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Calibrating Structured Output Predictors for Natural Language Processing [article]

Abhyuday Jagannatha, Hong Yu
2020 arXiv   pre-print
We address the problem of calibrating prediction confidence for output entities of interest in natural language processing (NLP) applications.  ...  In this study, we propose a general calibration scheme for output entities of interest in neural-network based structured prediction models.  ...  Introduction Several modern machine-learning based Natural Language Processing (NLP) systems can provide a confidence score with their output predictions.  ... 
arXiv:2004.04361v2 fatcat:s3ao3uxwcvdfvggu6k57coyfc4

Calibrating Structured Output Predictors for Natural Language Processing

Abhyuday Jagannatha, hong yu
2020 Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics  
We address the problem of calibrating prediction confidence for output entities of interest in natural language processing (NLP) applications.  ...  In this study, we propose a general calibration scheme for output entities of interest in neural network based structured prediction models.  ...  Introduction Several modern machine-learning based Natural Language Processing (NLP) systems can provide a confidence score with their output predictions.  ... 
doi:10.18653/v1/2020.acl-main.188 pmid:33612961 pmcid:PMC7890517 fatcat:wwffjpnkhbauhotzl7lqnymme4


A. Petrasova, V. Petras, D. Van Berkel, B. A. Harmon, H. Mitasova, R. K. Meentemeyer
2016 The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences  
GRASS GIS provides efficient libraries for FUTURES model development as well as standard GIS tools and graphical user interface for model users.  ...  The developed dataset and tutorial for this case study enable researchers to experiment with the model, explore its potential or even modify the model for their applications.  ...  ACKNOWLEDGEMENTS We would like to thank Monica Dorning and Douglas Shoemaker for discussing with us the original model implementation, and Brian Pickard and Georgina Sanchez for testing new FUTURES implementation  ... 
doi:10.5194/isprs-archives-xli-b7-953-2016 fatcat:xyeoq2wcgrhbxeq4ptptw45mba

Men Also Like Shopping: Reducing Gender Bias Amplification using Corpus-level Constraints

Jieyu Zhao, Tianlu Wang, Mark Yatskar, Vicente Ordonez, Kai-Wei Chang
2017 Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing  
We propose to inject corpus-level constraints for calibrating existing structured prediction models and design an algorithm based on Lagrangian relaxation for collective inference.  ...  Language is increasingly being used to define rich visual recognition problems with supporting image collections sourced from the web.  ...  While RBA can be applied to any structured predictor, it is unclear whether different predictors amplify bias more or less. Furthermore, we presented only one method for measuring bias.  ... 
doi:10.18653/v1/d17-1323 dblp:conf/emnlp/ZhaoWYOC17 fatcat:4plqmj4wwncpzhkw2jhs7xmyqy

Statistically downscaled climate dataset for East Africa

Solomon H. Gebrechorkos, Stephan Hülsmann, Christian Bernhofer
2019 Scientific Data  
The predictors are analysed more than 16458 times and we provided 20 ensembles for the current (1961-2005) and future (2006-2100, under RCP2.6, RCP4.5, and RCP8.5) climate.  ...  For many regions of the world, current climate change projections are only available at coarser spatial resolution from Global Climate Models (GCMs) that cannot directly be used in impact assessment and  ...  Using the selected predictors for each predictand, the model is calibrated under unconditional (temperature) and conditional (precipitation) processes on a monthly scale.  ... 
doi:10.1038/s41597-019-0038-1 pmid:30988412 pmcid:PMC6472408 fatcat:3ouxkjl43zfztienfst74qorwm

Predicting protein function and other biomedical characteristics with heterogeneous ensembles

Sean Whalen, Om Prakash Pandey, Gaurav Pandey
2016 Methods  
: (i) better balance of diversity and performance, (ii) more effective calibration of outputs and (iii) more robust incorporation of additional base predictors.  ...  regarding the ideal predictor for specific problems.  ...  Acknowledgments We thank the Icahn Institute for Genomics and Multiscale Biology and the Minerva supercomputing team for their financial and technical support of this work.  ... 
doi:10.1016/j.ymeth.2015.08.016 pmid:26342255 pmcid:PMC4718788 fatcat:dwg3lg5rxfe3tntrzdibfucpqe

Predicting Intensive Care Unit admission among patients presenting to the emergency department using machine learning and natural language processing

Marta Fernandes, Rúben Mendes, Susana M. Vieira, Francisca Leite, Carlos Palos, Alistair Johnson, Stan Finkelstein, Steven Horng, Leo Anthony Celi, Ivan Olier
2020 PLoS ONE  
Variables routinely collected at triage were used and natural language processing was applied to the patient chief complaint.  ...  Heart rate, pulse oximetry, respiratory rate and systolic blood pressure were the most important predictors of ICU admission.  ...  Acknowledgments The authors would like to acknowledge both hospitals Beth Israel Deaconess Medical Center and Hospital Beatriz  ngelo for having provided access to their databases for this study.  ... 
doi:10.1371/journal.pone.0229331 pmid:32126097 pmcid:PMC7053743 fatcat:tm4yuclvhjg6nk5v7gifrtdxuq

Interactive Computer Animation of Hand Gestures using Status Estimation with Multiple Regression Analysis

