Publications

Machine Learning | Operations Research | Technical Reports

Machine Learning

Submitted

  1. S. Mu and D. Klabjan. On the Convergence Rate of LoRA Gradient Descent. (submitted for publication) 2026 [.pdf]
  2. Z. Su, I. Banerjee and D. Klabjan. Central Limit Theorems for Transition Probabilities of Controlled Markov Chains. (submitted for publication) 2026 [.pdf]
  3. Y. Hong and D. Klabjan. Statistical Arbitrage in Options Markets by Graph Learning and Synthetic Long Positions. (submitted for publication) 2025 [.pdf]
  4. R. Wang and D. Klabjan. A Trainable Optimizer. (submitted for publication) 2025 [.pdf]
  5. A. Sandler, D. Klabjan, and Y. Luo. Non-Convex Optimization with Spectral Radius Regularization. (submitted for publication) 2025 [.pdf]
  6. H. Wu and D. Klabjan, LanFL: Differentially Private Federated Learning with Large Language Models using Synthetic Samples. (submitted for publication) 2025. [.pdf]
  7. T. Overman and D. Klabjan, Continuous-Time Analysis of Federated Averaging. (submitted for publication) 2025. [.pdf]
  8. H. Park and D. Klabjan, Communication-Efficient Federated Low-Rank Update Algorithm and its Connection to Implicit Regularization. (submitted for publication) 2025. [.pdf]
  9. M. Xu and D. Klabjan. Regret Bounds and Reinforcement Learning Exploration of EXP-based Algorithms. (submitted for publication) 2024. [.pdf]
  10. X. Qian and D. Klabjan. The Impact of the Mini-batch Size on the Variance of Gradients in Stochastic Gradient Descent. (submitted for publication) 2024. [.pdf]
  11. R. Wang and D. Klabjan. Divergence Results and Convergence of a Variance Reduced version of ADAM. (submitted for publication) 2022. [.pdf] [appendix.pdf]

Peer-Reviewed Journal Publications

  1. Y. Ma, D. Klabjan and J. Utke. Video to Video Generative Adversarial Network for Few-shot Learning Based on Policy Gradient. To appear in IEEE Transactions on Neural Networks and Learning Systems. 2025 [.pdf]
  2. J. Yang, D. Klabjan, H. Liu, N.S. Patel, X. Li, B. Ananthanarayanan, H. Dauod, T.H. Juang. Scalable Multi-agent Reinforcement Learning for Factory-wide Dynamic Scheduling. To appear in Engineering Applications of Artificial Intelligence. 2025. [.pdf]
  3. J. Jang, D. Klabjan, H. Liu, N.S. Patel, X. Li, B. Ananthanarayanan, H. Dauod, T-H Juang. Learning Multiple Coordinated Agents under Directed Acyclic Graph Constraints. To appear in Expert Systems with Applications. 2025. [.pdf] [Appendix.pdf]
  4. A. Cao, D. Klabjan, and Y. Luo. Open-Set Recognition of Breast Cancer Treatments. To appear in Artificial Intelligence in Medicine. 2022. [.pdf]
  5. Y. Ma and D. Klabjan, Diminishing Batch Normalization. To appear in IEEE Transactions on Neural Networks and Learning Systems, 2022. [.pdf] [appendix.pdf]
  6. Q. Gao, Z. Luo and D. Klabjan, Efficient Architecture Search for Continual Learning. To appear in IEEE Transactions on Neural Networks and Learning Systems, 2022. [.pdf]
  7. P. Wongchaisuwat and D. Klabjan. Truth Validation with Evidence. To appear in Knowledge and Information Systems, 2022. [.pdf]
  8. J. Koo, D. Klabjan and J. Utke. Inverse Classification with Limited Budget and Maximum Number of Perturbed Samples. To appear in Expert Systems With Applications,
    2020 [.pdf]
