Search Results for author: Ioannis Vlahavas

Found 12 papers, 0 papers with code

REIN-2: Giving Birth to Prepared Reinforcement Learning Agents Using Reinforcement Learning Agents

no code implementations11 Oct 2021 Aristotelis Lazaridis, Ioannis Vlahavas

In an effort to patch these issues, we integrated a meta-learning technique in order to shift the objective of learning to solve a task into the objective of learning how to learn to solve a task (or a set of tasks), which we empirically show that improves overall stability and performance of Deep RL algorithms.

Meta-Learning OpenAI Gym +1

E.T.: Entity-Transformers. Coreference augmented Neural Language Model for richer mention representations via Entity-Transformer blocks

no code implementations COLING (CRAC) 2020 Nikolaos Stylianou, Ioannis Vlahavas

In this paper we present an extension over the Transformer-block architecture used in neural language models, specifically in GPT2, in order to incorporate entity annotations during training.

Language Modelling named-entity-recognition +1

Multi-target regression via output space quantization

no code implementations22 Mar 2020 Eleftherios Spyromitros-Xioufis, Konstantinos Sechidis, Ioannis Vlahavas

Multi-target regression is concerned with the prediction of multiple continuous target variables using a shared set of predictors.

Multi-target regression Quantization

LionForests: Local Interpretation of Random Forests

no code implementations20 Nov 2019 Ioannis Mollas, Nick Bassiliades, Ioannis Vlahavas, Grigorios Tsoumakas

Towards a future where machine learning systems will integrate into every aspect of people's lives, researching methods to interpret such systems is necessary, instead of focusing exclusively on enhancing their performance.

A Neural Entity Coreference Resolution Review

no code implementations21 Oct 2019 Nikolaos Stylianou, Ioannis Vlahavas

We highlight the advantages and disadvantages of the approaches, the challenges of the task, the lack of agreed-upon standards in the task and propose a way to further expand the boundaries of the field.

Coreference Resolution Entity Linking +4

Large-Scale Online Semantic Indexing of Biomedical Articles via an Ensemble of Multi-Label Classification Models

no code implementations18 Apr 2017 Yannis Papanikolaou, Grigorios Tsoumakas, Manos Laliotis, Nikos Markantonatos, Ioannis Vlahavas

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.

General Classification Multi-Label Classification

The Tomaco Hybrid Matching Framework for SAWSDL Semantic Web Services

no code implementations21 Oct 2014 Thanos G. Stavropoulos, Stelios Andreadis, Nick Bassiliades, Dimitris Vrakas, Ioannis Vlahavas

The algorithm is hybrid in nature, combining novel and known concepts, such as a logic-based strategy and syntactic text-similarity measures on semantic annotations and textual descriptions.

text similarity

Multi-Target Regression via Random Linear Target Combinations

no code implementations20 Apr 2014 Grigorios Tsoumakas, Eleftherios Spyromitros-Xioufis, Aikaterini Vrekou, Ioannis Vlahavas

Multi-target regression is concerned with the simultaneous prediction of multiple continuous target variables based on the same set of input variables.

General Classification Multi-Label Classification +1

Multi-Target Regression via Input Space Expansion: Treating Targets as Inputs

no code implementations28 Nov 2012 Eleftherios Spyromitros-Xioufis, Grigorios Tsoumakas, William Groves, Ioannis Vlahavas

When the prediction targets are binary the task is called multi-label classification, while when the targets are continuous the task is called multi-target regression.

General Classification Multi-Label Classification +2

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