The more you know, the less you learn: from knowledge transfer to one-shot learning of object categories
Related publications (58)
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.
Learning a discriminative voice embedding allows speaker turns to be compared directly and efficiently, which is crucial for tasks such as diarization and verification. This paper investigates several transfer learning approaches to improve a voice embeddi ...
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 ...
Based mainly on sensors, flow optimization and algorithms, the smart city model has revealed its limits. The city’s smart citizens are scarcely included in the planning process, even though they occupy a key position to produce and share valuable knowledge ...
Empirical studies document a positive effect of collaboration on team productivity. However, little has been done to assess how knowledge flows among team members. Our study addresses this issue by exploring unique rich data on a Swiss funding program prom ...
Classical distillation methods transfer representations from a “teacher” neural network to a “student” network by matching their output activations. Recent methods also match the Jacobians, or the gradient of output activations with the input. However, thi ...
Collaborative learning flow patterns (CLFPs) encode solutions to recurrent pedagogical problems, which have been successfully applied to the design of learning experiences. However, the pedagogical knowledge encoded in these patterns has seldom been exploi ...
Modeling and predicting student learning is an important task in computer-based education. A large body of work has focused on representing and predicting student knowledge accurately. Existing techniques are mostly based on students' performance and on ti ...
Based mainly on sensors, flow optimization and algorithms, the smart city model has revealed its limits. The city’s smart citizens are scarcely included in the planning process, even though they occupy a key position to produce and share valuable knowledge ...
This paper proposes a novel approach to improve speaker modeling using knowledge transferred from face representation. In particular, we are interested in learning a discriminative metric which allows speaker turns to be compared directly, which is benefic ...
Sections are the building blocks of Wikipedia articles. They enhance readability and can be used as a structured entry point for creating and expanding articles. Structuring a new or already existing Wikipedia article with sections is a hard task for human ...