  9. Y.W. Park and D. Klabjan. Subset Selection for Multiple Linear Regression via Optimization (submitted for publication). To appear in Journal of Global Optimization, 2020. [.pdf] [data.zip][appendix.pdf]
  10. C. Kim, Y. Kim and D. Klabjan. Scale Invariant Power Iteration. To appear in Journal of Machine Learning Research. 2019. [.pdf]
  11. J. Yang and D. Klabjan. Bayesian Active Learning for Choice Models with Deep Gaussian Processes. To appear in Transactions on Intelligent Transportation Systems, 2019 [.pdf]
  12. C. Kim and D. Klabjan, A Simple and Fast Algorithm for L1-norm Kernel PCA. To appear in Transactions on Pattern Analysis and Machine Intelligence, 2019 [.pdf]
  13. Y. Yang, S. Shebalov and D. Klabjan. Semi-supervised Learning for Discrete Choice Models. To appear in Transactions on Intelligent Transportation Systems, 2018 [.pdf]
  14. Y. Zeng and D. Klabjan. Online Adaptive Machine Learning Based Algorithm for Implied Volatility Surface Modeling. To appear in Knowledge-Based Systems, 2018. [.pdf]
  15. Y. Xue, Y. Luo and D. Klabjan. Predicting ICU readmission using grouped physiological and medication trends. To appear in Artificial Intelligence in Medicine, 2018. [.pdf]
  16. D. Klabjan, M. Di, L. Sha and P. Lucey. Large-scale Adversarial Sports Play Retrieval with Learning to Rank. To appear in ACM Transactions on Knowledge Discovery from Data, 2017. [.pdf]
  17. Y.W. Park and D. Klabjan. Bayesian Network Learning via Topological Order. To appear in Journal of Machine Learning Research, 2017. [.pdf]
  18. Richards CT, Wang B, Markul E, Albarran F, Rottman D, Aggarwal NT, Lindeman P, Stein-Spencer L, Weber JM, Pearlman KS, Tataris KL, Holl JL, Klabjan D, Prabhakaran S. Identifying Key Words in 9-1-1 Calls for Stroke: A Mixed Methods Approach. To appear in Prehospital Emergency Care, 2017. [.pdf]
  19. C. Borraz-Sanchez, J. Ma, D. Klabjan, E. Pasalic, and M. Aref. Algebraic modeling in Datalog. In Declarative Logic Programming: Theory, Systems, and Applications. Editors: Michael Kifer and Yanhong A. Liu. Publisher: Association for Computing Machinery and Morgan & Claypool. 2017. [.pdf]
  20. Y.W. Park and D. Klabjan. Three Iteratively Reweighted Least Squares Algorithms for L1-Norm Principal Component Analysis. To appear in Knowledge and Information Systems, 2017. [.pdf] [Extended journal version of ICDM 2016 proceedings paper.]
  21. M. Dixon, D. Klabjan, and J.H. Bang. Classication-based Financial Markets Prediction using Deep Neural Networks. To appear in Journal of Algorithmic Finance 2016. [.pdf]
  22. P. Wongchaisuwat, D. Klabjan, and S. Jonnalagadda. A Semi-supervised Learning Approach to Enhance Health Care Community-based Question Answering: A case Study in Alcoholism. To appear in JMIR Medical Informatics 2016. [.pdf]
  23. Y.W. Park and D. Klabjan. An Aggregate and Iterative Disaggregate Algorithm with Proven Optimality in Machine Learning. To appear in Machine Learning, 2016 [.pdf]
  24. Y.W. Park, Y. Jiang, D. Klabjan, L. Williams. Algorithms for Generalized Cluster-wise Linear Regression. To appear in INFORMS Journal on Computing. 2016. [.pdf] [data.zip]
  25. A. Drachen, J. Riley, S. Baskin, D. Klabjan. Going Out of Business: Auction House Behavior in the Massively Multi-Player Online Game Glitch. To appear in Entertainment Computing, 2014. [pdf‘]
