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method ID: ensemblelearning

Related Papers

Unsupervised Named Entity Classification Models and their Ensembles

Authors: nan

Publication: TIPSTER (2002)

DOI: nan

This paper proposes an unsupervised learning model for classifying named entities. This model uses a training set, built automatically by means of a small-scale named entity dictionary and an unlabeled …...

6575

Ensemble-based Active Learning for Parse Selection

Authors: nan

Publication: TIPSTER (2004)

DOI: nan

Supervised estimation methods are widely seen as being superior to semi and fully unsuper- vised methods. However, supervised methods crucially rely upon training sets that need to be manually annotated. …...

24277

A Weakly Supervised Model for Sentence-Level Semantic Orientation Analysis with Multiple Experts

Authors: nan

Publication: TIPSTER (2012)

DOI: nan

We propose the weakly supervised Multi- Experts Model (MEM) for analyzing the se- mantic orientation of opinions expressed in natural language reviews. In contrast to most prior work, MEM predicts …...

44173

UNIBA-CORE: Combining Strategies for Semantic Textual Similarity

Authors: nan

Publication: TIPSTER (2013)

DOI: nan

This paper describes the UNIBA participation in the Semantic Textual Similarity (STS) core task 2013. We exploited three different sys- tems for computing the similarity between two texts. A system …...

26201

Biocom Usp: Tweet Sentiment Analysis with Adaptive Boosting Ensemble

Authors: nan

Publication: TIPSTER (2014)

DOI: nan

We describe our approach for the SemEval-2014 task 9: Sentiment Analy- sis in Twitter. We make use of an en- semble learning method for sentiment classification of tweets that relies …...

22878

Biocom Usp: Tweet Sentiment Analysis with Adaptive Boosting Ensemble

Authors: nan

Publication: TIPSTER (2014)

DOI: nan

We describe our approach for the SemEval-2014 task 9: Sentiment Analy- sis in Twitter. We make use of an en- semble learning method for sentiment classification of tweets that relies …...

22879

UTH_CCB: A report for SemEval 2014 – Task 7 Analysis of Clinical Text

Authors: nan

Publication: TIPSTER (2014)

DOI: nan

This work describes the participation of the University of Texas Health Science Center at Houston (UTHealth) team on the SemEval 2014 – Task 7 analysis of clinical text challenge. The …...

22670

HITSZ-ICRC: Exploiting Classification Approach for Answer Selection in Community Question Answering

Authors: nan

Publication: TIPSTER (2015)

DOI: nan

This paper describes the participation of the HITSZ-ICRC team on the Answer Selection Challenge in SemEval-2015. Our team parti- cipated in English subtask A, English subtask B and Arabic task. …...

22762

TwiSE at SemEval-2016 Task 4: Twitter Sentiment Classification

Authors: nan

Publication: TIPSTER (2016)

DOI: nan

This paper describes the participation of the team “TwiSE” in the SemEval 2016 challenge. Specifically, we participated in Task 4, namely “Sentiment Analysis in Twitter” for which we implemented sentiment …...

22576

TSA-INF at SemEval-2017 Task 4: An Ensemble of Deep Learning Architectures Including Lexicon Features for Twitter Sentiment Analysis

Authors: nan

Publication: TIPSTER (2017)

DOI: nan

AbstractThis paper describes the submission of team TSA-INF to SemEval-2017 Task 4 Subtask A. The submitted system is an ensemble of three varying deep learning architectures for sentiment analysis. The …...

25205

ETH-DS3Lab at SemEval-2018 Task 7: Effectively Combining Recurrent and Convolutional Neural Networks for Relation Classification and Extraction

Authors: nan

Publication: TIPSTER (2018)

DOI: nan

AbstractReliably detecting relevant relations between entities in unstructured text is a valuable resource for knowledge extraction, which is why it has awaken significant interest in the field of Natural Language …...

26013

Unfolding the External Behavior and Inner Affective State of Teammates through Ensemble Learning: Experimental Evidence from a Dyadic Team Corpus

Authors: nan

Publication: TIPSTER (2018)

DOI: nan

The current study was motivated to understand the relationship between the external behavior and inner affective state of two team members (“instructor”-“defuser”) during a demanding operational task (i.e., bomb defusion). …...

18011

YNU-HPCC at SemEval-2018 Task 1: BiLSTM with Attention based Sentiment Analysis for Affect in Tweets

Authors: nan

Publication: TIPSTER (2018)

DOI: nan

AbstractWe implemented the sentiment system in all five subtasks for English and Spanish. All subtasks involve emotion or sentiment intensity prediction (regression and ordinal classification) and emotions determining (multi-labels classification). …...

26081

Zeyad at SemEval-2019 Task 6: That’s Offensive! An All-Out Search For An Ensemble To Identify And Categorize Offense in Tweets.

Authors: nan

Publication: TIPSTER (2019)

DOI: nan

AbstractThe objective of this paper is to provide a description for a classification system built for SemEval-2019 Task 6: OffensEval. This system classifies a tweet as either offensive or not …...

25651

UMSIForeseer at SemEval-2020 Task 11: Propaganda Detection by Fine-Tuning BERT with Resampling and Ensemble Learning

Authors: nan

Publication: TIPSTER (2020)

DOI: nan

AbstractWe describe our participation at the SemEval 2020 “Detection of Propaganda Techniques in News Articles” - Techniques Classification (TC) task, designed to categorize textual fragments into one of the 14 …...

24424

A Study on Contextualized Language Modeling for Machine Reading Comprehension

Authors: nan

Publication: TIPSTER (2021)

DOI: nan

AbstractWith the recent breakthrough of deep learning technologies, research on machine reading comprehension (MRC) has attracted much attention and found its versatile applications in many use cases. MRC is an …...

