6 citations · 13 across the 9 of their papers we have counts for
9 papers
Search Wide, Focus Deep: Automated Fetal Brain Extraction with Sparse Training Data
Javid Dadashkarimi, Valeria Pena Trujillo, Camilo Jaimes +2
Automated fetal brain extraction from full-uterus MRI is a challenging task due to variable head sizes, orientations, complex anatomy, and prevalent artifacts. While deep-learning…
Enhancement attacks in biomedical machine learning
Matthew Rosenblatt, Javid Dadashkarimi, Dustin Scheinost
The prevalence of machine learning in biomedical research is rapidly growing, yet the trustworthiness of such research is often overlooked. While some previous works have investiga…
Data-driven mapping between functional connectomes using optimal transport
Javid Dadashkarimi, Amin Karbasi, Dustin Scheinost
Functional connectomes derived from functional magnetic resonance imaging have long been used to understand the functional organization of the brain. Nevertheless, a connectome is…
Zero-shot Transfer Learning for Semantic Parsing
Javid Dadashkarimi, Alexander Fabbri, Sekhar Tatikonda +1
While neural networks have shown impressive performance on large datasets, applying these models to tasks where little data is available remains a challenging problem. In this pape…
Sequence to Logic with Copy and Cache
Javid Dadashkarimi, Sekhar Tatikonda
Generating logical form equivalents of human language is a fresh way to employ neural architectures where long short-term memory effectively captures dependencies in both encoder a…
SS4MCT: A Statistical Stemmer for Morphologically Complex Texts
Javid Dadashkarimi, Hossein Nasr Esfahani, Heshaam Faili +1
There have been multiple attempts to resolve various inflection matching problems in information retrieval. Stemming is a common approach to this end. Among many techniques for ste…
Low-dimensional Query Projection based on Divergence Minimization Feedback Model for Ad-hoc Retrieval
Javid Dadashkarimi, Masoud Jalili Sabet, Heshaam Faili +1
Low-dimensional word vectors have long been used in a wide range of applications in natural language processing. In this paper we shed light on estimating query vectors in ad-hoc r…
Dimension Projection among Languages based on Pseudo-relevant Documents for Query Translation
Javid Dadashkarimi, Mahsa S. Shahshahani, Amirhossein Tebbifakhr +2
Using top-ranked documents in response to a query has been shown to be an effective approach to improve the quality of query translation in dictionary-based cross-language informat…
A Probabilistic Translation Method for Dictionary-based Cross-lingual Information Retrieval in Agglutinative Languages
Javid Dadashkarimi, Azadeh Shakery, Heshaam Faili
Translation ambiguity, out of vocabulary words and missing some translations in bilingual dictionaries make dictionary-based Cross-language Information Retrieval (CLIR) a challengi…