  26. A. Lavin, D. Klabjan. Clustering Time-Series Energy Data from Smart Meters. To appear in Energy Efficiency. 2013. [.pdf]
  27. H. Gonzalez, J. Han, H. Cheng, X. Li, and D. Klabjan. Modeling Massive RFID Datasets: A Gateway-Based Movement-Graph Approach. IEEE Transactions on Knowledge and Data Engineering, vol 22, p 90-104. 2010. [.pdf]
  28. H. Gonzalez, J. Han, X. Li, and D. Klabjan. Warehousing and Analyzing Massive RFID Data Sets. Lecture Notes in Computer Science, vol 4093, p 1-18. 2006. [.pdf]

Peer-Reviewed Proceedings

  1. H. Li, M. Fedeli, V. Kolar and D. Klabjan. BEAR: BGP Event Analysis and Reporting. 35th International Conference on Computer Communications and Networks, Honolulu, HI 2026. [.pdf]
  2. J. A. Nguyen and D. Klabjan. FedGA-Tree: Federated Decision Tree using Genetic Algorithm. The Genetic and Evolutionary Computation Conference (GECCO), San Jose, Costa Rica 2026. [.pdf]
  3. M. Xu and D. Klabjan. Decentralized Blockchain-based Robust Multi-agent Multi-armed Bandit. AISTATS, Tangler, Marocco 2026. [.pdf]
  4. Y. Zou, D. Klabjan, J. Utke, and H. Liu. PromptFE: Automated Feature Engineering by Prompting. 19th Conference of the European Chapter of the Association for Computational Linguistics (EACL), Rabat, Marocco, 2026. [.pdf]
  5. B. Fang, J. Utke, T. Vo and D. Klabjan. Tricks and Plugins to GBM on Images and Sequences. IEEE International Conference on Big Data, Macau, China 2025. [.pdf]
  6. Z. Zhang, D. Klabjan, and R. Manworren. DiffMVR: Diffusion-based Automated Multi-Guidance Video Restoration. IEEE International Conference on Big Data, Macau, China 2025. [.pdf]
  7. Z. Zhang and D. Klabjan. Unit Testing for Random Forest Models. IEEE International Conference on Big Data, Macau, China 2025. [.pdf]
  8. Y. Hong and D. Klabjan. Graph Learning for Foreign Exchange Rate Prediction and Statistical Arbitrage. ACM International Conference on AI in Finance. Singapore, 2025. [.pdf]
  9. Y. Zou, H. Liu, D. Klabjan. Investigating Hallucinations in Time Series Foundation Models through Signal Subspace Analysis. NeurIPS. San Diego, CA, 2025. [.pdf]
  10. S. Mu and D. Klabjan, Rewind-to-Delete: Certified Machine Unlearning for Nonconvex Functions. NeurIPS. San Diego, CA, 2025. [.pdf]
  11. T. Joo and D. Klabjan, Technical Debt in In-Context Learning: Diminishing Efficiency in Long Context. NeurIPS. San Diego, CA, 2025. [.pdf]
  12. S. Wang, S. Moazeni, and D. Klabjan, A Sequential Optimal Learning Approach to Automated Prompt Engineering in Large Language Models. EMNLP, Suzhou, 2025. [.pdf]
  13. H. Li , Kiran S. Jyothi , H. Hu , Y. Chen, H. Liang, S. Mahadevan and D. Klabjan. Zero-shot Graph Reasoning via Retrieval Augmented Framework with LLMs. EMNLP, Suzhou, 2025. [.pdf]
  14. H. Li and D. Klabjan, Reverse Prompt Engineering. EMNLP, Suzhou, 2025. [.pdf]
  15. A. Trevino Gavito, D. Klabjan, and S. Shah. Unsupervised Echocardiogram View Detection via Autoencoder-based Representation Learning.  International Conference on Deep Learning and Machine Learning in Ultrasound Imaging, Amsterdam, The Netherlands, 2025. [.pdf]
  16. S. Wang and D. Klabjan. A Mirror Descent Perspective of Smoothed Sign Descent. Uncertainty in AI, Rio de Janeiro, Brazil. 2025. [.pdf]
  17. A.V. Nguyen, D. Klabjan, M. Ryu, K. Kim, and Z. Di, Federated Low-Rank Tensor Estimation for Multimodal Image Reconstruction. International Joint Conference on Neural Networks, Roma, Italy. 2025. [.pdf]