Yoshifumi Kitamura, Tomohiko Higashi, Takayuki Iida, Fumio Kishino
2001 Computer graphics forum (Print)  
Even when the skeletal structure of the user who inputs the motion is different from that of the shape model in the computer, the motion that a user imagines is generated.  ...  This method enables us to make input devices that require minimal user training and computer calibration, and helps to make the user interface intuitive and easy to use.  ...  Exact calibration was not necessary for even a set of users who had a variety of skeletal structures.  ... 
doi:10.1111/1467-8659.00517 fatcat:zkkjppqrszbznipfxa726bz7uq

Rationale production to support clinical decision-making [article]

Niall Taylor, Lei Sha, Dan W Joyce, Thomas Lukasiewicz, Alejo Nevado-Holgado, Andrey Kormilitzin
2021 arXiv   pre-print
With the increasing adoption of electronic health records (EHRs), there is great interest in applications of natural language processing (NLP) to clinical free-text contained within EHRs.  ...  The need to delve into the black-box neural network and derive interpretable explanations of model output is paramount.  ...  Acknowledgments NT is supported by the EPSRC Center for Doctoral Training in Health Data Science (EP/S02428X/1),  ... 
arXiv:2111.07611v1 fatcat:mzja5s5vbbg5hmbn742pyfmvqa

Statistical Postprocessing for Weather Forecasts – Review, Challenges and Avenues in a Big Data World [article]

Stéphane Vannitsem, John Bjørnar Bremnes, Jonathan Demaeyer, Gavin R. Evans, Jonathan Flowerdew, Stephan Hemri, Sebastian Lerch, Nigel Roberts, Susanne Theis, Aitor Atencia, Zied Ben Bouallègue, Jonas Bhend (+12 others)
2020 arXiv   pre-print
The final aim is to provide optimal, automated, seamless forecasts for end users.  ...  Statistical postprocessing techniques are nowadays key components of the forecasting suites in many National Meteorological Services (NMS), with for most of them, the objective of correcting the impact  ...  For a recent overview of computer software for postprocessing and usage examples see Messner (2018) .  ... 
arXiv:2004.06582v1 fatcat:kjruwwm7krgwjp3rrxdb5twrhe

Identifying the Machine Translation Error Types with the Greatest Impact on Post-editing Effort

Joke Daems, Sonia Vandepitte, Robert J. Hartsuiker, Lieve Macken
2017 Frontiers in Psychology  
Coherence, meaning shifts, and structural issues are shown to be good indicators of post-editing effort.  ...  The translation and post-editing process of student translators and professional translators was logged with a combination of keystroke logging and eye-tracking, and the MT output was analyzed with a fine-grained  ...  Calibration was problematic for one of the professionals, their sessions with problematic calibration were removed from the data.  ... 
doi:10.3389/fpsyg.2017.01282 pmid:28824482 pmcid:PMC5539081 fatcat:3bonspuabnd5rcbx74crmu3rei

Assessing long-term fire risk at local scale by means of decision tree technique

Giuseppe Amatulli, Maria João Rodrigues, Marco Trombetti, Raffaella Lovreglio
2006 Journal of Geophysical Research  
Hence fire managers are seeking an unbiased statistical model able to highlight the multivariate spatial relationships between the predictor variables, yielding understandable output readily accessible  ...  The resulting map was then used as input response variable for the CART analysis with fire danger variables used as predictors.  ...  Houston for reviewing the final manuscript and the two anonymous peer reviewers for their important comments.  ... 
doi:10.1029/2005jg000133 fatcat:cqggbzndcbfydd254is5pxv3bq

BERTology Meets Biology: Interpreting Attention in Protein Language Models [article]

Jesse Vig, Ali Madani, Lav R. Varshney, Caiming Xiong, Richard Socher, Nazneen Fatema Rajani
2021 arXiv   pre-print
We also present a three-dimensional visualization of the interaction between attention and protein structure. Code for visualization and analysis is available at  ...  We show that attention: (1) captures the folding structure of proteins, connecting amino acids that are far apart in the underlying sequence, but spatially close in the three-dimensional structure, (2)  ...  Related Work Here we contextualize our techniques and findings in the protein modeling and interpretable neural network literatures, especially in natural language processing.  ... 
arXiv:2006.15222v3 fatcat:lf72u3lgfvfqbawj2ybdeee7pq

BERT-based conformal predictor for sentiment analysis

Lysimachos Maltoudoglou, Andreas Paisios, Harris Papadopoulos
2020 International Symposium on Conformal and Probabilistic Prediction with Applications  
We deal with the Natural Language Processing (NLP) task of Sentiment Analysis (SA) on text, by applying Inductive Conformal Prediction (ICP) on a transformers based model.  ...  Our classifier consists of the BERT model for turning words into contextualized word embeddings with parameters fine-tuned on the used corpus and a fully connected output layer for performing the classification  ...  SA is a task of Natural Language Processing (NLP), but it can also be applied on images or videos of humans to extract similar kind of information from facial expressions, gesture and body language.  ... 
dblp:conf/copa/MaltoudoglouPP20 fatcat:jkmu4hqhfbegla23idwchfcfji

Hydrological modelling using artificial neural networks

C. W. Dawson, R. L. Wilby
2001 Progress in physical geography  
The discussion then addresses related themes of the division and preprocessing of data for model calibration/validation; data standardization techniques; and methods of evaluating ANN model performance  ...  A literature survey underlines the need for clear guidance in current modelling practice, as well as the comparison of ANN methods with more conventional statistical models.  ...  Acknowledgements We thank the anonymous reviewer for constructive comments on our original manuscript. RW was supported by ACACIA (A Consortium for the Application of Climate Impact Assessments).  ... 
doi:10.1177/030913330102500104 fatcat:3phirit2mndqtjcojhvjw3kb7m
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