Concept

Knowledge modeling

Related publications (29)

Infusing structured knowledge priors in neural models for sample-efficient symbolic reasoning

The ability to reason, plan and solve highly abstract problems is a hallmark of human intelligence. Recent advancements in artificial intelligence, propelled by deep neural networks, have revolutionized disciplines like computer vision and natural language ...

EPFL2024

GenIE: Generative Information Extraction

Robert West, Maxime Jean Julien Peyrard, Martin Josifoski

Structured and grounded representation of text is typically formalized by closed information extraction, the problem of extracting an exhaustive set of (subject, relation, object) triplets that are consistent with a predefined set of entities and relations ...

ASSOC COMPUTATIONAL LINGUISTICS-ACL2022

The Role of Adaptivity in Source Identification with Time Queries

Gergely Odor

Understanding epidemic propagation in large networks is an important but challenging task, especially since we usually lack information, and the information that we have is often counter-intuitive. An illustrative example is the dependence of the final siz ...

EPFL2022

Motion as meaning: Representing embodied knowledge in the multimodal cultural archives

Yumeng Hou

The digitization of intangible cultural heritage (ICH) has grown rapidly since 2003 since UNESCO affirmed the significance of preserving "the practices, representations, expressions, knowledge, skills". Unlike tangible heritage, which is conventionally pro ...

2021

A semantic-driven approach toward Industry 4.0

Sangje Cho

The current manufacturing trend is towards sustainability. Due to the degradation of natural resources and the accumulation of waste with an increase in the world population and in the consumption of goods, many countries attempt to switch from a linear to ...

EPFL2020

Transforming knowledge systems for life on Earth: Visions of future systems and how to get there

Susan Marie Mühlemeier

Formalised knowledge systems, including universities and research institutes, are important for contemporary societies. They are, however, also arguably failing humanity when their impact is measured against the level of progress being made in stimulating ...

ELSEVIER2020

Iterative Classroom Teaching

Pierre Dillenbourg, Volkan Cevher, Thibault Lucien Christian Asselborn, Shuqing Teresa Yeo, Louis Pierre Faucon, Kamalaruban Parameswaran

We consider the machine teaching problem in a classroom-like setting wherein the teacher has to deliver the same examples to a diverse group of students. Their diversity stems from differences in their initial internal states as well as their learning rate ...

ASSOC ADVANCEMENT ARTIFICIAL INTELLIGENCE2019

Interactive Teaching Algorithms for Inverse Reinforcement Learning

Volkan Cevher, Kamalaruban Parameswaran

We study the problem of inverse reinforcement learning (IRL) with the added twist that the learner is assisted by a helpful teacher. More formally, we tackle the following algorithmic question: How could a teacher provide an informative sequence of demonst ...

2019

Interactive Teaching Algorithms for Inverse Reinforcement Learning

Volkan Cevher, Kamalaruban Parameswaran

2019

Neuromorphic System with Phase-Change Synapses for Pattern Learning and Feature Extraction

Yusuf Leblebici, Stanislaw Andrzej Wozniak, Evangelos Eleftheriou, Angeliki Pantazi

Neuromorphic systems provide biologically inspired methods of computing, alternative to the classical von Neumann approach. In these systems, computation is performed by a network of spiking neurons controlled by the values of their synaptic weights, which ...

2017

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