Measuring the Impact of Model and Input Heterogeneity in Personalized Federated Learning
Graph Chatbot
Chat with Graph Search
Ask any question about EPFL courses, lectures, exercises, research, news, etc. or try the example questions below.
DISCLAIMER: The Graph Chatbot is not programmed to provide explicit or categorical answers to your questions. Rather, it transforms your questions into API requests that are distributed across the various IT services officially administered by EPFL. Its purpose is solely to collect and recommend relevant references to content that you can explore to help you answer your questions.
Through profiling and matching processes, technology provides individuals with information that becomes redundant to their previous beliefs, attitudes and preferences. The emergence of informational redundancies encouraged by some technologies is likely to ...
Learning analytics (LA) and lesson observations are two approaches frequently used to study teaching and learning processes. In both cases, in order to extract meaningful data interpretations, there is a need for contextualization. Previous works propose t ...
While Ubiquitous Learning Environments (ULEs) have shown several benefits for learning, they pose challenges for orchestration. Teachers need to be aware of the learning process, which is difficult to achieve when it occurs across a heterogeneous set of sp ...
Detection of curvilinear structures has long been of interest due to its wide range of applications. Large amounts of imaging data could be readily used in many fields, but it is practically not possible to analyze them manually. Hence, the need for automa ...
A medical student learning to perform a laparoscopic procedure or a recently paralyzed user of a powered wheelchair must learn to operate machinery via interfaces that translate their actions into commands for an external device. Since the user’s actions a ...
Inductive reasoning is an important educational practice but can be difficult for teachers to support in the classroom due to the high level of preparation and classroom time needed to choose the teaching materials that challenge students' current views. I ...
Imaging systems can be designed using examples and methods similar to the techniques used in deep learning. We describe experimental results demonstrating optical tomography based on the learning approach. ...
Whether it occurs in artificial or biological substrates, {\it learning} is a {distributed} phenomenon in at least two aspects. First, meaningful data and experiences are rarely found in one location, hence {\it learners} have a strong incentive to work to ...
The design and analysis of machine learning algorithms typically considers the problem of learning on a single task, and the nature of learning in such scenario is well explored. On the other hand, very often tasks faced by machine learning systems arrive ...
What is new in perceptual learning? In the early days of research, specificity was the hallmark of perceptual learning; that is, improvements following training were limited to the trained stimulus features. For example, training with a stimulus improves p ...
Association for Research in Vision and Ophthalmology (ARVO)2017
