Zobrazeno 1 - 10
of 11
pro vyhledávání: '"Eli Chien"'
Many high-dimensional practical data sets have hierarchical structures induced by graphs or time series. Such data sets are hard to process in Euclidean spaces and one often seeks low-dimensional embeddings in other space forms to perform the require
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::45335f6fc88052a5e3cffd1b2190eea6
http://arxiv.org/abs/2203.03730
http://arxiv.org/abs/2203.03730
As the demand for user privacy grows, controlled data removal (machine unlearning) is becoming an important feature of machine learning models for data-sensitive Web applications such as social networks and recommender systems. Nevertheless, at this
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ec0d9324f8b061826ba0412ab8fb5663
Publikováno v:
ISIT
The problem of estimating the support of a distribution is of great importance in many areas of machine learning, computer science, physics and biology. Most of the existing work in this domain has focused on settings that assume perfectly accurate s
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::698e39791e386ca2e23db4cfedbdae6e
https://doi.org/10.1109/isit45174.2021.9517892
https://doi.org/10.1109/isit45174.2021.9517892
Publikováno v:
IEEE Transactions on Information Theory. 65:8095-8118
Community detection in hypergraphs is explored. Under a generative hypergraph model called "d-wise hypergraph stochastic block model" (d-hSBM) which naturally extends the Stochastic Block Model from graphs to d-uniform hypergraphs, the asymptotic min
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::57a948224767ec14d33362eeeef39326
https://doi.org/10.1109/tit.2019.2928301
https://doi.org/10.1109/tit.2019.2928301
The problem of estimating unknown features of viral species using a limited collection of observations is of great relevance in computational biology. We consider one such particular problem, concerned with determining the mutational support and dist
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::219cc358e7df23e2f1c5b66b57042e5f
https://doi.org/10.1101/2020.04.23.20076075
https://doi.org/10.1101/2020.04.23.20076075
Publikováno v:
IEEE/ACM Transactions on Computational Biology and Bioinformatics. :1-1
We consider the problem of determining the mutational support and distribution of the SARS-CoV-2 viral genome in the small-sample regime. The mutational support refers to the unknown number of sites that may eventually mutate in the SARS-CoV-2 genome
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::2b06593a23ba6ed25ed9575cad3d2542
https://doi.org/10.1109/tcbb.2022.3165395
https://doi.org/10.1109/tcbb.2022.3165395
Publikováno v:
ICASSP
Generative graph models create instances of graphs that mimic the properties of real-world networks. Generative models are successful at retaining pairwise associations in the underlying networks but often fail to capture higher-order connectivity pa
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::627c0114c45e6b7b7176cecda98180b4
http://arxiv.org/abs/1911.05469
http://arxiv.org/abs/1911.05469
Publikováno v:
ITW
We describe the first known mean-field study of landing probabilities for random walks on hypergraphs. In particular, we examine clique-expansion and tensor methods and evaluate their mean-field characteristics over a class of random hypergraph model
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::9a0a10cdf02ea8d0b68f1ef212682de1
http://arxiv.org/abs/1910.09040
http://arxiv.org/abs/1910.09040
Publikováno v:
AAAI
The geometric block model is a recently proposed generative model for random graphs that is able to capture the inherent geometric properties of many community detection problems, providing more accurate characterizations of practical community struc
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::eab27a8b3c532390c1abbdf06978c52c
Publikováno v:
ISIT
The problem of community detection in random hypergraphs is considered. We extend the Stochastic Block Model (SBM) from graphs to hypergraphs with d-uniform hyperedges, which we term “d-wise hyper stochastic block model” (d-hSBM) and consider a h
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::7b32e0ebc48db2fe8da0c64a68e3e392
https://doi.org/10.1109/isit.2017.8006915
https://doi.org/10.1109/isit.2017.8006915