85 citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- University of ParmaIT2 papers
- Aalborg UniversityDK1 paper
- Beijing Institute of TechnologyCN1 paper
- Centre National de la Recherche ScientifiqueFR1 paper
- Henan University of Science and TechnologyCN1 paper
- Institute of Mathematics and InformaticsBG1 paper
- Laboratoire d'Informatique pour la Mécanique et les Sciences de l'IngénieurFR1 paper
- Massachusetts Institute of TechnologyUS1 paper
- National Research University Higher School of EconomicsRU1 paper
- Shenzhen Technology UniversityCN1 paper
- Shenzhen UniversityCN1 paper
- Stevens Institute of TechnologyUS1 paper
7 papers
Modern approaches to building interpretable models of the property market using machine learning on the base of mass cadastral valuation
Alexey S. Tanashkin, Irina G. Tanashkina, Alexander S. Maksimchuik
In this paper, we review modern approaches to building interpretable models of property markets using machine learning on the base of mass valuation of property in the Primorye reg…
Boundary transfer matrices arising from quantum symmetric pairs
Andrea Appel, Bart Vlaar
We introduce a universal framework for boundary transfer matrices, inspired by Sklyanin's two-row transfer matrix approach for quantum integrable systems with boundary conditions.…
Ensemble Control for Stochastic Systems with Asymmetric Laplace Noises
Yajie Yu, Xuehui Ma, Shiliang Zhang +4
This paper presents an adaptive ensemble control for stochastic systems subject to asymmetric noises and outliers. Asymmetric noises skew system observations, and outliers with lar…
Tensor K-matrices for quantum symmetric pairs
Andrea Appel, Bart Vlaar
Let be a symmetrizable Kac-Moody algebra, its quantum group, and a quantum symmetric pair subalgebr…
Shifted symplectic structures on derived Quot-stacks II -- Derived Quot-schemes as dg manifolds
Dennis Borisov, Ludmil Katzarkov, Artan Sheshmani
It is proved that derived Quot-schemes, as defined by Ciocan-Fontanine and Kapranov, are represented by dg manifolds of finite type. This is the second part if a work aimed to anal…
Variational Deep Embedding: An Unsupervised and Generative Approach to Clustering
Zhuxi Jiang, Yin Zheng, Huachun Tan +2
Clustering is among the most fundamental tasks in computer vision and machine learning. In this paper, we propose Variational Deep Embedding (VaDE), a novel unsupervised generative…
Document Neural Autoregressive Distribution Estimation
Stanislas Lauly, Yin Zheng, Alexandre Allauzen +1
We present an approach based on feed-forward neural networks for learning the distribution of textual documents. This approach is inspired by the Neural Autoregressive Distribution…