Aldo Pacchiano
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Learning General World Models in a Handful of Reward-Free Deployments
ES-ENAS: Blackbox Optimization over Hybrid Spaces via Combinatorial and Continuous Evolution
Towards an Understanding of Default Policies in Multitask Policy Optimization
Unlocking Pixels for Reinforcement Learning via Implicit Attention
Towards Tractable Optimism in Model-Based Reinforcement Learning
Tactical Optimism and Pessimism for Deep Reinforcement Learning
Effective Diversity in Population-Based Reinforcement Learning
Ridge Rider: Finding Diverse Solutions by Following Eigenvectors of the Hessian
Learning to Score Behaviors for Guided Policy Optimization
Ready Policy one: World Building Through Active Learning
Stochastic Flows and Geometric Optimization on the Orthogonal Group
Taming the Herd: Multi-Modal Meta-Learning with a Population of Agents
Practical Nonisotropic Monte Carlo Sampling in High Dimensions via Determinantal Point Processes
Provably Robust Blackbox Optimization for Reinforcement Learning
From Complexity to Simplicity: Adaptive ES-Active Subspaces for Blackbox Optimization
Reinforcement Learning with Chromatic Networks for Compact Architecture Search
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