  18. A. Sandler, D. Klabjan and Y. Luo. Conditional Hierarchical Bayesian Tucker Decomposition for Genetic Data Analysis. IEEE Conference on Artificial Intelligence, Santa Clara, CA. 2025. [.pdf]
  19. M. Xu and D.Klabjan. Regret Lower Bounds in Multi-agent Multi-armed Bandit. AISTATS. Thailand, 2025. [.pdf]
  20. Z. Su and D. Klabjan. Differentiable Calibration of Inexact Stochastic Simulation Models via Kernel Score Minimization. AISTATS. Thailand, 2025. [.pdf]
  21. T. Joo and D. Klabjan. Improving Self-training under Distribution Shifts via Anchored Confidence with Theoretical Guarantees. NeurIPS. Vancouver, BC, Canada. 2024. [.pdf]
  22. B. Fang, T. Vo and D. Klabjan. A Stochastic Large-scale Machine Learning Algorithm for Distributed Features and Observations. IEEE International Conference on Big Data. Washington DC, 2024. [.pdf]
  23. C. Kim, Y, Kim, D. Klabjan, and Y. Jambunath. Stochastic Scale Invariant Power Iteration for Kullback-Leibler Divergence Nonnegative Matrix Factorization. IEEE International Conference on Big Data. Washington DC, 2024. [.pdf]
  24. Y. Xue, D. Klabjan and J. Utke. Multimodal Learning on Temporal Data. IEEE International Conference on Big Data. Washington DC, 2024. [.pdf]
  25. H. Li, D.Klabjan, and J.Utke. Unsupervised Video Summarization. 17th Asian Conference on Computer Vision. Hanoi, Vietnam, 2024. [.pdf]
  26. Y. Xue, D. Klabjan and J.Utke. S-Omninet: Structured Data Enhanced Universal Multimodal Learning Architecture. International Conference on Machine Learning and Applications. Coral Gabels, 2024. [.pdf]
  27. A. Trevino, J. Utke and D. Klabjan. Multi-Layer Attention-Based Explainability via Transformers for Tabular Data. International Conference on Machine Learning and Applications. Coral Gabels, 2024. [.pdf]
  28. T. Overman, D. Klabjan, and J. Utke. IIFE: Interaction Information Based Automated Feature Engineering. International Conference on Data Mining. Abu Dhabi. 2024. [.pdf]
  29. H. Wu and D. Klabjan. Robust Softmax Aggregation on Blockchain based Federated Learning with Convergence Guarantee. IEEE Coins. London, UK. 2024. [.pdf]
  30. S. Mu and D. Klabjan. On the Second-Order Convergence of Biased Policy Gradient Algorithms.  ICML, Vienna, Austria 2024. [.pdf]
  31. T. Joo and D. Klabjan. IW-GAE: Importance Weighted Group Accuracy Estimation for Improved Calibration and Model Selection in Unsupervised Domain Adaptation. ICML, Vienna, Austria 2024. [.pdf]
  32. S. Wang and D. Klabjan. An Ensemble Method of Deep Reinforcement Learning for Automated Cryptocurrency Trading. IEEE International Conference on Blockchain and Cryptocurrency, Dublin, Ireland 2024. [.pdf]
  33. T. Overman, G. Blum and D. Klabjan. A Primal-Dual Algorithm for Hybrid Federated Learning. AAAI, Vancouver, Canada 2024. [.pdf]
  34. G. Blum, R. Doris, D. Klabjan, H. Espinosa and R. Szalkowski. Use of Deep Neural Networks for Uncertain Stress Functions with Extensions to Impact Mechanics. To appear in IEEE's 9th International Conference on Big Data Analytics, Tokyo, Japan 2023. [.pdf]
  35. Y. Ma and D. Klabjan. Semi-supervised 3D Video Information Retrieval with Deep Neural Network and Bi-directional Dynamic-time Warping Algorithm. IEEE International Conference on Big Data, Sorrento, Italy 2023. [.pdf]
