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2020 – today
- 2024
[i34]Sean Berry, Berk Görgülü, Sait Tunç, Mucahit Cevik, Matthew J. Ellis:
Optimizing Hard-to-Place Kidney Allocation: A Machine Learning Approach to Center Ranking. CoRR abs/2410.09116 (2024)- 2023
- [j26]Sanaz Mohammadjafari, Mucahit Cevik
, Ayse Basar:
VARGAN: variance enforcing network enhanced GAN. Appl. Intell. 53(1): 69-95 (2023) - [j25]Sanaz Mohammad Jafari, Mucahit Cevik, Ayse Basar:
Improved α-GAN architecture for generating 3D connected volumes with an application to radiosurgery treatment planning. Appl. Intell. 53(18): 21050-21076 (2023) - [j24]Robert K. Helmeczi, Can Kavaklioglu, Mucahit Cevik:
Linear programming-based solution methods for constrained partially observable Markov decision processes. Appl. Intell. 53(19): 21743-21769 (2023) - [j23]Merve Bodur, Mucahit Cevik, André A. Ciré, Mark Ruschin, Juyoung Wang:
Multistage stochastic fractionated intensity modulated radiation therapy planning. Comput. Oper. Res. 160: 106371 (2023) - [j22]Oylum Seker, Mucahit Cevik, Merve Bodur, Young Lee, Mark Ruschin:
A Multiobjective Approach for Sector Duration Optimization in Stereotactic Radiosurgery Treatment Planning. INFORMS J. Comput. 35(1): 248-264 (2023) - [j21]Mucahit Cevik, Sanaz Mohammad Jafari, Mitchell Myers, Savas Yildirim:
Sequence Labeling for Disambiguating Medical Abbreviations. J. Heal. Informatics Res. 7(4): 501-526 (2023) - [j20]Robert K. Helmeczi, Can Kavaklioglu, Mucahit Cevik, Davood Pirayesh Neghab:
A multi-objective constrained partially observable Markov decision process model for breast cancer screening. Oper. Res. 23(2): 30 (2023) - [j19]Hadi Jahanshahi, Mucahit Cevik, Kianoush Mousavi, Ayse Basar:
ADPTriage: Approximate Dynamic Programming for Bug Triage. IEEE Trans. Software Eng. 49(10): 4594-4609 (2023) - [c27]Robert K. Helmeczi, Savas Yildirim, Mucahit Cevik, Sojin Lee:
Few shot learning approaches to essay scoring. Canadian AI 2023 - [c26]Garima Malik, Savas Yildirim, Mucahit Cevik, Ayse Bener:
An Empirical Study on Vagueness Detection in Privacy Policy Texts. Canadian AI 2023 - [c25]Davood Pirayesh Neghab, Mucahit Cevik, Ayse Basar:
Identifying the Factors Influencing IPO Underpricing using Explainable Machine Learning Techniques. Canadian AI 2023 - [c24]Sanaz Mohammad Jafari, Savas Yildirim, Mucahit Cevik, Ayse Basar:
Anaphoric Ambiguity Resolution in Software Requirement Texts. IEEE Big Data 2023: 4722-4730 - [c23]Garima Malik, Mucahit Cevik, Ayse Basar:
Data Augmentation for Conflict and Duplicate Detection in Software Engineering Sentence Pairs. CASCON 2023: 34-43 - [c22]Savas Yildirim, Mucahit Cevik, Ayse Basar:
Few-shot Learning Approaches to Software Requirement Quality Prediction. CASCON 2023: 155-160 - [i33]Savas Yildirim, Mucahit Cevik, Devang Parikh, Ayse Basar:
Adaptive Fine-tuning for Multiclass Classification over Software Requirement Data. CoRR abs/2301.00495 (2023) - [i32]Syed Kazmi, Berk Görgülü, Mucahit Cevik, Mustafa Gökçe Baydogan:
A Concurrent CNN-RNN Approach for Multi-Step Wind Power Forecasting. CoRR abs/2301.00819 (2023) - [i31]Ozan Ozyegen, Juyoung Wang, Mucahit Cevik:
