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Reinforcement Learning Experiments and Benchmark for Solving Robotic Reaching Tasks
PierreAumjaud, DavidMcAuliffe, FranciscoJavierRodríguezLera....
Published date-11/11/2020
Reinforcement learning has shown great promise in robotics thanks to its ability to develop efficient robotic control procedures through self-training. In particular, reinforcement learning has been successfully applied to solving …
End-To-End Semi-supervised Learning for Differentiable Particle Filters
HaoWen, XiongjieChen, GeorgiosPapagiannis....
Published date-11/11/2020
Recent advances in incorporating neural networks into particle filters provide the desired flexibility to apply particle filters in large-scale real-world applications. The dynamic and measurement models in this framework are …
Rediscovering alignment relations with Graph Convolutional Networks
PierreMonnin, ChedyRaïssi, AmedeoNapoli....
Published date-11/11/2020
Clustering, KnowledgeGraphs
Knowledge graphs are concurrently published and edited in the Web of data. Hence they may overlap, which makes key the task that consists in matching their content. This task encompasses …
IGSQL: Database Schema Interaction Graph Based Neural Model for Context-Dependent Text-to-SQL Generation
YitaoCai, XiaojunWan....
Published date-11/11/2020
Text-To-Sql
Context-dependent text-to-SQL task has drawn much attention in recent years. Previous models on context-dependent text-to-SQL task only concentrate on utilizing historical user inputs. In this work, in addition to using …
VStreamDRLS: Dynamic Graph Representation Learning with Self-Attention for Enterprise Distributed Video Streaming Solutions
StefanosAntaris, DimitriosRafailidis....
Published date-11/11/2020
GraphRepresentationLearning, LinkPrediction, RepresentationLearning
Live video streaming has become a mainstay as a standard communication solution for several enterprises worldwide. To efficiently stream high-quality live video content to a large amount of offices, companies …
Distill2Vec: Dynamic Graph Representation Learning with Knowledge Distillation
StefanosAntaris, DimitriosRafailidis....
Published date-11/11/2020
GraphRepresentationLearning, LinkPrediction, RepresentationLearning
Dynamic graph representation learning strategies are based on different neural architectures to capture the graph evolution over time. However, the underlying neural architectures require a large amount of parameters to …