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Unlocking Pixels for Reinforcement Learning via Implicit Attention
There has recently been significant interest in training reinforcement l...
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ES-ENAS: Combining Evolution Strategies with Neural Architecture Search at No Extra Cost for Reinforcement Learning
We introduce ES-ENAS, a simple neural architecture search (NAS) algorith...
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Sub-Linear Memory: How to Make Performers SLiM
The Transformer architecture has revolutionized deep learning on sequent...
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Rethinking Attention with Performers
We introduce Performers, Transformer architectures which can estimate re...
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An Ode to an ODE
We present a new paradigm for Neural ODE algorithms, calledODEtoODE, whe...
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UFO-BLO: Unbiased First-Order Bilevel Optimization
Bilevel optimization (BLO) is a popular approach with many applications ...
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Masked Language Modeling for Proteins via Linearly Scalable Long-Context Transformers
Transformer models have achieved state-of-the-art results across a diver...
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Robotic Table Tennis with Model-Free Reinforcement Learning
We propose a model-free algorithm for learning efficient policies capabl...
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Stochastic Flows and Geometric Optimization on the Orthogonal Group
We present a new class of stochastic, geometrically-driven optimization ...
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Rapidly Adaptable Legged Robots via Evolutionary Meta-Learning
Learning adaptable policies is crucial for robots to operate autonomousl...
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Observational Overfitting in Reinforcement Learning
A major component of overfitting in model-free reinforcement learning (R...
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Gradientless Descent: High-Dimensional Zeroth-Order Optimization
Zeroth-order optimization is the process of minimizing an objective f(x)...
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ES-MAML: Simple Hessian-Free Meta Learning
We introduce ES-MAML, a new framework for solving the model agnostic met...
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Reinforcement Learning with Chromatic Networks
We present a new algorithm for finding compact neural networks encoding ...
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An Empirical Study on Hyperparameters and their Interdependence for RL Generalization
Recent results in Reinforcement Learning (RL) have shown that agents wit...
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The Principle of Unchanged Optimality in Reinforcement Learning Generalization
Several recent papers have examined generalization in reinforcement lear...
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Sentiment Predictability for Stocks
In this work, we present our findings and experiments for stock-market p...
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