Robust and Hierarchical Stop Discovery in Sparse and Diverse Trajectories
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.
Non-negative matrix factorization (NMF) based sound source separation involves two phases: First, the signal spectrum is decomposed into components which, in a second step, are clustered in order to obtain estimates of the source signal spectra. The major ...
In this paper, a new framework to discover places-of-interest from multimodal mobile phone data is presented. Mobile phones have been used as sensors to obtain location information from users’ real lives. A place-of-interest is defined as a location where ...
The aim of the domain-adaptation task for speaker verification is to exploit unlabelled target domain data by using the labelled source domain data effectively. The i-vector based Probabilistic Linear Dis- criminant Analysis (PLDA) framework approaches thi ...
It has been recently shown that a macroscopic fundamental diagram (MFD) linking space-mean network flow, density and speed exists in the urban transportation networks under some conditions. An MFD is further well defined if the network is homogeneous with ...
Clustering algorithms have evolved to handle more and more complex structures. However, measures allowing to qualify the quality of such partitions are rare and only specic to certain algorithms. In this work, we propose a new cluster validity measure (CVM ...
In this paper we address the problem of detecting and localizing objects that can be both seen and heard, e.g., people. This may be solved within the framework of data clustering. We propose a new multimodal clustering algorithm based on a Gaussian mixture ...
We propose to apply statistical clustering algorithms on a three-dimensional profile of red blood cells (RBCs) obtained through digital holographic microscopy (DHM). We show that two classes of RBCs stored for 14 and 38 days can be effectively classified. ...
The R package bclust is useful for clustering high-dimensional continuous data. The package uses a parametric spike-and-slab Bayesian model to downweight the effect of noise variables and to quantify the importance of each variable in agglomerative cluster ...
We present an algorithm for clustering sets of detected interest points into groups that correspond to visually distinct structure. Through the use of a suitable colour and texture representation, our clustering method is able to identify keypoints that be ...
In this paper, a new framework to discover places-of-interest from multimodal mobile phone data is presented. Mobile phones have been used as sensors to obtain location information from users’ real lives. Two levels of clustering are used to obtain place ...