Search Results for author: Hugo Penedones

Found 4 papers, 0 papers with code

Equivariant neural networks for recovery of Hadamard matrices

no code implementations31 Jan 2022 Augusto Peres, Eduardo Dias, Luís Sarmento, Hugo Penedones

We propose a message passing neural network architecture designed to be equivariant to column and row permutations of a matrix.

Combinatorial Optimization

Adaptive Temporal-Difference Learning for Policy Evaluation with Per-State Uncertainty Estimates

no code implementations NeurIPS 2019 Hugo Penedones, Carlos Riquelme, Damien Vincent, Hartmut Maennel, Timothy Mann, Andre Barreto, Sylvain Gelly, Gergely Neu

We consider the core reinforcement-learning problem of on-policy value function approximation from a batch of trajectory data, and focus on various issues of Temporal Difference (TD) learning and Monte Carlo (MC) policy evaluation.

Temporal Difference Learning with Neural Networks - Study of the Leakage Propagation Problem

no code implementations9 Jul 2018 Hugo Penedones, Damien Vincent, Hartmut Maennel, Sylvain Gelly, Timothy Mann, Andre Barreto

Temporal-Difference learning (TD) [Sutton, 1988] with function approximation can converge to solutions that are worse than those obtained by Monte-Carlo regression, even in the simple case of on-policy evaluation.

Adaptive Lambda Least-Squares Temporal Difference Learning

no code implementations30 Dec 2016 Timothy A. Mann, Hugo Penedones, Shie Mannor, Todd Hester

Temporal Difference learning or TD($\lambda$) is a fundamental algorithm in the field of reinforcement learning.

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