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Estimating confidence of individual rating predictions in collaborative filtering recommender systems

Maciej A. Mazurowski
2013 Expert systems with applications  
This approach has gained notable popularity both in academic research and in commercial applications.  ...  provide the best performance in terms of separation between predictions of high and low confidence.  ...  This estimate of the Bayesian confidence interval for each prediction can be used in a number of ways depending on the application including: • select only items with a very high confidence of prediction  ... 
doi:10.1016/j.eswa.2012.12.102 fatcat:3xig3xhrfnf4nfpxdd4njmnffu

New directions for diffusion-based network prediction of protein function: incorporating pathways with confidence

Mengfei Cao, Christopher M. Pietras, Xian Feng, Kathryn J. Doroschak, Thomas Schaffner, Jisoo Park, Hao Zhang, Lenore J. Cowen, Benjamin J. Hescott
2014 Computer applications in the biosciences : CABIOS  
We test four popular function prediction methods (majority vote, weighted majority vote, multi-way cut and functional flow) using these different matrices on the Baker's yeast PPI network in crossvalidation  ...  We find that diffusion state distance (DSD), our recent diffusion-based metric for measuring dissimilarity in PPI networks, has natural extensions that incorporate confidence, directions and can even express  ...  ACKNOWLEDGEMENTS Thanks to the CRA-W DREU program which supported K.J.D. to spend the summer doing research with L.J.C. at Tufts.  ... 
doi:10.1093/bioinformatics/btu263 pmid:24931987 pmcid:PMC4058952 fatcat:px2evsqeljbufe4d7xgshlivvm

I Find Your Lack of Uncertainty in Computer Vision Disturbing [article]

Matias Valdenegro-Toro
2021 arXiv   pre-print
Neural networks are used for many real world applications, but often they have problems estimating their own confidence.  ...  This is particularly problematic for computer vision applications aimed at making high stakes decisions with humans and their lives.  ...  Many tree detections with low confidence are also present in the same figure, indicating a problem in localizing the tree in the background.  ... 
arXiv:2104.08188v1 fatcat:to2gzhvmavczrbtndh5nbdhkei

Page 451 of The Journal of the Operational Research Society Vol. 58, Issue 4 [page]

2007 The Journal of the Operational Research Society  
Figure 4 also shows that the model placed applicant | in RH (with confidence greater than 99%) and applicant 2 in NH (with confidence greater than 95%).  ...  Applicant | Applicant 2 Bh Se sere =» ° NH Figure 4 The triangle represents the composite model with several confidence bands.  ... 

PaCo: Probability-based path confidence prediction

Kshitiz Malik, Mayank Agarwal, Vikram Dhar, Matthew I. Frank
2008 High-Performance Computer Architecture  
Accurate path confidence prediction is critical for applications like pipeline gating and confidence-based SMT fetch prioritization.  ...  In pipeline gating, while the best conventional predictor can reduce badpath instructions executed by 7% with a small loss in performance, PaCo can reduce badpath instructions by 32% without any performance  ...  We found that the path confidence estimate derived from PaCo was very accurate, with a low RMS error.  ... 
doi:10.1109/hpca.2008.4658627 dblp:conf/hpca/MalikADF08 fatcat:2wm3wg6b7vcs3fztrtsceua5ri

Performance estimation of embedded software with confidence levels

Marco Lattuada, Fabrizio Ferrandi
2012 17th Asia and South Pacific Design Automation Conference  
In this paper we propose a methodology, based on statistical analysis, that provides a prediction interval on the estimation and a confidence level on meeting a time constraint.  ...  Estimation techniques based on mathematical models are usually preferred during this phase since they provide quite accurate estimation of the application performance in a fast way.  ...  Performance Prediction: a new application a is analyzed in order to compute: • punctual prediction y xa of execution time (Equation 3), • prediction interval P I with a given confidence level (Equation  ... 
doi:10.1109/aspdac.2012.6165022 dblp:conf/aspdac/LattuadaF12 fatcat:tae5nofj45cw5mq7uo7bb3kofu

An Exploration of Location Error Estimation [chapter]

David Dearman, Alex Varshavsky, Eyal de Lara, Khai N. Truong
2007 Lecture Notes in Computer Science  
We report findings obtained under four different error visualization conditions and show significant benefit in revealing the error of location predictions to the user in location finding tasks.  ...  This paper explores the effect of revealing the error of location predictions to the enduser in a location finding field study.  ...  This research is supported in part by the Natural Science and Engineering Research Council of Canada (NSERC) and the Walter C. Sumner Foundation.  ... 
doi:10.1007/978-3-540-74853-3_11 fatcat:asxfs4tdprayfbdtrksfsyhnua

