default search action
Google
Google Scholar
Semantic Scholar
Internet Archive Scholar
CiteSeerX
ORCIDBernhard Pfahringer
Person information
Refine list
refinements active!
zoomed in on ?? of ?? records
view refined list in
export refined list as
showing all ?? records
2020 – today
- 2025
[j44]Zijing Zhang
, Vimal Kumar, Bernhard Pfahringer, Albert Bifet:
Ai-enabled automated common vulnerability scoring from common vulnerabilities and exposures descriptions. Int. J. Inf. Sec. 24(1): 16 (2025)- 2024
- [j43]Fabrício Ceschin, Marcus Botacin, Albert Bifet, Bernhard Pfahringer, Luiz S. Oliveira, Heitor Murilo Gomes, André Grégio:
Machine Learning (In) Security: A Stream of Problems. DTRAP 5(1): 9:1-9:32 (2024) - [j42]Hongyu Wang, Eibe Frank, Bernhard Pfahringer, Michael Mayo, Geoff Holmes:
Feature extractor stacking for cross-domain few-shot learning. Mach. Learn. 113(1): 121-158 (2024) - [j41]Nuwan Gunasekara, Bernhard Pfahringer, Heitor Murilo Gomes, Albert Bifet:
Gradient boosted trees for evolving data streams. Mach. Learn. 113(5): 3325-3352 (2024) - [c151]Reginaldo Luna, Guilherme Weigert Cassales, Bernhard Pfahringer, Albert Bifet, Heitor Murilo Gomes, Hermes Senger:
Mini-batching with Fused Training and Testing for Data Streams Processing on the Edge. CF 2024 - [c150]Filippo Leveni, Guilherme Weigert Cassales, Bernhard Pfahringer, Albert Bifet, Giacomo Boracchi:
Online Isolation Forest. ICML 2024 - [c149]Yun Sing Koh, Albert Bifet, Karin R. Bryan, Guilherme Weigert Cassales, Olivier Graffeuille, Nick Jin Sean Lim, Phil Mourot, Ding Ning, Bernhard Pfahringer, Varvara Vetrova, Heitor Murilo Gomes:
Time-Evolving Data Science and Artificial Intelligence for Advanced Open Environmental Science (TAIAO) Programme. IJCAI 2024: 7314-7322 - [c148]Nuwan Gunasekara, Bernhard Pfahringer, Heitor Murilo Gomes, Albert Bifet, Yun Sing Koh:
Recurrent Concept Drifts on Data Streams. IJCAI 2024: 8029-8037 - [c147]Yibin Sun, Bernhard Pfahringer, Heitor Murilo Gomes, Albert Bifet:
Adaptive Prediction Interval for Data Stream Regression. PAKDD (3) 2024: 130-141 - [c146]Marco Heyden, Heitor Murilo Gomes, Edouard Fouché, Bernhard Pfahringer, Klemens Böhm:
Leveraging Plasticity in Incremental Decision Trees. ECML/PKDD (5) 2024: 38-54 - [c145]Yibin Sun, Heitor Murilo Gomes, Bernhard Pfahringer, Albert Bifet:
Real-Time Energy Pricing in New Zealand: An Evolving Stream Analysis. PRICAI (5) 2024: 91-97 - [i29]Yibin Sun, Heitor Murilo Gomes, Bernhard Pfahringer, Albert Bifet:
Real-Time Energy Pricing in New Zealand: An Evolving Stream Analysis. CoRR abs/2408.16187 (2024) - [i28]Muhammad Zain Ali, Yuxia Wang, Bernhard Pfahringer, Tony Smith:
Detection of Human and Machine-Authored Fake News in Urdu. CoRR abs/2410.19517 (2024) - 2023
- [j40]Mi Li, Eibe Frank, Bernhard Pfahringer:
Large scale K-means clustering using GPUs. Data Min. Knowl. Discov. 37(1): 67-109 (2023) - [j39]Jesus Antonanzas, Yunzhe Jia, Eibe Frank, Albert Bifet, Bernhard Pfahringer:
teex: A toolbox for the evaluation of explanations. Neurocomputing 555: 126642 (2023) - [j38]Guilherme Weigert Cassales, Heitor Murilo Gomes, Albert Bifet, Bernhard Pfahringer, Hermes Senger:
Balancing Performance and Energy Consumption of Bagging Ensembles for the Classification of Data Streams in Edge Computing. IEEE Trans. Netw. Serv. Manag. 20(3): 3038-3054 (2023) - [c144]Anton Lee, Yaqian Zhang, Heitor Murilo Gomes, Albert Bifet, Bernhard Pfahringer:
Look At Me, No Replay! SurpriseNet: Anomaly Detection Inspired Class Incremental Learning. CIKM 2023: 4038-4042 - [c143]Hongyu Wang, Eibe Frank, Bernhard Pfahringer, Geoffrey Holmes:
Self-trained Centroid Classifiers for Semi-supervised Cross-domain Few-shot Learning. CoLLAs 2023: 481-492 - [c142]Nuwan Gunasekara, Bernhard Pfahringer, Heitor Murilo Gomes, Albert Bifet:
Survey on Online Streaming Continual Learning. IJCAI 2023: 6628-6637 - [i27]Anton Lee, Yaqian Zhang, Heitor Murilo Gomes, Albert Bifet, Bernhard Pfahringer:
Look At Me, No Replay! SurpriseNet: Anomaly Detection Inspired Class Incremental Learning. CoRR abs/2310.20052 (2023) - 2022
- [j37]Felipe Bravo-Marquez, Arun Khanchandani, Bernhard Pfahringer:
Incremental Word Vectors for Time-Evolving Sentiment Lexicon Induction. Cogn. Comput. 14(1): 425-441 (2022) - [j36]Yibin Sun, Bernhard Pfahringer, Heitor Murilo Gomes, Albert Bifet:
SOKNL: A novel way of integrating K-nearest neighbours with adaptive random forest regression for data streams. Data Min. Knowl. Discov. 36(5): 2006-2032 (2022) - [j35]Emanuele Pio Barracchia, Gianvito Pio, Albert Bifet, Heitor Murilo Gomes, Bernhard Pfahringer, Michelangelo Ceci:
LP-ROBIN: Link prediction in dynamic networks exploiting incremental node embedding. Inf. Sci. 606: 702-721 (2022) - [c141]Vithya Yogarajan, Jacob Montiel, Tony Smith, Bernhard Pfahringer:
Predicting COVID-19 Patient Shielding: A Comprehensive Study. AI 2022: 332-343 - [c140]Rajchada Chanajitt, Bernhard Pfahringer, Heitor Murilo Gomes, Vithya Yogarajan:
Multiclass Malware Classification Using Either Static Opcodes or Dynamic API Calls. AI 2022: 427-441 - [c139]Attaullah Sahito, Eibe Frank, Bernhard Pfahringer:
Better Self-training for Image Classification Through Self-supervision. AI 2022: 645-657 - [c138]Nuwan Gunasekara, Heitor Murilo Gomes, Albert Bifet, Bernhard Pfahringer:
Adaptive Neural Networks for Online Domain Incremental Continual Learning. DS 2022: 89-103 - [c137]Hongyu Wang, Huon Fraser, Henry Gouk, Eibe Frank, Bernhard Pfahringer, Michael Mayo, Geoff Holmes:
Experiments in Cross-domain Few-shot Learning for Image Classification: Extended Abstract. Meta-Knowledge Transfer @ ECML/PKDD 2022: 81-83 - [c136]Vithya Yogarajan, Bernhard Pfahringer, Tony Smith, Jacob Montiel:
Concatenating BioMed-Transformers to Tackle Long Medical Documents and to Improve the Prediction of Tail-End Labels. ICANN (2) 2022: 209-221 - [c135]Rajchada Chanajitt, Bernhard Pfahringer, Heitor Murilo Gomes:
A Comparison of Neural Network Architectures for Malware Classification Based on Noriben Operation Sequences. ICANN (1) 2022: 428-440 - [c134]Nuwan Gunasekara, Heitor Murilo Gomes, Albert Bifet, Bernhard Pfahringer:
Adaptive Online Domain Incremental Continual Learning. ICANN (1) 2022: 491-502 - [c133]Nuwan Gunasekara, Heitor Murilo Gomes, Bernhard Pfahringer, Albert Bifet:
Online Hyperparameter Optimization for Streaming Neural Networks. IJCNN 2022: 1-9 - [c132]Chen Zheng, Bernhard Pfahringer, Michael Mayo:
Alzheimer's Disease Detection via a Surrogate Brain Age Prediction Task using 3D Convolutional Neural Networks. IJCNN 2022: 1-8 - [c131]Yaqian Zhang, Bernhard Pfahringer, Eibe Frank, Albert Bifet, Nick Jin Sean Lim, Yunzhe Jia:
A simple but strong baseline for online continual learning: Repeated Augmented Rehearsal. NeurIPS 2022 - [i26]Guilherme Weigert Cassales, Heitor Murilo Gomes, Albert Bifet, Bernhard Pfahringer, Hermes Senger:
Balancing Performance and Energy Consumption of Bagging Ensembles for the Classification of Data Streams in Edge Computing. CoRR abs/2201.06205 (2022) - [i25]Hongyu Wang, Eibe Frank, Bernhard Pfahringer, Michael Mayo, Geoffrey Holmes:
Cross-domain Few-shot Meta-learning Using Stacking. CoRR abs/2205.05831 (2022) - [i24]Yaqian Zhang, Bernhard Pfahringer, Eibe Frank, Albert Bifet, Nick Jin Sean Lim, Yunzhe Jia:
A simple but strong baseline for online continual learning: Repeated Augmented Rehearsal. CoRR abs/2209.13917 (2022) - 2021
- [j34]Guilherme Weigert Cassales, Heitor Murilo Gomes, Albert Bifet, Bernhard Pfahringer, Hermes Senger:
Improving the performance of bagging ensembles for data streams through mini-batching. Inf. Sci. 580: 260-282 (2021) - [j33]Jesse Read, Bernhard Pfahringer, Geoff Holmes, Eibe Frank:
Classifier Chains: A Review and Perspectives. J. Artif. Intell. Res. 70: 683-718 (2021) - [j32]Henry Gouk, Eibe Frank, Bernhard Pfahringer, Michael J. Cree:
Regularisation of neural networks by enforcing Lipschitz continuity. Mach. Learn. 110(2): 393-416 (2021) - [c130]Vithya Yogarajan, Jacob Montiel, Tony Smith, Bernhard Pfahringer:
Transformers for Multi-label Classification of Medical Text: An Empirical Comparison. AIME 2021: 114-123 - [c129]Rajchada Chanajitt, Bernhard Pfahringer, Heitor Murilo Gomes:
Combining Static and Dynamic Analysis to Improve Machine Learning-based Malware Classification. DSAA 2021: 1-10 - [c128]Alan Ansell, Felipe Bravo-Marquez, Bernhard Pfahringer:
PolyLM: Learning about Polysemy through Language Modeling. EACL 2021: 563-574 - [c127]Saulo Martiello Mastelini, Jacob Montiel, Heitor Murilo Gomes, Albert Bifet, Bernhard Pfahringer, André C. P. L. F. de Carvalho:
Fast and lightweight binary and multi-branch Hoeffding Tree Regressors. ICDM (Workshops) 2021: 380-388 - [c126]Yunzhe Jia, Eibe Frank, Bernhard Pfahringer, Albert Bifet, Nick Jin Sean Lim:
Studying and Exploiting the Relationship Between Model Accuracy and Explanation Quality. ECML/PKDD (2) 2021: 699-714 - [i23]Alan Ansell, Felipe Bravo-Marquez, Bernhard Pfahringer:
PolyLM: Learning about Polysemy through Language Modeling. CoRR abs/2101.10448 (2021) - [i22]Attaullah Sahito, Eibe Frank, Bernhard Pfahringer:
Better Self-training for Image Classification through Self-supervision. CoRR abs/2109.00778 (2021) - [i21]Attaullah Sahito, Eibe Frank, Bernhard Pfahringer:
Transfer of Pretrained Model Weights Substantially Improves Semi-Supervised Image Classification. CoRR abs/2109.00788 (2021) - [i20]Attaullah Sahito, Eibe Frank, Bernhard Pfahringer:
Semi-Supervised Learning using Siamese Networks. CoRR abs/2109.00794 (2021) - [i19]Vithya Yogarajan, Jacob Montiel, Tony Smith, Bernhard Pfahringer:
Predicting COVID-19 Patient Shielding: A Comprehensive Study. CoRR abs/2110.00183 (2021) - [i18]Vithya Yogarajan, Bernhard Pfahringer, Tony Smith, Jacob Montiel:
Improving Predictions of Tail-end Labels using Concatenated BioMed-Transformers for Long Medical Documents. CoRR abs/2112.01718 (2021) - [i17]Guilherme Weigert Cassales, Heitor Murilo Gomes, Albert Bifet, Bernhard Pfahringer, Hermes Senger:
Improving the performance of bagging ensembles for data streams through mini-batching. CoRR abs/2112.09834 (2021) - 2020
- [j31]Vithya Yogarajan, Bernhard Pfahringer, Michael Mayo:
A review of Automatic end-to-end De-Identification: Is High Accuracy the Only Metric? Appl. Artif. Intell. 34(3): 251-269 (2020) - [j30]Adriano Rivolli, Jesse Read, Carlos Soares, Bernhard Pfahringer, André C. P. L. F. de Carvalho:
An empirical analysis of binary transformation strategies and base algorithms for multi-label learning. Mach. Learn. 109(8): 1509-1563 (2020) - [c125]Vithya Yogarajan, Henry Gouk, Tony Smith, Michael Mayo, Bernhard Pfahringer:
Comparing High Dimensional Word Embeddings Trained on Medical Text to Bag-of-Words for Predicting Medical Codes. ACIIDS (1) 2020: 97-108 - [c124]Attaullah Sahito, Eibe Frank, Bernhard Pfahringer:
Transfer of Pretrained Model Weights Substantially Improves Semi-supervised Image Classification. Australasian Conference on Artificial Intelligence 2020: 433-444 - [c123]Hongyu Wang, Henry Gouk, Eibe Frank, Bernhard Pfahringer, Michael Mayo:
A Comparison of Machine Learning Methods for Cross-Domain Few-Shot Learning. Australasian Conference on Artificial Intelligence 2020: 445-457 - [c122]Alessio Bernardo, Heitor Murilo Gomes, Jacob Montiel, Bernhard Pfahringer, Albert Bifet, Emanuele Della Valle:
C-SMOTE: Continuous Synthetic Minority Oversampling for Evolving Data Streams. IEEE BigData 2020: 483-492 - [c121]Guilherme Weigert Cassales, Heitor Murilo Gomes, Albert Bifet, Bernhard Pfahringer, Hermes Senger:
Improving parallel performance of ensemble learners for streaming data through data locality with mini-batching. HPCC/DSS/SmartCity 2020: 138-146 - [c120]Maroua Bahri, Bernhard Pfahringer, Albert Bifet, Silviu Maniu:
Efficient Batch-Incremental Classification Using UMAP for Evolving Data Streams. IDA 2020: 40-53 - [c119]Heitor Murilo Gomes, Jacob Montiel, Saulo Martiello Mastelini, Bernhard Pfahringer, Albert Bifet:
On Ensemble Techniques for Data Stream Regression. IJCNN 2020: 1-8 - [c118]Jacob Montiel, Rory Mitchell, Eibe Frank, Bernhard Pfahringer, Talel Abdessalem, Albert Bifet:
Adaptive XGBoost for Evolving Data Streams. IJCNN 2020: 1-8 - [c117]Matthias Carnein, Heike Trautmann, Albert Bifet, Bernhard Pfahringer:
confStream: Automated Algorithm Selection and Configuration of Stream Clustering Algorithms. LION 2020: 80-95 - [i16]Vithya Yogarajan, Jacob Montiel, Tony Smith, Bernhard Pfahringer:
Seeing The Whole Patient: Using Multi-Label Medical Text Classification Techniques to Enhance Predictions of Medical Codes. CoRR abs/2004.00430 (2020) - [i15]Jacob Montiel, Rory Mitchell, Eibe Frank, Bernhard Pfahringer, Talel Abdessalem, Albert Bifet:
Adaptive XGBoost for Evolving Data Streams. CoRR abs/2005.07353 (2020) - [i14]Fabricio Ceschin, Heitor Murilo Gomes, Marcus Botacin, Albert Bifet, Bernhard Pfahringer, Luiz S. Oliveira, André Grégio:
Machine Learning (In) Security: A Stream of Problems. CoRR abs/2010.16045 (2020)
2010 – 2019
- 2019
- [j29]Jean Paul Barddal, Fabrício Enembreck, Heitor Murilo Gomes, Albert Bifet, Bernhard Pfahringer:
Merit-guided dynamic feature selection filter for data streams. Expert Syst. Appl. 116: 227-242 (2019) - [j28]Jean Paul Barddal, Fabrício Enembreck, Heitor Murilo Gomes, Albert Bifet, Bernhard Pfahringer:
Boosting decision stumps for dynamic feature selection on data streams. Inf. Syst. 83: 13-29 (2019) - [j27]Felipe Bravo-Marquez, Eibe Frank, Bernhard Pfahringer, Saif M. Mohammad:
AffectiveTweets: a Weka Package for Analyzing Affect in Tweets. J. Mach. Learn. Res. 20: 92:1-92:6 (2019) - [j26]Heitor Murilo Gomes, Albert Bifet, Jesse Read, Jean Paul Barddal, Fabrício Enembreck, Bernhard Pfahringer, Geoff Holmes, Talel Abdessalem:
Correction to: Adaptive random forests for evolving data stream classification. Mach. Learn. 108(10): 1877-1878 (2019) - [c116]Alex Yuxuan Peng, Yun Sing Koh, Patricia Riddle, Bernhard Pfahringer:
Investigating the effect of novel classes in semi-supervised learning. ACML 2019: 615-630 - [c115]Henry Gouk, Bernhard Pfahringer, Eibe Frank:
Stochastic Gradient Trees. ACML 2019: 1094-1109 - [c114]Attaullah Sahito, Eibe Frank, Bernhard Pfahringer:
Semi-supervised Learning Using Siamese Networks. Australasian Conference on Artificial Intelligence 2019: 586-597 - [c113]Heitor Murilo Gomes, Rodrigo Fernandes de Mello, Bernhard Pfahringer, Albert Bifet:
Feature Scoring using Tree-Based Ensembles for Evolving Data Streams. IEEE BigData 2019: 761-769 - [c112]Jörg Wicker, Yan Cathy Hua, Rayner Rebello, Bernhard Pfahringer:
XOR-Based Boolean Matrix Decomposition. ICDM 2019: 638-647 - [c111]Tim Leathart, Eibe Frank, Bernhard Pfahringer, Geoffrey Holmes:
On Calibration of Nested Dichotomies. PAKDD (1) 2019: 69-80 - [c110]Tim Leathart, Eibe Frank, Bernhard Pfahringer, Geoffrey Holmes:
Ensembles of Nested Dichotomies with Multiple Subset Evaluation. PAKDD (1) 2019: 81-93 - [c109]Matthias Carnein, Heike Trautmann, Albert Bifet, Bernhard Pfahringer:
