process Optimization by Evaluating a Few Unique Candidates Multiple Times. | Daniele Calandriello, Luigi Carratino, Alessandro Lazaric, Michal Valko, Lorenzo Rosasco |
| 2020 | ICML | Near-linear time Gaussian process optimization with adaptive batching and resparsification. | Daniele Calandriello, Luigi Carratino, Alessandro Lazaric, Michal Valko, Lorenzo Rosasco |
| 2019 | COLT | Gaussian Process Optimization with Adaptive Sketching: Scalable and No Regret. | Daniele Calandriello, Luigi Carratino, Alessandro Lazaric, Michal Valko, Lorenzo Rosasco |
| 2019 | IROS | Learning to Sequence Multiple Tasks with Competing Constraints. | Anqing Duan, Raffaello Camoriano, Diego Ferigo, Yanlong Huang, Daniele Calandriello, Lorenzo Rosasco, Daniele Pucci |
| 2018 | ICML | Improved Large-Scale Graph Learning through Ridge Spectral Sparsification. | Daniele Calandriello, Ioannis Koutis, Alessandro Lazaric, Michal Valko |
| 2017 | AISTATS | Distributed Adaptive Sampling for Kernel Matrix Approximation. | Daniele Calandriello, Alessandro Lazaric, Michal Valko |
| 2017 | ICML | Second-Order Kernel Online Convex Optimization with Adaptive Sketching. | Daniele Calandriello, Alessandro Lazaric, Michal Valko |
| 2016 | UAI | Analysis of Nystrm method with sequential ridge leverage scores. | Daniele Calandriello, Alessandro Lazaric, Michal Valko |
| 2013 | ICML | Safe Policy Iteration. | Matteo Pirotta, Marcello Restelli, Alessio Pecorino, Daniele Calandriello |