Zobrazeno 1 - 10
of 31
pro vyhledávání: '"Sivan Sabato"'
Publikováno v:
ITA
We extend a recently proposed 1-nearest-neighbor based multiclass learning algorithm and prove that our modification is universally strongly Bayes-consistent in all metric spaces admitting any such learner, making it an "optimistically universal" Bay
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b055c72d96eb35f34296dcea57764f94
https://doi.org/10.1214/20-aos2029
https://doi.org/10.1214/20-aos2029
Publikováno v:
AAAI
Scopus-Elsevier
Scopus-Elsevier
We propose a hybrid approach to temporal anomaly detection in access data of users to databases --- or more generally, any kind of subject-object co-occurrence data. We consider a high-dimensional setting that also requires fast computation at test t
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b8f0c3219923924b69a8be0afae23c2a
https://doi.org/10.1609/aaai.v33i01.33013755
https://doi.org/10.1609/aaai.v33i01.33013755
Autor:
Sivan Sabato
Publikováno v:
Theoretical Computer Science. 742:98-113
We consider interactive learning and covering problems, in a setting where actions may incur different costs, depending on the response to the action. We propose a natural greedy algorithm for response-dependent costs. We bound the approximation fact
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::1ab17dc38506cbf3f65793ba55416b02
https://doi.org/10.1016/j.tcs.2017.12.033
https://doi.org/10.1016/j.tcs.2017.12.033
Publikováno v:
IJCAI
Scopus-Elsevier
Scopus-Elsevier
We consider neural network training, in applications in which there are many possible classes, but at test-time, the task is a binary classification task of determining whether the given example belongs to a specific class. We define the Single Logit
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::14b7ce80bd3347db58b9d480c5fdb6eb
https://doi.org/10.24963/ijcai.2019/861
https://doi.org/10.24963/ijcai.2019/861
We consider neural network training, in applications in which there are many possible classes, but at test time, the task is a binary classification task of determining whether the given example belongs to a specific class. We define the single logit
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::096de9684308dd4df63f468035cf71ad
https://opus.bibliothek.uni-augsburg.de/opus4/frontdoor/index/index/docId/71539
https://opus.bibliothek.uni-augsburg.de/opus4/frontdoor/index/index/docId/71539
Publikováno v:
Bioinformatics (Oxford, England). 35(12)
Motivation Bacterial infections are a major cause of illness worldwide. However, most bacterial strains pose no threat to human health and may even be beneficial. Thus, developing powerful diagnostic bioinformatic tools that differentiate pathogenic
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::50a7f674afd22f1a71e8cc126d464166
https://pubmed.ncbi.nlm.nih.gov/30407484
https://pubmed.ncbi.nlm.nih.gov/30407484
Publikováno v:
ICDM
We consider neural network training, in applications in which there are many possible classes, but at test-time, the task is a binary classification task of determining whether the given example belongs to a specific class, where the class of interes
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c9c3e4fb495a64d0838053ad56e3ec44
http://arxiv.org/abs/1705.10246
http://arxiv.org/abs/1705.10246
Autor:
Sivan Sabato
Publikováno v:
Lecture Notes in Computer Science ISBN: 9783319463780
ALT
ALT
We consider interactive learning and covering problems, in a setting where actions may incur different costs, depending on the response to the action. We propose a natural greedy algorithm for response-dependent costs. We bound the approximation fact
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::e64f8751be7c6bf87ec1a4eff2c8d717
https://doi.org/10.1007/978-3-319-46379-7_9
https://doi.org/10.1007/978-3-319-46379-7_9
Publikováno v:
Scopus-Elsevier
We propose a pool-based non-parametric active learning algorithm for general metric spaces, called MArgin Regularized Metric Active Nearest Neighbor (MARMANN), which outputs a nearest-neighbor classifier. We give prediction error guarantees that depe
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::470570ad5a62519c2009acee636b6f52
Publikováno v:
Theoretical Computer Science. 411(29-30):2696-2711
The Information Bottleneck is an information theoretic framework that finds concise representations for an ‘input’ random variable that are as relevant as possible for an ‘output’ random variable. This framework has been used successfully in
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::27948b86d852629c65a625def13f3c36