Visual reinforcement learning (RL), which makes decisions directly from high-dimensional
visual inputs, has demonstrated significant potential in various domains. However …

Efficient code search techniques are crucial in accelerating software development by aiding
developers in locating specific code snippets and understanding code functionalities. This …

Any representation of data involves arbitrary investigator choices. Because those choices
are external to the data-generating process, each choice leads to an exact symmetry …

Symmetry plays a central role in the sciences, machine learning, and statistics. For situations
in which data are known to obey a symmetry, a multitude of methods that exploit symmetry …

Transfer learning is a powerful technique for knowledge-sharing between different tasks.
Recent work has found that the representations of models with certain invariances, such as …

Symmetry plays a central role in the sciences, machine learning, and statistics. When data
are known to obey a symmetry, various methods that exploit symmetry have been …

We develop a Mean-Field (MF) view of the learning dynamics of overparametrized Artificial
Neural Networks (NN) under data symmetric in law wrt the action of a general compact …

Symmetry plays a central role in the sciences, machine learning, and statistics. While
statistical tests for the presence of distributional invariance with respect to groups have a …

In this paper we present the framework of symmetry in nonparametric regression. This
generalises the framework of covariate sparsity, where the regression function depends only …

First, a few background assumptions. I assume the existence of a probability space (Ω, H, P)
that is rich enough to support all of the random variables, etc., that we introduce. I also …