1073

abcbpc at SemEval-2021 Task 7: ERNIE-based Multi-task Model for Detecting and Rating Humor and Offense

Authors: nan

Publication: TIPSTER (2021)

DOI: nan

AbstractThis paper describes our system participated in Task 7 of SemEval-2021: Detecting and Rating Humor and Offense. The task is designed to detect and score humor and offense which are …...

25736

Huawei BabelTar NMT at WMT22 Biomedical Translation Task: How We Further Improve Domain-specific NMT

Authors: nan

Publication: TIPSTER (2022)

DOI: nan

AbstractThis paper describes Huawei Artificial Intelligence Application Research Center’s neural machine translation system (“BabelTar”). Our submission to the WMT22 biomedical translation shared task covers language directions between English and the …...

27461

One-Teacher and Multiple-Student Knowledge Distillation on Sentiment Classification

Authors: nan

Publication: TIPSTER (2022)

DOI: nan

AbstractKnowledge distillation is an effective method to transfer knowledge from a large pre-trained teacher model to a compacted student model. However, in previous studies, the distilled student models are still …...

3660

RubCSG at SemEval-2022 Task 5: Ensemble learning for identifying misogynous MEMEs

Authors: nan

Publication: TIPSTER (2022)

DOI: nan

AbstractThis work presents an ensemble system based on various uni-modal and bi-modal model architectures developed for the SemEval 2022 Task 5: MAMI-Multimedia Automatic Misogyny Identification. The challenge organizers provide an …...

25092

taochen at SemEval-2022 Task 5: Multimodal Multitask Learning and Ensemble Learning

Authors: nan

Publication: TIPSTER (2022)

DOI: nan

AbstractWe present a multi-modal deep learning system for the Multimedia Automatic Misogyny Identification (MAMI) challenge, a SemEval task of identifying and classifying misogynistic messages in online memes. We adapt multi-task …...

25084

UMUTeam at SemEval-2022 Task 5: Combining image and textual embeddings for multi-modal automatic misogyny identification

Authors: nan

Publication: TIPSTER (2022)

DOI: nan

AbstractIn this manuscript we describe the participation of the UMUTeam on the MAMI shared task proposed at SemEval 2022. This task is concerning the identification of misogynous content from a …...

25070

UMUTeam at SemEval-2022 Task 6: Evaluating Transformers for detecting Sarcasm in English and Arabic

Authors: nan

Publication: TIPSTER (2022)

DOI: nan

AbstractIn this manuscript we detail the participation of the UMUTeam in the iSarcasm shared task (SemEval-2022). This shared task is related to the identification of sarcasm in English and Arabic …...

25033

YNU-HPCC at ROCLING 2022 Shared Task: A Transformer-based Model with Focal Loss and Regularization Dropout for Chinese Healthcare Named Entity Recognition

Authors: nan

Publication: TIPSTER (2022)

DOI: nan

AbstractNamed Entity Recognition (NER) is a fundamental task in information extraction that locates the mentions of named entities and classifies them in unstructured texts. Previous studies typically used hidden Markov …...

992

Bag of Tricks for In-Distribution Calibration of Pretrained Transformers

Authors: nan

Publication: TIPSTER (2023)

DOI: nan

AbstractWhile pre-trained language models (PLMs) have become a de-facto standard promoting the accuracy of text classification tasks, recent studies find that PLMs often predict over-confidently. Although calibration methods have been …...

33410

CICL_DMS at SemEval-2023 Task 11: Learning With Disagreements (Le-Wi-Di)

Authors: nan

Publication: TIPSTER (2023)

DOI: nan

AbstractIn this system paper, we describe our submission for the 11th task of SemEval2023: Learning with Disagreements, or Le-Wi-Di for short. In the task, the assumption that there is a …...

24351

Fine-Grained Argument Understanding with BERT Ensemble Techniques: A Deep Dive into Financial Sentiment Analysis

Authors: nan

Publication: TIPSTER (2023)

DOI: nan

While argument mining has garnered attention over the years, its application in the financial sector remains nascent. This study presents a BERT-based ensemble learning approach tailored for sentiment analysis grounded …...

1108

HEVS-TUW at SemEval-2023 Task 8: Ensemble of Language Models and Rule-based Classifiers for Claims Identification and PICO Extraction

Authors: nan

Publication: TIPSTER (2023)

DOI: nan

AbstractThis paper describes the HEVS-TUW team submission to the SemEval-2023 Task 8: Causal Claims. We participated in two subtasks: (1) causal claims detection and (2) PIO identification. For subtask 1, …...

24725

Multi-task Ensemble Learning for Fake Reviews Detection and Helpfulness Prediction: A Novel Approach

Authors: nan

Publication: TIPSTER (2023)

DOI: nan

AbstractResearch on fake reviews detection and review helpfulness prediction is prevalent, yet most studies tend to focus solely on either fake reviews detection or review helpfulness prediction, considering them separate …...

20036

StFX-NLP at SemEval-2023 Task 4: Unsupervised and Supervised Approaches to Detecting Human Values in Arguments

Authors: nan

Publication: TIPSTER (2023)

DOI: nan

AbstractIn this paper, we discuss our models applied to Task 4: Human Value Detection of SemEval 2023, which incorporated two different embedding techniques to interpret the data. Preliminary experiments were …...

24940

UMUTeam and SINAI at SemEval-2023 Task 9: Multilingual Tweet Intimacy Analysis using Multilingual Large Language Models and Data Augmentation

Authors: nan

Publication: TIPSTER (2023)

DOI: nan

AbstractThis work presents the participation of the UMUTeam and the SINAI research groups in the SemEval-2023 Task 9: Multilingual Tweet Intimacy Analysis. The goal of this task is to predict …...

24938