Determining the number of clusters in a data set

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Modeling and Analyzing Inquiry Strategies in Open-Ended Learning Environments

Tanja Christina Käser Jacober

Modeling and predicting student learning in computer-based environments often relies solely on sequences of accuracy data. Previous research suggests that it does not only matter what we learn, but also how we learn. The detection and analysis of learning ...

2020

Removing imaging systematics from galaxy clustering measurements with Obiwan: application to the SDSS-IV extended Baryon Oscillation Spectroscopic Survey emission-line galaxy sample

Cheng Zhao, Anand Stéphane Raichoor

This work presents the application of a new tool, Obiwan, which uses image simulations to determine the selection function of a galaxy redshift survey and calculate three-dimensional (3D) clustering statistics. Obiwan relies on a forward model of the proce ...

OXFORD UNIV PRESS2020

Graph Laplacian Mixture Model

Pascal Frossard, Hermina Petric Maretic

Graph learning methods have recently been receiving increasing interest as means to infer structure in datasets. Most of the recent approaches focus on different relationships between a graph and data sample distributions, mostly in settings where all avai ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2020

Key Performance Indicators for Decision Making in Building Energy Systems

François Maréchal, Luc Girardin, Luise Middelhauve, Alessio Santecchia

Policy makers and energy operator have the responsibility to select indicators for their mission to lead the renewable energy transition ensuring energy independence and security of supply in the context of decarbonisation of the energy mix and and/or nucl ...

2020

Fast Transformers with Clustered Attention

François Fleuret, Apoorv Vyas, Angelos Katharopoulos

Transformers have been proven a successful model for a variety of tasks in sequence modeling. However, computing the attention matrix, which is their key component, has quadratic complexity with respect to the sequence length, thus making them prohibitivel ...

2020

Lane Detection and Lane-Changing Identification with High-Resolution Data from a Swarm of Drones

Nikolaos Geroliminis, Emmanouil Barmpounakis

In the era of big data, new transportation-related concepts and methodologies need to be proposed to understand how congestion propagates. pNEUMA, a unique dataset that was acquired during a first-of-its-kind experiment using a swarm of drones over a dense ...

National Academy of Sciences2020

Predicting learners' effortful behaviour in adaptive assessment using multimodal data

Kshitij Sharma, Jennifer Kaitlyn Olsen

Many factors influence learners' performance on an activity beyond the knowledge required. Learners' on-task effort has been acknowledged for strongly relating to their educational outcomes, reflecting how actively they are engaged in that activity. Howeve ...

ASSOC COMPUTING MACHINERY2020

Dynamical mean-field theory for stochastic gradient descent in Gaussian mixture classification

Lenka Zdeborová, Florent Gérard Krzakala

We analyze in a closed form the learning dynamics of stochastic gradient descent (SGD) for a single layer neural network classifying a high-dimensional Gaussian mixture where each cluster is assigned one of two labels. This problem provides a prototype of ...

Curran Associates, Inc.2020

Assessing spatial temporal patterns of ecosystem services in Switzerland

Jérôme Chenal, Rémi Jaligot, Martí Bosch Padrós

Despite the importance of understanding the historical dynamics of ecosystem services (ES), littleresearch has focused on a historical, spatially explicit, assessment of ES supply. This research is aimed at understanding the spatial patterns and potential ...

2019