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07/31/2023
Discovering Adaptable Symbolic Algorithms from Scratch
Autonomous robots deployed in the real world will need control policies ...
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07/27/2022
Open Source Vizier: Distributed Infrastructure and API for Reliable and Flexible Blackbox Optimization
Vizier is the de-facto blackbox and hyperparameter optimization service ...
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05/26/2022
Towards Learning Universal Hyperparameter Optimizers with Transformers
Meta-learning hyperparameter optimization (HPO) algorithms from prior ex...
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01/11/2022
Automated Reinforcement Learning (AutoRL): A Survey and Open Problems
The combination of Reinforcement Learning (RL) with deep learning has le...
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06/04/2021
Debiasing a First-order Heuristic for Approximate Bi-level Optimization
Approximate bi-level optimization (ABLO) consists of (outer-level) optim...
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06/04/2021
RL-DARTS: Differentiable Architecture Search for Reinforcement Learning
We introduce RL-DARTS, one of the first applications of Differentiable A...
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02/08/2021
Unlocking Pixels for Reinforcement Learning via Implicit Attention
There has recently been significant interest in training reinforcement l...
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01/19/2021
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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12/21/2020
Sub-Linear Memory: How to Make Performers SLiM
The Transformer architecture has revolutionized deep learning on sequent...
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09/30/2020
Rethinking Attention with Performers
We introduce Performers, Transformer architectures which can estimate re...
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06/19/2020
An Ode to an ODE
We present a new paradigm for Neural ODE algorithms, calledODEtoODE, whe...
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06/05/2020
UFO-BLO: Unbiased First-Order Bilevel Optimization
Bilevel optimization (BLO) is a popular approach with many applications ...
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06/05/2020
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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03/31/2020
Robotic Table Tennis with Model-Free Reinforcement Learning
We propose a model-free algorithm for learning efficient policies capabl...
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03/30/2020
Stochastic Flows and Geometric Optimization on the Orthogonal Group
We present a new class of stochastic, geometrically-driven optimization ...
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03/02/2020
Rapidly Adaptable Legged Robots via Evolutionary Meta-Learning
Learning adaptable policies is crucial for robots to operate autonomousl...
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12/06/2019
Observational Overfitting in Reinforcement Learning
A major component of overfitting in model-free reinforcement learning (R...
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11/14/2019
Gradientless Descent: High-Dimensional Zeroth-Order Optimization
Zeroth-order optimization is the process of minimizing an objective f(x)...
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09/25/2019
ES-MAML: Simple Hessian-Free Meta Learning
We introduce ES-MAML, a new framework for solving the model agnostic met...
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07/10/2019
Reinforcement Learning with Chromatic Networks
We present a new algorithm for finding compact neural networks encoding ...
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06/02/2019
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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06/02/2019
The Principle of Unchanged Optimality in Reinforcement Learning Generalization
Several recent papers have examined generalization in reinforcement lear...
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12/15/2017