Daniele Calandriello

According to our database1, Daniele Calandriello authored at least 38 papers between 2013 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

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In proceedings 
Article 
PhD thesis 
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Links

On csauthors.net:

Bibliography

2024
Generalized Preference Optimization: A Unified Approach to Offline Alignment.
CoRR, 2024

Decoding-time Realignment of Language Models.
CoRR, 2024

2023
Nash Learning from Human Feedback.
CoRR, 2023

Demonstration-Regularized RL.
CoRR, 2023

A General Theoretical Paradigm to Understand Learning from Human Preferences.
CoRR, 2023

Unlocking the Power of Representations in Long-term Novelty-based Exploration.
CoRR, 2023

Model-free Posterior Sampling via Learning Rate Randomization.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Fast Rates for Maximum Entropy Exploration.
Proceedings of the International Conference on Machine Learning, 2023

Understanding Self-Predictive Learning for Reinforcement Learning.
Proceedings of the International Conference on Machine Learning, 2023

2022
Optimistic Posterior Sampling for Reinforcement Learning with Few Samples and Tight Guarantees.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

BYOL-Explore: Exploration by Bootstrapped Prediction.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Scaling Gaussian Process Optimization by Evaluating a Few Unique Candidates Multiple Times.
Proceedings of the International Conference on Machine Learning, 2022

Information-theoretic Online Memory Selection for Continual Learning.
Proceedings of the Tenth International Conference on Learning Representations, 2022

2021
On the Emergence of Whole-Body Strategies From Humanoid Robot Push-Recovery Learning.
IEEE Robotics Autom. Lett., 2021

Safe Policy Iteration: A Monotonically Improving Approximate Policy Iteration Approach.
J. Mach. Learn. Res., 2021

One Pass ImageNet.
CoRR, 2021

ParK: Sound and Efficient Kernel Ridge Regression by Feature Space Partitions.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

2020
Learning to Avoid Obstacles With Minimal Intervention Control.
Frontiers Robotics AI, 2020

Sampling from a k-DPP without looking at all items.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Near-linear time Gaussian process optimization with adaptive batching and resparsification.
Proceedings of the 37th International Conference on Machine Learning, 2020

2019
Exact sampling of determinantal point processes with sublinear time preprocessing.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Learning to Sequence Multiple Tasks with Competing Constraints.
Proceedings of the 2019 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2019

Gaussian Process Optimization with Adaptive Sketching: Scalable and No Regret.
Proceedings of the Conference on Learning Theory, 2019

2018
On Fast Leverage Score Sampling and Optimal Learning.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Statistical and Computational Trade-Offs in Kernel K-Means.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Improved Large-Scale Graph Learning through Ridge Spectral Sparsification.
Proceedings of the 35th International Conference on Machine Learning, 2018

Constrained DMPs for Feasible Skill Learning on Humanoid Robots.
Proceedings of the 18th IEEE-RAS International Conference on Humanoid Robots, 2018

2017
Efficient Sequential Learning in Structured and Constrained Environments. (Apprentissage séquentiel efficace dans des environnements structurés avec contraintes).
PhD thesis, 2017

Efficient Second-Order Online Kernel Learning with Adaptive Embedding.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Second-Order Kernel Online Convex Optimization with Adaptive Sketching.
Proceedings of the 34th International Conference on Machine Learning, 2017

Distributed Adaptive Sampling for Kernel Matrix Approximation.
Proceedings of the 20th International Conference on Artificial Intelligence and Statistics, 2017

2016
Incremental Spectral Sparsification for Large-Scale Graph-Based Semi-Supervised Learning.
CoRR, 2016

Analysis of Kelner and Levin graph sparsification algorithm for a streaming setting.
CoRR, 2016

Analysis of Nyström method with sequential ridge leverage scores.
Proceedings of the Thirty-Second Conference on Uncertainty in Artificial Intelligence, 2016

2015
Sparse multi-task reinforcement learning.
Intelligenza Artificiale, 2015

2014
Semi-supervised information-maximization clustering.
Neural Networks, 2014

2013
Physically Interactive Robogames: Definition and design guidelines.
Robotics Auton. Syst., 2013

Safe Policy Iteration.
Proceedings of the 30th International Conference on Machine Learning, 2013


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