  36. S. Lim, D. Klabjan and M. Shapiro. Feature Acquisition Using Monte Carlo Tree Search. IEEE International Conference on Big Data, Sorrento, Italy 2023. [.pdf]
  37. S. Ger, Y. Jambunath and D. Klabjan. Autoencoders and Generative Adversarial Networks for Anomaly Detection for Sequences IEEE International Conference on Big Data, Sorrento, Italy 2023. [.pdf]
  38. S. Ger, Y. Jambunath, D. Klabjan, J. Utke. Cohesive Attention-Based Explanations for Sequences and Explainability in Presence of Event Types. IEEE International Conference on Big Data, Sorrento, Italy 2023. [.pdf]
  39. M. Xu and D.Klabjan. Decentralized Randomly Distributed Multi-agent Multi-armed Bandit with Heterogeneous Rewards. NeurIPS. New Orleans 2023. [.pdf]
  40. A. Cao, J. Utke and D. Klabjan. Early Classifying Multimodal Sequences. 25th ACM International Conference on Multimodal Interaction. Paris, France 2023. [.pdf]
  41. A. Cao, J. Utke and D. Klabjan. A Policy for Early Sequence Classification. 32nd International Conference on Artificial Neural Networks. Crete, Greece 2023. [.pdf]
  42. A. Trevino-Gavito, D. Klabjan, and J.Utke. Gradient-boosted Based Structured and Unstructured Learning. 32nd International Conference on Artificial Neural Networks. Crete, Greece 2023. [.pdf]
  43. M. Xu and D. Klabjan. Pareto Regret Analyses in Multi-objective Multi-armed Bandit. International Conference on Machine Learning, Honolulu, HI 2023. [.pdf]
  44. G. Ebrahimi and D. Klabjan. Neuron-based pruning of deep neural networks with better generalization using Kronecker factored curvature approximation. International Joint Conference on Neural Networks, Queensland, Australia 2023. [.pdf]
  45. X. Qian, M. Kennedy and D. Klabjan. Dynamic Cell Structure via Recursive-Recurrent Neural Networks. IEEE International Conference on Big Data, Osaka, Japan. Virtual due to Covid-19 2022. [.pdf]
  46. Y. Xu and D. Klabjan. Open Set Domain Adaptation by Extreme Value Theory. IEEE International Conference on Big Data, Osaka, Japan. Virtual due to Covid-19 2022. [.pdf]
  47. Y. Xue, D. Klabjan, and Y. Luo. Aggregation Delayed Federated Learning. IEEE International Conference on Big Data, Osaka, Japan Virtual due to Covid-19 2022. [.pdf]
  48. C. Ke, H. Deng, C. Xu, J. Li, X. Gu, B. Yadamsuren, D. Klabjan, R. Sifa, A. Drachen and S. Demediuk. DOTA 2 match prediction through deep learning team fight models. IEEE Conference on Games, Beijing, China, Virtual due to Covid-19 2022. [.pdf]
  49. A. Ebrahimi, A. Stec, D. Klabjan, and J. Utke. Nested Multi-Instance Image Classification. International Conference on Pattern Recognition. Montreal 2022. [.pdf]
  50. D. Klabjan and X. Zhu. Neural Network Retraining for Model Serving. IEEE International Conference on Big Data,  Virtual due to Covid-19 2021. [.pdf]
  51. H. Wu and D. Klabjan, Logit-based Uncertainty Measure in Classification. IEEE International Conference on Big Data,  Virtual due to Covid-19 2021. [.pdf]
  52. X. Wang, L. Zhang and D. Klabjan. Keyword-based Topic Modeling and Keyword Selection. IEEE International Conference on Big Data,  Virtual due to Covid-19 2021. [.pdf]
  53. Y. Xu and D. Klabjan. Concept Drift and Covariate Shift Detection Ensemble with Lagged Labels. IEEE International Conference on Big Data,  Virtual due to Covid-19 2021. [.pdf]
