Search Results for author: Tigran Galstyan

Found 6 papers, 2 papers with code

Guaranteed Optimal Generative Modeling with Maximum Deviation from the Empirical Distribution

no code implementations31 Jul 2023 Elen Vardanyan, Arshak Minasyan, Sona Hunanyan, Tigran Galstyan, Arnak Dalalyan

Generative modeling is a widely-used machine learning method with various applications in scientific and industrial fields.

Matching Map Recovery with an Unknown Number of Outliers

no code implementations24 Oct 2022 Arshak Minasyan, Tigran Galstyan, Sona Hunanyan, Arnak Dalalyan

If $n$ and $m$ are the sizes of these two sets, we assume that the matching map that should be recovered is defined on a subset of unknown cardinality $k^*\le \min(n, m)$.

Optimal detection of the feature matching map in presence of noise and outliers

no code implementations NeurIPS 2021 Tigran Galstyan, Arshak Minasyan, Arnak Dalalyan

The matching map is then an injection, which can be consistently estimated only if the vectors of the second set are well separated.

Robust Classification under Class-Dependent Domain Shift

no code implementations10 Jul 2020 Tigran Galstyan, Hrant Khachatrian, Greg Ver Steeg, Aram Galstyan

Investigation of machine learning algorithms robust to changes between the training and test distributions is an active area of research.

Classification General Classification +1

BioRelEx 1.0: Biological Relation Extraction Benchmark

1 code implementation WS 2019 Hrant Khachatrian, Lilit Nersisyan, Karen Hambardzumyan, Tigran Galstyan, Anna Hakobyan, Arsen Arakelyan, Andrey Rzhetsky, Aram Galstyan

Automatic extraction of relations and interactions between biological entities from scientific literature remains an extremely challenging problem in biomedical information extraction and natural language processing in general.

Relation Relation Extraction

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