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20052026
most citedPhotonic microwave signals with zeptosecond level absolute timing noise

447 citations

Showing 2020Show all

12 papers · 1 filter

eess.SP2020

Intelligent Reflecting Surface Assisted Anti-Jamming Communications Based on Reinforcement Learning

Helin Yang, Zehui Xiong, Jun Zhao +4

Malicious jamming launched by smart jammer, which attacks legitimate transmissions has been regarded as one of the critical security challenges in wireless communications. Thus, th…

stat.ME2020★ 1 cited

Sparse Correspondence Analysis for Contingency Tables

Ruiping Liu, Ndeye Niang, Gilbert Saporta +1

Since the introduction of the lasso in regression, various sparse methods have been developed in an unsupervised context like sparse principal component analysis (s-PCA), sparse ca…

cs.CY2020

Contribution of Conceptual Modeling to Enhancing Historians' Intuition -Application to Prosopography

Jacky Akoka, Isabelle Comyn-Wattiau, Stéphane Lamassé +1

Historians, and in particular researchers in prosopography, focus a lot of effort on extracting and coding information from historical sources to build databases. To deal with this…

cs.SI2020

Testing the Impact of Semantics and Structure on Recommendation Accuracy and Diversity

Pedro Ramaciotti Morales, Lionel Tabourier, Raphaël Fournier-S'niehotta

The Heterogeneous Information Network (HIN) formalism is very flexible and enables complex recommendations models. We evaluate the effect of different parts of a HIN on the accurac…

cs.CV2020★ 72 cited

Semi-Supervised Semantic Segmentation in Earth Observation: The MiniFrance Suite, Dataset Analysis and Multi-task Network Study

Javiera Castillo-Navarro, Bertrand Le Saux, Alexandre Boulch +2

The development of semi-supervised learning techniques is essential to enhance the generalization capacities of machine learning algorithms. Indeed, raw image data are abundant whi…

stat.ML2020★ 20 cited

Probabilistic Time Series Forecasting with Structured Shape and Temporal Diversity

Vincent Le Guen, Nicolas Thome

Probabilistic forecasting consists in predicting a distribution of possible future outcomes. In this paper, we address this problem for non-stationary time series, which is very ch…