Aldo Pacchiano

According to our database1, Aldo Pacchiano authored at least 75 papers between 2012 and 2024.

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Bibliography

2024
Provably Sample Efficient RLHF via Active Preference Optimization.
CoRR, 2024

A Framework for Partially Observed Reward-States in RLHF.
CoRR, 2024

Contextual Bandits with Stage-wise Constraints.
CoRR, 2024

2023
Unbiased Decisions Reduce Regret: Adversarial Domain Adaptation for the Bank Loan Problem.
CoRR, 2023

Data-Driven Regret Balancing for Online Model Selection in Bandits.
CoRR, 2023

Improving Offline RL by Blending Heuristics.
CoRR, 2023

Estimating Optimal Policy Value in General Linear Contextual Bandits.
CoRR, 2023

Experiment Planning with Function Approximation.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Anytime Model Selection in Linear Bandits.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

A Unified Model and Dimension for Interactive Estimation.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Supervised Pretraining Can Learn In-Context Reinforcement Learning.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Leveraging Offline Data in Online Reinforcement Learning.
Proceedings of the International Conference on Machine Learning, 2023

Neural Design for Genetic Perturbation Experiments.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

An Instance-Dependent Analysis for the Cooperative Multi-Player Multi-Armed Bandit.
Proceedings of the International Conference on Algorithmic Learning Theory, 2023

Dueling RL: Reinforcement Learning with Trajectory Preferences.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

2022
Transfer RL via the Undo Maps Formalism.
CoRR, 2022

Joint Representation Training in Sequential Tasks with Shared Structure.
CoRR, 2022

Learning General World Models in a Handful of Reward-Free Deployments.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Best of Both Worlds Model Selection.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Unpacking Reward Shaping: Understanding the Benefits of Reward Engineering on Sample Complexity.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Online Nonsubmodular Minimization with Delayed Costs: From Full Information to Bandit Feedback.
Proceedings of the International Conference on Machine Learning, 2022

Meta Learning MDPs with linear transition models.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

Towards an Understanding of Default Policies in Multitask Policy Optimization.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

2021
Parallelizing Contextual Linear Bandits.
CoRR, 2021

Unlocking Pixels for Reinforcement Learning via Implicit Attention.
CoRR, 2021

Deep Reinforcement Learning with Dynamic Optimism.
CoRR, 2021

ES-ENAS: Combining Evolution Strategies with Neural Architecture Search at No Extra Cost for Reinforcement Learning.
CoRR, 2021

Fairness with Continuous Optimal Transport.
CoRR, 2021

Towards tractable optimism in model-based reinforcement learning.
Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, 2021

Reinforcement Learning in Linear MDPs: Constant Regret and Representation Selection.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Neural Pseudo-Label Optimism for the Bank Loan Problem.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Near Optimal Policy Optimization via REPS.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Tactical Optimism and Pessimism for Deep Reinforcement Learning.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

On the Theory of Reinforcement Learning with Once-per-Episode Feedback.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Sample Efficient Reinforcement Learning In Continuous State Spaces: A Perspective Beyond Linearity.
Proceedings of the 38th International Conference on Machine Learning, 2021

Dynamic Balancing for Model Selection in Bandits and RL.
Proceedings of the 38th International Conference on Machine Learning, 2021

Stochastic Bandits with Linear Constraints.
Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

Online Model Selection for Reinforcement Learning with Function Approximation.
Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

Learning the Truth From Only One Side of the Story.
Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

Robustness Guarantees for Mode Estimation with an Application to Bandits.
Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020
Regret Bound Balancing and Elimination for Model Selection in Bandits and RL.
CoRR, 2020

On Optimism in Model-Based Reinforcement Learning.
CoRR, 2020

Regret Balancing for Bandit and RL Model Selection.
CoRR, 2020

On Thompson Sampling with Langevin Algorithms.
CoRR, 2020

Effective Diversity in Population Based Reinforcement Learning.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Ridge Rider: Finding Diverse Solutions by Following Eigenvectors of the Hessian.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Model Selection in Contextual Stochastic Bandit Problems.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Learning to Score Behaviors for Guided Policy Optimization.
Proceedings of the 37th International Conference on Machine Learning, 2020

On Approximate Thompson Sampling with Langevin Algorithms.
Proceedings of the 37th International Conference on Machine Learning, 2020

Accelerated Message Passing for Entropy-Regularized MAP Inference.
Proceedings of the 37th International Conference on Machine Learning, 2020

Stochastic Flows and Geometric Optimization on the Orthogonal Group.
Proceedings of the 37th International Conference on Machine Learning, 2020

Ready Policy One: World Building Through Active Learning.
Proceedings of the 37th International Conference on Machine Learning, 2020

ES-MAML: Simple Hessian-Free Meta Learning.
Proceedings of the 8th International Conference on Learning Representations, 2020

Convergence Rates of Smooth Message Passing with Rounding in Entropy-Regularized MAP Inference.
Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

Practical Nonisotropic Monte Carlo Sampling in High Dimensions via Determinantal Point Processes.
Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

A General Approach to Fairness with Optimal Transport.
Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019
Reinforcement Learning with Chromatic Networks.
CoRR, 2019

Approximate Sherali-Adams Relaxations for MAP Inference via Entropy Regularization.
CoRR, 2019

Wasserstein Reinforcement Learning.
CoRR, 2019

Structured Monte Carlo Sampling for Nonisotropic Distributions via Determinantal Point Processes.
CoRR, 2019

Adaptive Sample-Efficient Blackbox Optimization via ES-active Subspaces.
CoRR, 2019

When random search is not enough: Sample-Efficient and Noise-Robust Blackbox Optimization of RL Policies.
CoRR, 2019

Wasserstein Fair Classification.
Proceedings of the Thirty-Fifth Conference on Uncertainty in Artificial Intelligence, 2019

From Complexity to Simplicity: Adaptive ES-Active Subspaces for Blackbox Optimization.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Online learning with kernel losses.
Proceedings of the 36th International Conference on Machine Learning, 2019

Provably Robust Blackbox Optimization for Reinforcement Learning.
Proceedings of the 3rd Annual Conference on Robot Learning, 2019

Computing Stable Solutions in Threshold Network Flow Games With Bounded Treewidth.
Proceedings of the 18th International Conference on Autonomous Agents and MultiAgent Systems, 2019

KAMA-NNs: Low-dimensional Rotation Based Neural Networks.
Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

2018
Gen-Oja: A Simple and Efficient Algorithm for Streaming Generalized Eigenvector Computation.
CoRR, 2018

A note on reinforcement learning with Wasserstein distance regularisation, with applications to multipolicy learning.
CoRR, 2018

Geometrically Coupled Monte Carlo Sampling.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Gen-Oja: Simple & Efficient Algorithm for Streaming Generalized Eigenvector Computation.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

2017
Conditions beyond treewidth for tightness of higher-order LP relaxations.
Proceedings of the 20th International Conference on Artificial Intelligence and Statistics, 2017

2015
Real time clustering of time series using triangular potentials.
CoRR, 2015

2012
Computational Approaches to Poisson Traces Associated to Finite Subgroups of S<sub>P<sub>2n</sub></sub>(ℂ).
Exp. Math., 2012


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