Computational Analysis Of Behavior In Employment Interviews And Video Resumes

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.

A range of behavioral and contextual factors, including eating and drinking behavior, mood, social context, and other daily activities, can significantly impact an individual's quality of life and overall well-being. Therefore, inferring everyday life aspe ...

Computing servers have played a key role in developing and processing emerging compute-intensive applications in recent years. Consolidating multiple virtual machines (VMs) inside one server to run various applications introduces severe competence for limi ...

Photometric stereo, a computer vision technique for estimating the 3D shape of objects through images captured under varying illumination conditions, has been a topic of research for nearly four decades. In its general formulation, photometric stereo is an ...

Machine learning (ML) enables artificial intelligent (AI) agents to learn autonomously from data obtained from their environment to perform tasks. Modern ML systems have proven to be extremely effective, reaching or even exceeding human intelligence. Altho ...

Social behaviors such as cooperation are crucial for mammals. A deeper knowledge of the neuronal mechanisms underlying cooperation can be beneficial for people suffering from pathologies with impaired social behavior. Our aim was to study the brain activit ...

In the past few years, Machine Learning (ML) techniques have ushered in a paradigm shift, allowing the harnessing of ever more abundant sources of data to automate complex tasks. The technical workhorse behind these important breakthroughs arguably lies in ...

A large body of work shows that machine learning (ML) models can leak sensitive or confidential information about their training data. Recently, leakage due to distribution inference (or property inference) attacks is gaining attention. In this attack, the ...

Machine learning models trained with passive sensor data from mobile devices can be used to perform various inferences pertaining to activity recognition, context awareness, and health and well-being. Prior work has improved inference performance through t ...

This training dataset includes a total of 34,913 manually transcribed text segments. It is dedicated to the handwritten text recognition (HTR) of historical sources, typically tabular records, such as censuses. This dataset is based on a sample of 83 pages ...

When studying discomfort glare, researchers tend to rely on a single questionnaire item to obtain user evaluations. It is unclear whether the choice of questionnaire item affects the distribution of user responses and leads to inconsistencies between studi ...

Investigating the intangible nature of a cultural domain can take multiple forms, addressing for example the aesthetic, epistemic and social dimensions of its phenomenology. The context of Southern Chinese martial arts is of particular significance as it c ...

Measuring the intensity of events is crucial for monitoring and tracking armed conflict. Advances in automated event extraction have yielded massive data sets of '' who did what to whom '' micro-records that enable datadriven approaches to monitoring confl ...

Metal-based Laser Powder Bed Fusion (LPBF) has made fabricating intricate components easier. Yet, assessing part quality is inefficient, relying on costly Computed Tomography (CT) scans or time-consuming destructive tests. Also, intermittent inspection of ...

State-of-the-art object detection and segmentation methods for microscopy images rely on supervised machine learning, which requires laborious manual annotation of training data. Here we present a self-supervised method based on time arrow prediction pre-t ...

Dense image-based prediction methods have advanced tremendously in recent years. Their remarkable development has been possible due to the ample availability of real-world imagery. While these methods work well on photographs, their abilities do not genera ...

Humans can express their actions and intentions, resorting to verbal and/or non-verbal communication. In verbal communication, humans use language to express, in structured linguistic terms, the desired action they wish to perform. Non-verbal communication ...

End-to-end learning methods like deep neural networks have been the driving force in the remarkable progress of machine learning in recent years. However, despite their success, the deployment process of such networks in safety-critical use cases, such as ...

The successes of deep learning for semantic segmentation can in be, in part, attributed to its scale: a notion that encapsulates the largeness of these computational architectures and the labeled datasets they are trained on. These resource requirements hi ...

Over the years, clinical institutes accumulated large amounts of digital slides from resected tissue specimens. These digital images, called whole slide images (WSIs), are high-resolution tissue snapshots that depict the complex interaction of cells at the ...

Single-photon avalanche diodes (SPADs) are novel image sensors that record the arrival of individual photons at extremely high temporal resolution. In the past, they were only available as single pixels or small-format arrays, for various active imaging ap ...

Computational Analysis Of Behavior In Employment Interviews And Video Resumes

Chat with Graph Search

Generalization and Personalization of Machine Learning for Multimodal Mobile Sensing in Everyday Life

CloudProphet: A Machine Learning-Based Performance Prediction for Public Clouds

Aggregating Spatial and Photometric Context for Photometric Stereo

Few-shot Learning for Efficient and Effective Machine Learning Model Adaptation

Involvement of prelimbic cortex neurons and related circuits in the acquisition of a cooperative learning by pairs of rats

Topics in statistical physics of high-dimensional machine learning

Distribution Inference Risks: Identifying and Mitigating Sources of Leakage

Keep Sensors in Check: Disentangling Country-Level Generalization Issues in Mobile Sensor-Based Models with Diversity Scores

Lausanne Historical Censuses Dataset HTR 35k

Comparison of questionnaire items for discomfort glare studies in daylit spaces

The Facets of Intangible Heritage in Southern Chinese Martial Arts: Applying a Knowledge-Driven Cultural Contact Detection Approach

An Ordinal Latent Variable Model of Conflict Intensity

Optimizing in-situ monitoring for laser powder bed fusion process: Deciphering acoustic emission and sensor sensitivity with explainable machine learning

Self-supervised Dense Representation Learning for Live-Cell Microscopy with Time Arrow Prediction

Dense Image-based Predictions for Comics Analysis

Non-verbal Communication between Humans and Robots: Imitation, Mutual Understanding and Inferring Object Properties

Estimating and Improving the Robustness of Attributions in Text

Confidence Matters: Applications to Semantic Segmentation

Self-Supervised Learning for Patient Stratification and Survival Analysis in Computational Pathology: An Application to Colorectal Cancer

Burst Vision Using Single-Photon Cameras