DANLIP: Deep Autoregressive Networks for Locally Interpretable Probabilistic Forecasting. CoRR abs/2301.02332 (2023) - [i30]Garima Malik, Savas Yildirim, Mucahit Cevik, Ayse Bener, Devang Parikh:
Transfer learning for conflict and duplicate detection in software requirement pairs. CoRR abs/2301.03709 (2023) - [i29]Davood Pirayesh Neghab, Mucahit Cevik, M. I. M. Wahab:
Explaining Exchange Rate Forecasts with Macroeconomic Fundamentals Using Interpretive Machine Learning. CoRR abs/2303.16149 (2023) - [i28]Garima Malik, Mucahit Cevik, Ayse Basar:
Data Augmentation for Conflict and Duplicate Detection in Software Engineering Sentence Pairs. CoRR abs/2305.09608 (2023) - [i27]Robert Kraig Helmeczi, Mucahit Cevik, Savas Yildirim:
Few-shot learning for sentence pair classification and its applications in software engineering. CoRR abs/2306.08058 (2023) - [i26]Mucahit Cevik, Can Kavaklioglu, Fahad Razak, Amol A. Verma, Ayse Basar:
Assessing the impact of emergency department short stay units using length-of-stay prediction and discrete event simulation. CoRR abs/2308.02730 (2023) - [i25]Arash Dehghan, Mucahit Cevik, Merve Bodur:
Neural Approximate Dynamic Programming for the Ultra-fast Order Dispatching Problem. CoRR abs/2311.12975 (2023) - [i24]Arash Dehghan, Mucahit Cevik, Merve Bodur:
Dynamic AGV Task Allocation in Intelligent Warehouses. CoRR abs/2312.16026 (2023) - 2022
- [j18]Eray Mert Kavuk, Ayse Tosun, Mucahit Cevik, Aysun Bozanta, Sibel B. Sonuc, Mehmetcan Tutuncu, Bilgin Kosucu, Ayse Basar:
Order dispatching for an ultra-fast delivery service via deep reinforcement learning. Appl. Intell. 52(4): 4274-4299 (2022) - [j17]Ozan Ozyegen, Igor Ilic, Mucahit Cevik:
Evaluation of interpretability methods for multivariate time series forecasting. Appl. Intell. 52(5): 4727-4743 (2022) - [j16]Ozan Ozyegen, Devika Kabe, Mucahit Cevik:
Word-level text highlighting of medical texts for telehealth services. Artif. Intell. Medicine 127: 102284 (2022) - [j15]Aysun Bozanta, Mucahit Cevik, Can Kavaklioglu, Eray Mert Kavuk, Ayse Tosun, Sibel B. Sonuc, Alper Duranel, Ayse Basar:
Courier routing and assignment for food delivery service using reinforcement learning. Comput. Ind. Eng. 164: 107871 (2022) - [j14]Can Kavaklioglu, Mucahit Cevik:
Scalable grid-based approximation algorithms for partially observable Markov decision processes. Concurr. Comput. Pract. Exp. 34(5) (2022) - [j13]Parisa Lak, Aysun Bozanta, Can Kavaklioglu, Mucahit Cevik, Ayse Basar, Martin Petitclerc, Graham J. Wills:
A replication study on implicit feedback recommender systems with application to the data visualization recommendation. Expert Syst. J. Knowl. Eng. 39(4) (2022) - [j12]Juyoung Wang, Mucahit Cevik, Merve Bodur:
On the impact of deep learning-based time-series forecasts on multistage stochastic programming policies. INFOR Inf. Syst. Oper. Res. 60(2): 133-164 (2022) - [j11]Hadi Jahanshahi, Mucahit Cevik:
S-DABT: Schedule and Dependency-aware Bug Triage in open-source bug tracking systems. Inf. Softw. Technol. 151: 107025 (2022) - [j10]Mucahit Cevik, Sabrina Angco, Elham Heydarigharaei, Hadi Jahanshahi, Nicholas Prayogo:
Active Learning for Multi-way Sensitivity Analysis with Application to Disease Screening Modeling. J. Heal. Informatics Res. 6(3): 317-343 (2022) - [j9]Hadi Jahanshahi, Syed Kazmi, Mucahit Cevik:
Auto Response Generation in Online Medical Chat Services. J. Heal. Informatics Res. 6(3): 344-374 (2022) - [j8]Hadi Jahanshahi, Mucahit Cevik, José Navas-Sú, Ayse Basar, Antonio González Torres:
Wayback Machine: A tool to capture the evolutionary behavior of the bug reports and their triage process in open-source software systems. J. Syst. Softw. 189: 111308 (2022) - [j7]Hadi Jahanshahi, Aysun Bozanta, Mucahit Cevik, Eray Mert Kavuk, Ayse Tosun, Sibel B. Sonuc, Bilgin Kosucu, Ayse Basar:
A deep reinforcement learning approach for the meal delivery problem. Knowl. Based Syst. 243: 108489 (2022) - [j6]Ozan Ozyegen, Sanaz Mohammadjafari, Mucahit Cevik, Karim El Mokhtari, Jonathan Ethier, Ayse Basar:
An Empirical Study on Using CNNs for Fast Radio Signal Prediction. SN Comput. Sci. 3(2): 131 (2022) - [c21]Garima Malik, Mucahit Cevik, Swayami Bera, Savas Yildirim, Devang Parikh, Ayse Basar:
Software requirement specific entity extraction using transformer models. Canadian AI 2022 - [c20]Syed Rafayal, Mucahit Cevik, Derya Kici:
An empirical study on probabilistic forecasting for predicting city-wide electricity consumption. Canadian AI 2022 - [c19]Syed Mahbub Rafayal, Mucahit Cevik:
Time series forecasting-based peak shaving for building energy management. CASCON 2022: 52-61 - [c18]Nicholas Prayogo, Davood Pirayesh Neghab, Syed Mahbub Rafayal, Mucahit Cevik:
Partially Observable Markov Chain Models for Evaluating Lung Cancer Screening Policies. CASCON 2022: 81-90 - [c17]Robert K. Helmeczi, Mucahit Cevik, Savas Yildirim:
A Prompt-based Few-shot Learning Approach to Software Conflict Detection. CASCON 2022: 101-109 - [i23]Hadi Jahanshahi, Mucahit Cevik:
S-DABT: Schedule and Dependency-Aware Bug Triage in Open-Source Bug Tracking Systems. CoRR abs/2204.05972 (2022) - [i22]Aysun Bozanta, Sean Berry, Mucahit Cevik, Beste Bulut, Deniz Yigit, Fahrettin F. Gonen, Ayse Basar:
Time Series Clustering for Grouping Products Based on Price and Sales Patterns. CoRR abs/2204.08334 (2022) - [i21]Can Kavaklioglu, Mucahit Cevik, Robert Helmeczi, Davood Pirayesh Neghab:
A multi-objective constrained POMDP model for breast cancer screening. CoRR abs/2206.05370 (2022) - [i20]Garima Malik, Mucahit Cevik, Devang Parikh, Ayse Basar:
Identifying the requirement conflicts in SRS documents using transformer-based sentence embeddings. CoRR abs/2206.13690 (2022) - [i19]Can Kavaklioglu, Robert Helmeczi, Mucahit Cevik:
Linear programming-based solution methods for constrained POMDPs. CoRR abs/2206.14081 (2022) - [i18]Sanaz Mohammadjafari, Mucahit Cevik, Ayse Basar:
Improved α-GAN architecture for generating 3D connected volumes with an application to radiosurgery treatment planning. CoRR abs/2207.11223 (2022) - [i17]Ozan Ozyegen, Nicholas Prayogo, Mucahit Cevik, Ayse Basar:
Interpretable Time Series Clustering Using Local Explanations. CoRR abs/2208.01152 (2022) - [i16]Mucahit Cevik, Sanaz Mohammad Jafari, Mitchell Myers, Savas Yildirim:
Token Classification for Disambiguating Medical Abbreviations. CoRR abs/2210.02487 (2022) - [i15]Hadi Jahanshahi, Mucahit Cevik, Kianoush Mousavi, Ayse Basar:
ADPTriage: Approximate Dynamic Programming for Bug Triage. CoRR abs/2211.00872 (2022) - [i14]Robert K. Helmeczi, Mucahit Cevik, Savas Yildirim:
A Prompt-based Few-shot Learning Approach to Software Conflict Detection. CoRR abs/2211.02709 (2022) - 2021
- [j5]Sanaz Mohammadjafari, Ozan Ozyegen, Mucahit Cevik, Emir Kavurmacioglu, Jonathan Ethier, Ayse Basar:
Designing mm-wave electromagnetic engineered surfaces using generative adversarial networks. Neural Comput. Appl. 33(17): 11309-11323 (2021) - [j4]Igor Ilic, Berk Görgülü, Mucahit Cevik, Mustafa Gökçe Baydogan:
Explainable boosted linear regression for time series forecasting. Pattern Recognit. 120: 108144 (2021) - [c16]Derya Kici, Garima Malik, Mucahit Cevik, Devang Parikh, Ayse Basar:
A BERT-based transfer learning approach to text classification on software requirements specifications. Canadian AI 2021 - [c15]Garima Malik, Mucahit Cevik, Yusef Khedr, Devang Parikh, Ayse Basar:
Named Entity Recognition on Software Requirements Specification Documents. Canadian AI 2021 - [c14]Sanaz Mohammadjafari, Mucahit Cevik, Mathusan Thanabalasingam, Ayse Basar, Alzheimer's Disease Neuroimaging Initiative:
Using ProtoPNet for Interpretable Alzheimer's Disease Classification. Canadian AI 2021 - [c13]Hadi Jahanshahi, Ozan Ozyegen, Mucahit Cevik, Beste Bulut, Deniz Yigit, Fahrettin F. Gonen, Ayse Basar:
Text classification for predicting multi-level product categories. CASCON 2021: 33-42 - [c12]Syed Kazmi, Aysun Bozanta, Mucahit Cevik:
Time series forecasting for patient arrivals in online health services. CASCON 2021: 43-52 - [c11]Derya Kici, Aysun Bozanta, Mucahit Cevik, Devang Parikh, Ayse Basar:
Text classification on software requirements specifications using transformer models. CASCON 2021: 163-172 - [c10]Mucahit Cevik, Savas Yildirim, Ayse Basar:
Natural language processing for software requirement specifications. CASCON 2021: 308-309 - [c9]Hadi Jahanshahi, Kritika Chhabra, Mucahit Cevik, Ayse Basar:
DABT: A Dependency-aware Bug Triaging Method. EASE 2021: 221-230 - [c8]Aysun Bozanta, Sabrina Angco, Mucahit Cevik, Ayse Basar:
Sentiment Analysis of StockTwits Using Transformer Models. ICMLA 2021: 1253-1258 - [i13]Hadi Jahanshahi, Mucahit Cevik, Ayse Basar:
Moving from Cross-Project Defect Prediction to Heterogeneous Defect Prediction: A Partial Replication Study. CoRR abs/2103.03490 (2021) - [i12]Hadi Jahanshahi, Dhanya Jothimani, Ayse Basar, Mucahit Cevik:
Does chronology matter in JIT defect prediction? A Partial Replication Study. CoRR abs/2103.03506 (2021) - [i11]Hadi Jahanshahi, Aysun Bozanta, Mucahit Cevik, Eray Mert Kavuk, Ayse Tosun, Sibel B. Sonuc, Bilgin Kosucu, Ayse Basar:
A Deep Reinforcement Learning Approach for the Meal Delivery Problem. CoRR abs/2104.12000 (2021) - [i10]Hadi Jahanshahi, Mucahit Cevik, Ayse Basar:
Predicting the Number of Reported Bugs in a Software Repository. CoRR abs/2104.12001 (2021) - [i9]Hadi Jahanshahi, Kritika Chhabra, Mucahit Cevik, Ayse Basar:
DABT: A Dependency-aware Bug Triaging Method. CoRR abs/2104.12744 (2021) - [i8]Hadi Jahanshahi, Syed Kazmi, Mucahit Cevik:
Auto Response Generation in Online Medical Chat Services. CoRR abs/2104.12755 (2021) - [i7]Ozan Ozyegen, Devika Kabe, Mucahit Cevik:
Word-level Text Highlighting of Medical Texts forTelehealth Services. CoRR abs/2105.10400 (2021) - [i6]Hadi Jahanshahi, Ozan Ozyegen, Mucahit Cevik, Beste Bulut, Deniz Yigit, Fahrettin F. Gonen, Ayse Basar:
Text Classification for Predicting Multi-level Product Categories. CoRR abs/2109.01084 (2021) - [i5]Sanaz Mohammadjafari, Mucahit Cevik, Ayse Basar:
VARGAN: Variance Enforcing Network Enhanced GAN. CoRR abs/2109.02117 (2021) - 2020
- [j3]Ashok Bhowmick, Mucahit Cevik, Ayse Basar:
Analyzing Intracranial EEG in Pharmacoresistant Epilepsy Patients Using Hidden Markov Models and Time Series Forecasting Methods. SN Comput. Sci. 1(6): 325 (2020) - [j2]Sanaz Mohammadjafari, Sophie Roginsky, Emir Kavurmacioglu, Mucahit Cevik, Jonathan Ethier, Ayse Basar Bener:
Machine Learning-Based Radio Coverage Prediction in Urban Environments. IEEE Trans. Netw. Serv. Manag. 17(4): 2117-2130 (2020) - [c7]Karim El Mokhtari, Mucahit Cevik, Ayse Basar:
Using Topic Modelling to Improve Prediction of Financial Report Commentary Classes. Canadian AI 2020: 201-207 - [c6]Igor Ilic, Berk Görgülü, Mucahit Cevik:
Augmented Out-of-Sample Comparison Method for Time Series Forecasting Techniques. Canadian AI 2020: 302-308 - [c5]Hadi Jahanshahi, Mucahit Cevik, Ayse Basar:
Predicting the Number of Reported Bugs in a Software Repository. Canadian AI 2020: 309-320 - [c4]Hadi Jahanshahi, Mucahit Cevik, Ayse Basar:
Moving from cross-project defect prediction to heterogeneous defect prediction: a partial replication study. CASCON 2020: 133-142 - [c3]Nicholas Prayogo, Mucahit Cevik, Merve Bodur:
Time series sampling for probabilistic forecasting. CASCON 2020: 153-162 - [c2]Jingli Wang, Ashok Bhowmick, Mucahit Cevik, Ayse Basar:
Deep learning approaches to classify the relevance and sentiment of news articles to the economy. CASCON 2020: 207-216 - [i4]Ozan Ozyegen, Sanaz Mohammadjafari, Karim El Mokhtari, Mucahit Cevik, Jonathan Ethier, Ayse Basar:
Deep learning approaches for fast radio signal prediction. CoRR abs/2006.09245 (2020) - [i3]Ozan Ozyegen, Igor Ilic, Mucahit Cevik:
Evaluation of Local Explanation Methods for Multivariate Time Series Forecasting. CoRR abs/2009.09092 (2020) - [i2]Igor Ilic, Berk Görgülü, Mucahit Cevik, Mustafa Gökçe Baydogan:
Explainable boosted linear regression for time series forecasting. CoRR abs/2009.09110 (2020) - [i1]Hadi Jahanshahi, Mucahit Cevik, José Navas-Sú, Ayse Basar, Antonio González Torres:
Wayback Machine: Capturing the evolutionary behaviour of the bug dependency graph in open-source software systems. CoRR abs/2011.05382 (2020)
2010 – 2019
- 2019
- [c1]Hadi Jahanshahi, Dhanya Jothimani, Ayse Basar, Mucahit Cevik:
Does chronology matter in JIT defect prediction?: A Partial Replication Study. PROMISE 2019: 90-99 - 2013
- [j1]Z. Caner Taskin, Mucahit Cevik:
Combinatorial Benders cuts for decomposing IMRT fluence maps using rectangular apertures. Comput. Oper. Res. 40(9): 2178-2186 (2013)
Coauthor Index
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last updated on 2024-11-25 22:47 CET by the dblp team
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