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Found 4 papers, 2 papers with code
Tune As You Scale: Hyperparameter Optimization For Compute Efficient Training
Hyperparameter tuning of deep learning models can lead to order-of-magnitude performance gains for the same amount of compute.
On the Stepwise Nature of Self-Supervised Learning
We present a simple picture of the training process of joint embedding self-supervised learning methods.
Avalon: A Benchmark for RL Generalization Using Procedurally Generated Worlds
As a benchmark tailored for studying RL generalization, we introduce Avalon, a set of tasks in which embodied agents in highly diverse procedural 3D worlds must survive by navigating terrain, hunting or gathering food, and avoiding hazards.
Assessment of Reward Functions for Reinforcement Learning Traffic Signal Control under Real-World Limitations
Adaptive traffic signal control is one key avenue for mitigating the growing consequences of traffic congestion.
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