Confidence estimation for NLP applications

Simona Gandrabur, George Foster, Guy Lapalme
2006 ACM Transactions on Speech and Language Processing  
We give an overview of the application of confidence estimation in various fields of Natural Language Processing, and present experimental results for speech recognition, spoken language understanding,  ...  Confidence measures are a practical solution for improving the usefulness of Natural Language Processing applications.  ...  ACKNOWLEDGMENT The authors wish to thank Didier Guillevic and Yves Normandin for their contribution in providing the experimental results regarding the ASR application we presented.  ... 
doi:10.1145/1177055.1177057 dblp:journals/tslp/GandraburFL06 fatcat:funmvci2sfhk3davwffajqkhze

Malware Detection with Confidence Guarantees on Android Devices [chapter]

Nestoras Georgiou, Andreas Konstantinidis, Harris Papadopoulos
2016 IFIP Advances in Information and Communication Technology  
with a confidence and a credibility measure for its prediction.  ...  This means that we can have a certain prediction for the large majority of applications with a very small risk, while for applications with uncertain predictions further investigation might be the best  ... 
doi:10.1007/978-3-319-44944-9_35 fatcat:fphpt7n7orh63br3tadhksh33u

Likelihood based observability analysis and confidence intervals for predictions of dynamic models

Clemens Kreutz, Andreas Raue, Jens Timmer
2012 BMC Systems Biology  
In this article it is shown that a so-called prediction profile likelihood yields reliable confidence intervals for model predictions, despite arbitrarily complex and high-dimensional shapes of the confidence  ...  Prediction confidence intervals of the dynamic states allow a data-based observability analysis.  ...  Ursula Klingmüller and their groups for their support and their experience in practically relevant issues.  ... 
doi:10.1186/1752-0509-6-120 pmid:22947028 pmcid:PMC3490710 fatcat:d3274vlqa5a23o5c5piy3tqmsq

Assessment of Prediction Confidence and Domain Extrapolation of Two Structure–Activity Relationship Models for Predicting Estrogen Receptor Binding Activity

Weida Tong, Qian Xie, Huixiao Hong, Leming Shi, Hong Fang, Roger Perkins
2004 Environmental Health Perspectives  
We used an extensive cross-validation process to define an applicability domain for model predictions based on two quantitative measures: prediction confidence and domain extrapolation.  ...  For prediction in the high confidence domain, accuracy was inversely proportional to the degree of domain extrapolation.  ...  We demonstrated in this study that there could be more than a 22% difference in prediction accuracy for the chemicals with high confidence compared with those with low confidence.  ... 
doi:10.1289/txg.7125 pmid:15345371 pmcid:PMC1277118 fatcat:lqqnkkzpmvfe7ohvjfijut6sye

Multiple cue integration in transductive confidence machines for head pose classification

Vineeth Balasubramanian, Sethuraman Panchanathan, Shayok Chakraborty
2008 2008 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops  
An important facet of learning in an online setting is the confidence associated with a prediction on a given test data point.  ...  We present a statistical approach in this work to associate a confidence value with a predicted class label in an online learning scenario.  ...  necessary to make a prediction with high confidence and not make a prediction at all when the system is not very confident of a prediction.  ... 
doi:10.1109/cvprw.2008.4563070 dblp:conf/cvpr/Balasubramanian08 fatcat:f6pbt6n3lbevfh6kpdjjzxxyoy

Storage free confidence estimation for the TAGE branch predictor

Andre Seznec
2011 2011 IEEE 17th International Symposium on High Performance Computer Architecture  
Moreover a slight modification of the predictor automaton allows to discriminate the prediction in three classes, low-confidence (with a misprediction rate in the 30 % range), medium confidence (with a  ...  We show that the observation of the outputs of the predictor tables is sufficient to grade the confidence in the branch predictions with a very good granularity.  ...  rate in the 30 % range), medium confidence predictions (with a misprediction rate in 8-12% range) and high confidence predictions (with a misprediction rate lower than 1 %).  ... 
doi:10.1109/hpca.2011.5749750 dblp:conf/hpca/Seznec11 fatcat:jrucge6bbbdpxpcvzsavjnoqdq

Concepts and Applications of Conformal Prediction in Computational Drug Discovery [article]

Isidro Cortés-Ciriano, Andreas Bender
2019 arXiv   pre-print
For instance, at a confidence level of 90% the true value will be within the predicted confidence intervals in at least 90% of the cases.  ...  In this review, we summarize underlying concepts and practical applications of CP with a particular focus on virtual screening and activity modelling, and list open source implementations of relevant software  ...  predictions with the desired confidence in turn.  ... 
arXiv:1908.03569v1 fatcat:evr67kv32ve4dg6yd3iqg5ukd4

Confidence estimation for speculation control

Dirk Grunwald, Artur Klauser, Srilatha Manne, Andrew Pleszkun
1998 SIGARCH Computer Architecture News  
In this paper, we introduce performance metrics to compare confidence estimation mechanisms, and argue that these metrics are appropriate for speculation control.  ...  The outcome of data and control decisions is predicted, and the operations are speculatively executed and only committed if the original predictions were correct.  ...  MIP-9706286 and in part by ARPA contract ARMY DABT63-94-C-0029.  ... 
doi:10.1145/279361.279376 fatcat:6x4yrta7rfbtdj2oiqltqohdxm
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