25 citations · 50 across the 10 of their papers we have counts for
10 papers
Transcriptomics-based matching of drugs to diseases with deep learning
Yannis Papanikolaou, Francesco Tuveri, Misa Ogura +1
In this work we present a deep learning approach to conduct hypothesis-free, transcriptomics-based matching of drugs for diseases. Our proposed neural network architecture is train…
Slot Filling for Biomedical Information Extraction
Yannis Papanikolaou, Marlene Staib, Justin Grace +1
Information Extraction (IE) from text refers to the task of extracting structured knowledge from unstructured text. The task typically consists of a series of sub-tasks such as Nam…
Teach me how to Label: Labeling Functions from Natural Language with Text-to-text Transformers
Yannis Papanikolaou
Annotated data has become the most important bottleneck in training accurate machine learning models, especially for areas that require domain expertise. A recent approach to deal…
DARE: Data Augmented Relation Extraction with GPT-2
Yannis Papanikolaou, Andrea Pierleoni
Real-world Relation Extraction (RE) tasks are challenging to deal with, either due to limited training data or class imbalance issues. In this work, we present Data Augmented Relat…
Deep Bidirectional Transformers for Relation Extraction without Supervision
Yannis Papanikolaou, Ian Roberts, Andrea Pierleoni
We present a novel framework to deal with relation extraction tasks in cases where there is complete lack of supervision, either in the form of gold annotations, or relations from…
Neural Embedding Allocation: Distributed Representations of Topic Models
Kamrun Naher Keya, Yannis Papanikolaou, James R. Foulds
Word embedding models such as the skip-gram learn vector representations of words' semantic relationships, and document embedding models learn similar representations for documents…
Subset Labeled LDA for Large-Scale Multi-Label Classification
Yannis Papanikolaou, Grigorios Tsoumakas
Labeled Latent Dirichlet Allocation (LLDA) is an extension of the standard unsupervised Latent Dirichlet Allocation (LDA) algorithm, to address multi-label learning tasks. Previous…
Large-Scale Online Semantic Indexing of Biomedical Articles via an Ensemble of Multi-Label Classification Models
Yannis Papanikolaou, Grigorios Tsoumakas, Manos Laliotis +2
Background: In this paper we present the approaches and methods employed in order to deal with a large scale multi-label semantic indexing task of biomedical papers. This work was…
Hierarchical Partitioning of the Output Space in Multi-label Data
Yannis Papanikolaou, Ioannis Katakis, Grigorios Tsoumakas
Hierarchy Of Multi-label classifiers (HOMER) is a multi-label learning algorithm that breaks the initial learning task to several, easier sub-tasks by first constructing a hierarch…
Dense Distributions from Sparse Samples: Improved Gibbs Sampling Parameter Estimators for LDA
Yannis Papanikolaou, James R. Foulds, Timothy N. Rubin +1
We introduce a novel approach for estimating Latent Dirichlet Allocation (LDA) parameters from collapsed Gibbs samples (CGS), by leveraging the full conditional distributions over…