Seyda Ertekin

Publication Activity (10 Years)

Years Active: 2005-2024
Publications (10 Years): 16

Top Topics

Dimensionality Reduction

Forecasting Accuracy

Hilbert Huang Transform

Top Venues

Publications

Güven Orkun Tanik, Seyda Ertekin
Hierarchical reinforcement Thompson composition. Neural Comput. Appl. 36 (20) (2024)
Pinar Ezgi Duymus, Seyda Ertekin
Alleviating Mode Collapse Problem in Deep Bayesian Active Learning. SIU (2022)
Egemen Sert, Oral Okan, Alper Özbilen, Seyda Ertekin, Suat Özdemir
Linking COVID-19 Perception With Socioeconomic Conditions Using Twitter Data. IEEE Trans. Comput. Soc. Syst. 9 (2) (2022)
Güven Orkun Tanik, Seyda Ertekin
Recursive Compositional Reinforcement Learning for Continuous Control. SIU (2022)
Pinar Ezgi Çöl, Seyda Ertekin
Feature Dimensionality Reduction with Variational Autoencoders in Deep Bayesian Active Learning. SIU (2021)
Mehmet Dinç, Seyda Ertekin, Hadi Özkan, Can Meydanli, Volkan Atalay
Forecasting of Product Quality Through Anomaly Detection. PKDD/ECML Workshops (2) (2019)
Ümit Çavus Büyüksahin, Seyda Ertekin
Prediction Model Selection with Frequency Check on Decomposed Time Series. SIU (2019)
Ümit Çavus Büyüksahin, Seyda Ertekin
Improving forecasting accuracy of time series data using a new ARIMA-ANN hybrid method and empirical mode decomposition. Neurocomputing 361 (2019)
Ümit Çavus Büyüksahin, Seyda Ertekin
Improving forecasting accuracy of time series data using a new ARIMA-ANN hybrid method and empirical mode decomposition. CoRR (2018)
Cynthia Rudin, Seyda Ertekin
Learning customized and optimized lists of rules with mathematical programming. Math. Program. Comput. 10 (4) (2018)
Ümit Cavus Büyüksahin, Seyda Ertekin
Time series forecasting using empirical mode decomposition and hybrid method. SIU (2018)
Yusuf Arslan, Aybike Simsek Dilbaz, Seyda Ertekin, Pinar Karagoz, Aysenur Birturk, Sinan Eren, Dilek Küçük
Short-Term Electricity Consumption Forecast Using Datasets of Various Granularities. DARE@PKDD/ECML (2018)
Memduh Cagri Demir, Seyda Ertekin
Identifying textual personal information using bidirectional LSTM networks. SIU (2018)
Ramin Moghaddass, Seyda Ertekin
Joint optimization of ordering and maintenance with condition monitoring data. Ann. Oper. Res. 263 (1-2) (2018)
Salva Daneshgadeh, Nazife Baykal, Seyda Ertekin
DDoS Attack Modeling and Detection Using SMO. ICMLA (2017)
Egemen Sert, Seyda Ertekin, Ugur Halici
Ensemble of convolutional neural networks for classification of breast microcalcification from mammograms. EMBC (2017)
Seyda Ertekin, Cynthia Rudin
A Bayesian Approach to Learning Scoring Systems. Big Data 3 (4) (2015)
Seyda Ertekin, Cynthia Rudin, Haym Hirsh
Approximating the crowd. Data Min. Knowl. Discov. 28 (5-6) (2014)
Cynthia Rudin, Seyda Ertekin, Rebecca J. Passonneau, Axinia Radeva, Ashish Tomar, Boyi Xie, Stanley Lewis, Mark Riddle, Debbie Pangsrivinij, Tyler H. McCormick
Analytics for Power Grid Distribution Reliability in New York City. Interfaces 44 (4) (2014)
Seyda Ertekin
Adaptive Oversampling for Imbalanced Data Classification. ISCIS (2013)
Seyda Ertekin, Cynthia Rudin, Tyler H. McCormick
Predicting Power Failures with Reactive Point Processes. AAAI (Late-Breaking Developments) (2013)
Seyda Ertekin, Haym Hirsh, Cynthia Rudin
Learning to Predict the Wisdom of Crowds CoRR (2012)
Seyda Ertekin, Haym Hirsh, Cynthia Rudin
Selective Sampling of Labelers for Approximating the Crowd. AAAI Fall Symposium: Machine Aggregation of Human Judgment (2012)
Seyda Ertekin, Cynthia Rudin
On Equivalence Relationships Between Classification and Ranking Algorithms. J. Mach. Learn. Res. 12 (2011)
Seyda Ertekin, Léon Bottou, C. Lee Giles
Nonconvex Online Support Vector Machines. IEEE Trans. Pattern Anal. Mach. Intell. 33 (2) (2011)
Levent Bolelli, Seyda Ertekin, C. Lee Giles
Topic and Trend Detection in Text Collections Using Latent Dirichlet Allocation. ECIR (2009)
Levent Bolelli, Seyda Ertekin, Ding Zhou, C. Lee Giles
Finding topic trends in digital libraries. JCDL (2009)
Jian Huang, Seyda Ertekin, Yang Song, Hongyuan Zha, C. Lee Giles
Efficient Multiclass Boosting Classification with Active Learning. SDM (2007)
Levent Bolelli, Seyda Ertekin, Ding Zhou, C. Lee Giles
A clustering method for web data with multi-type interrelated components. WWW (2007)
Seyda Ertekin, Jian Huang, Léon Bottou, C. Lee Giles
Learning on the border: active learning in imbalanced data classification. CIKM (2007)
Levent Bolelli, Seyda Ertekin, Ding Zhou, C. Lee Giles
K-SVMeans: A Hybrid Clustering Algorithm for Multi-Type Interrelated Datasets. Web Intelligence (2007)
Seyda Ertekin, Jian Huang, C. Lee Giles
Active learning for class imbalance problem. SIGIR (2007)
Jian Huang, Seyda Ertekin, C. Lee Giles
Efficient Name Disambiguation for Large-Scale Databases. PKDD (2006)
Levent Bolelli, Seyda Ertekin, C. Lee Giles
Clustering Scientific Literature Using Sparse Citation Graph Analysis. PKDD (2006)
Antoine Bordes, Seyda Ertekin, Jason Weston, Léon Bottou
Fast Kernel Classifiers with Online and Active Learning. J. Mach. Learn. Res. 6 (2005)