Tag: meta learning

AI Machine Learning & Data Science Research

Beyond Bayes-Optimality: DeepMind & Stanford’s Meta-Learning Approach Builds Risk & Ambiguity Sensitive Agents

In the new paper Beyond Bayes-Optimality: Meta-Learning What You Know You Don’t Know, researchers from DeepMind and Stanford University use modified meta-training algorithms to build agents with risk- and ambiguity-sensitivity.

AI Machine Learning & Data Science Research

DeepMind’s Meta-Learning Sparse Compression Networks Set New SOTA on Diverse Modality Data Compression

In the new paper Meta-Learning Sparse Compression Networks, a DeepMind research team proposes steps for scaling implicit neural representations (INRs). The resulting meta-learning sparse compression networks can represent diverse data modalities such as images, manifolds, signed distance functions, 3D shapes, and scenes, achieving state-of-the-art results on some of them.

AI Machine Learning & Data Science Nature Language Tech Research

Introducing MetaICL: A Language Model Meta-Training Framework for Few-Shot In-Context Learning

A research team from the University of Washington, Facebook AI Research and the Allen Institute for AI introduces Meta-training for InContext Learning (MetaICL), a new meta-training framework for few-shot learning where an LM is meta-trained to learn in-context — conditioning on training examples to recover the task and make predictions.

AI Machine Learning & Data Science Research

DeepMind & IDSIA Introduce Symmetries to Black-Box MetaRL to Improve Its Generalization Ability

In the paper Introducing Symmetries to Black Box Meta Reinforcement Learning, a research team from DeepMind and The Swiss AI Lab IDSIA explores the role of symmetries in meta generalization and shows that introducing more symmetries to black-box meta-learners can improve their ability to generalize to unseen action and observation spaces, tasks, and environments.