Towards Automated Configuration of Stream Clustering Algorithms. PKDD/ECML Workshops (1) 2019: 137-143 - [c108]Alan Ansell, Felipe Bravo-Marquez, Bernhard Pfahringer:
An ELMo-inspired approach to SemDeep-5's Word-in-Context task. SemDeep@IJCAI 2019: 21-25 - [i13]Henry Gouk, Bernhard Pfahringer, Eibe Frank:
Stochastic Gradient Trees. CoRR abs/1901.07777 (2019) - [i12]Vithya Yogarajan, Bernhard Pfahringer, Michael Mayo:
Automatic end-to-end De-identification: Is high accuracy the only metric? CoRR abs/1901.10583 (2019) - [i11]Jesse Read, Bernhard Pfahringer, Geoff Holmes, Eibe Frank:
Classifier Chains: A Review and Perspectives. CoRR abs/1912.13405 (2019) - 2018
- [j25]Jan N. van Rijn, Geoffrey Holmes, Bernhard Pfahringer, Joaquin Vanschoren:
The online performance estimation framework: heterogeneous ensemble learning for data streams. Mach. Learn. 107(1): 149-176 (2018) - [j24]Felipe Bravo-Marquez, Eibe Frank, Bernhard Pfahringer:
Transferring sentiment knowledge between words and tweets. Web Intell. 16(4): 203-220 (2018) - [c107]Bartosz Krawczyk, Bernhard Pfahringer, Michal Wozniak:
Combining active learning with concept drift detection for data stream mining. IEEE BigData 2018: 2239-2244 - [c106]Edmond Zhang, Reece Robinson, Bernhard Pfahringer:
Deep Holistic Representation Learning from EHR. ISMICT 2018: 1-6 - [c105]Alex Yuxuan Peng, Yun Sing Koh, Patricia Riddle, Bernhard Pfahringer:
Using Supervised Pretraining to Improve Generalization of Neural Networks on Binary Classification Problems. ECML/PKDD (1) 2018: 410-425 - [c104]Henry Gouk, Bernhard Pfahringer, Eibe Frank, Michael J. Cree:
MaxGain: Regularisation of Neural Networks by Constraining Activation Magnitudes. ECML/PKDD (1) 2018: 541-556 - [c103]Lanqin Yuan, Bernhard Pfahringer, Jean Paul Barddal:
Iterative subset selection for feature drifting data streams. SAC 2018: 510-517 - [i10]Henry Gouk, Eibe Frank, Bernhard Pfahringer, Michael J. Cree:
Regularisation of Neural Networks by Enforcing Lipschitz Continuity. CoRR abs/1804.04368 (2018) - [i9]Henry Gouk, Bernhard Pfahringer, Eibe Frank, Michael J. Cree:
MaxGain: Regularisation of Neural Networks by Constraining Activation Magnitudes. CoRR abs/1804.05965 (2018) - [i8]Tim Leathart, Eibe Frank, Geoffrey Holmes, Bernhard Pfahringer:
Probability Calibration Trees. CoRR abs/1808.00111 (2018) - [i7]Tim Leathart, Eibe Frank, Bernhard Pfahringer, Geoffrey Holmes:
Ensembles of Nested Dichotomies with Multiple Subset Evaluation. CoRR abs/1809.02740 (2018) - [i6]Tim Leathart, Eibe Frank, Bernhard Pfahringer, Geoffrey Holmes:
On the Calibration of Nested Dichotomies for Large Multiclass Tasks. CoRR abs/1809.02744 (2018) - [i5]Vithya Yogarajan, Michael Mayo, Bernhard Pfahringer:
A survey of automatic de-identification of longitudinal clinical narratives. CoRR abs/1810.06765 (2018) - 2017
- [j23]Jean Paul Barddal, Heitor Murilo Gomes, Fabrício Enembreck, Bernhard Pfahringer:
