Further Applications of Sector-Based Detection and Short-Term Clustering
Graph Chatbot
Chattez avec Graph Search
Posez n’importe quelle question sur les cours, conférences, exercices, recherches, actualités, etc. de l’EPFL ou essayez les exemples de questions ci-dessous.
AVERTISSEMENT : Le chatbot Graph n'est pas programmé pour fournir des réponses explicites ou catégoriques à vos questions. Il transforme plutôt vos questions en demandes API qui sont distribuées aux différents services informatiques officiellement administrés par l'EPFL. Son but est uniquement de collecter et de recommander des références pertinentes à des contenus que vous pouvez explorer pour vous aider à répondre à vos questions.
Capturing students' behavioral patterns through analysis of sequential interaction logs, is an important task in educational data mining to enable more effective personalized support during the learning process. This study aims at discovery and temporal an ...
Language independent query-by-example spoken term detection (QbE-STD) is the problem of retrieving audio documents from an archive, which contain a spoken query provided by a user. This is usually casted as a hypothesis testing and pattern matching problem ...
The extraction of student behavior is an important task in educational data mining. A common approach to detect similar behavior patterns is to cluster sequential data. Standard approaches identify clusters at each time step separately and typically show l ...
The main challenge of new information technologies is to retrieve intelligible information from the large volume of digital data gathered every day. Among the variety of existing data sources, the satellites continuously observing the surface of the Earth ...
Polarimetric radar-based hydrometeor classification is the procedure of identifying different types of hydrometeors by exploiting polarimetric radar observations. The main drawback of the existing supervised classification methods, mostly based on fuzzy lo ...
Automatic visual speech recognition is an interesting problem in pattern recognition especially when audio data is noisy or not readily available. It is also a very challenging task mainly because of the lower amount of information in the visual articulati ...
The diffusion strategy for distributed learning from streaming data employs local stochastic gradient updates along with exchange of iterates over neighborhoods. In this work we establish that agents cluster around a network centroid in the mean-fourth sen ...
Speaker diarization is the task of identifying ``who spoke when'' in an audio stream containing multiple speakers. This is an unsupervised task as there is no a priori information about the speakers. Diagnostical studies on state-of-the-art diarization sys ...
In this work, we consider the problem of estimating the coefficients of linear shift-invariant FIR graph filters. We assume hybrid node-varying graph filters where the network is decomposed into clusters of nodes and, within each cluster, all nodes have th ...
Speaker diarization is the task of identifying “who spoke when” in an audio stream containing multiple speakers. This is an unsupervised task as there is no a priori information about the speakers. Diagnostical studies on state-of-the-art diarization syste ...