A survey on feature drift adaptation: Definition, benchmark, challenges and future directions. J. Syst. Softw. 127: 278-294 (2017) - [j22]Heitor Murilo Gomes, Albert Bifet, Jesse Read, Jean Paul Barddal, Fabrício Enembreck, Bernhard Pfahringer, Geoff Holmes, Talel Abdessalem:
Adaptive random forests for evolving data stream classification. Mach. Learn. 106(9-10): 1469-1495 (2017) - [c102]Tim Leathart, Eibe Frank, Geoffrey Holmes, Bernhard Pfahringer:
Probability Calibration Trees. ACML 2017: 145-160 - [c101]Min-Hsien Weng, Bernhard Pfahringer, Mark Utting:
Static techniques for reducing memory usage in the C implementation of whiley programs. ACSW 2017: 15:1-15:8 - [c100]Paula Branco, Luís Torgo, Rita P. Ribeiro, Eibe Frank, Bernhard Pfahringer, Markus Michael Rau:
Learning Through Utility Optimization in Regression Tasks. DSAA 2017: 30-39 - [c99]Vítor Cerqueira, Luís Torgo, Mariana Oliveira, Bernhard Pfahringer:
Dynamic and Heterogeneous Ensembles for Time Series Forecasting. DSAA 2017: 242-251 - [c98]Albert Bifet, Jiajin Zhang, Wei Fan, Cheng He, Jianfeng Zhang, Jianfeng Qian, Geoff Holmes, Bernhard Pfahringer:
Extremely Fast Decision Tree Mining for Evolving Data Streams. KDD 2017: 1733-1742 - [r3]Bernhard Pfahringer:
Conjunctive Normal Form. Encyclopedia of Machine Learning and Data Mining 2017: 260-261 - [r2]Bernhard Pfahringer:
Disjunctive Normal Form. Encyclopedia of Machine Learning and Data Mining 2017: 371-372 - 2016
- [j21]Jesse Read, Peter Reutemann, Bernhard Pfahringer, Geoff Holmes:
MEKA: A Multi-label/Multi-target Extension to WEKA. J. Mach. Learn. Res. 17: 21:1-21:5 (2016) - [j20]Felipe Bravo-Marquez, Eibe Frank, Bernhard Pfahringer:
Building a Twitter opinion lexicon from automatically-annotated tweets. Knowl. Based Syst. 108: 65-78 (2016) - [c97]Henry Gouk, Bernhard Pfahringer, Michael J. Cree:
Learning Distance Metrics for Multi-Label Classification. ACML 2016: 318-333 - [c96]Felipe Bravo-Marquez, Eibe Frank, Bernhard Pfahringer:
Annotate-Sample-Average (ASA): A New Distant Supervision Approach for Twitter Sentiment Analysis. ECAI 2016: 498-506 - [c95]Jean Paul Barddal, Heitor Murilo Gomes, Fabrício Enembreck, Bernhard Pfahringer, Albert Bifet:
On Dynamic Feature Weighting for Feature Drifting Data Streams. ECML/PKDD (2) 2016: 129-144 - [c94]Tim Leathart, Bernhard Pfahringer, Eibe Frank:
Building Ensembles of Adaptive Nested Dichotomies with Random-Pair Selection. ECML/PKDD (2) 2016: 179-194 - [c93]Felipe Bravo-Marquez, Eibe Frank, Bernhard Pfahringer:
From Opinion Lexicons to Sentiment Classification of Tweets and Vice Versa: A Transfer Learning Approach. WI 2016: 145-152 - [c92]Felipe Bravo-Marquez, Eibe Frank, Saif M. Mohammad, Bernhard Pfahringer:
Determining Word-Emotion Associations from Tweets by Multi-label Classification. WI 2016: 536-539 - [i4]Tim Leathart, Bernhard Pfahringer, Eibe Frank:
Building Ensembles of Adaptive Nested Dichotomies with Random-Pair Selection. CoRR abs/1604.01854 (2016) - 2015
- [j19]Luís Torgo