  54. S. Ger, D. Klabjan, and J. Utke. Classification Models for Partially Ordered Sequences. International Conference on Artificial Neural Networks, Virtual due to Covid-19 2021. [.pdf]
  55. N. Byanna, G. Ebrahimi and D. Klabjan. Evaluating the Performance of Offensive Linemen in the NFL. ICMLDMSA: 15. International Conference on Machine Learning and Data Mining for Sports Analytics, Virtual due to Covid-19 2021. [.pdf]
  56. G. Ebrahimi, C. Ge, D. Klabjan, D. Ladner, and P. Stride. Cirrhosis Mortality Prediction as Classification. 15th International Conference on Health Information Systems and Clinical Decision, Virtual due to Covid-19 2021. [.pdf]
  57. X. Qian and D. Klabjan. A Probabilistic Approach to Neural Network Pruning. International Conference on Machine Learning, Virtual due to Covid-19 2021. [.pdf]
  58. Y. Xu and D. Klabjan. k-Nearest Neighbors by Means of Sequence to Sequence Deep Neural Networks and Memory Networks. International Joint Conferences on Artificial Intelligence (IJCAI), Virtual due to Covid-19 2021. [.pdf]
  59. G. Ebrahimi, B. Wang and D. Klabjan. Generative Adversarial Nets for Multiple Text Corpora. International Joint Conference on Neural Network (IJCNN), Virtual due to Covid-19  2021. [.pdf]
  60. G. Ebrahimi, L. Zhang and D. Klabjan. Layer Flexible Adaptive Computational Time for Recurrent Neural Networks. International Joint Conference on Neural Network (IJCNN), Virtual due to Covid-19  2021. [.pdf]
  61. M. Harmon, A. Ebrahimi, D. Klabjan, and P. Lucey. Predicting Shot Making in Basketball using Convolutional Neural Networks Learnt from Adversarial Multiagent Trajectories. International Conference on Computer Science in Sport and Exercise, Istanbul, Turkey 2021 [.pdf]
  62. A. Cao, Y. Luo and D. Klabjan. Open-Set Recognition with Gaussian Mixture Variational Autoencoders. AAAI, Virtual due to Covid-19  2020. [.pdf]
  63. M. Harmon and D. Klabjan. Dynamic Prediction Length for Time Series with Sequence to Sequence Network. ACM International Conference on AI in Finance, New York, NY  2020. [.pdf]
  64. J. Koo and D. Klabjan. Improved classification based on Deep Belief Networks (submitted for publication. 29th International Conference on Artificial Neural Networks (ICANN), Bratislava, Slovakia 2020. [.pdf]
  65. Y. Xu, D. Rajpathak, I. Gibbs, D. Klabjan. Automatic Ontology Learning from Domain-Specific Short Unstructured Text Data. 12th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (KMIS), Budapest, Hungary 2020. [.pdf]
  66. C. Kim and D. Klabjan. Stochastic Variance-Reduced Algorithms for PCA with Arbitrary Mini-Batch Sizes. AISTATS, Palermo, Italy 2020. [.pdf]
  67. R. Sifa, M. Fedell, N. Franklin, D. Klabjan, S. Ram, A. Venugopal, S. Demediuk, and A. Drachen (2020). Retention Prediction in Sandbox Games with Bipartite Tensor Factorization. Computing Conference, London, UK 2020. [.pdf]
  68. X. Zhu and D. Klabjan. Listwise Learning to Rank by Exploring Unique Ratings. The 13th ACM International Conference on Web Search and Data Mining (WSDM), Houston, TX 2020. [.pdf]
  69. J. Koo, D. Klabjan, and J. Utke. Combined Convolutional and Recurrent Neural Networks for Hierarchical Classification of Images. IEEE International Conference on Big Data, Virtual due to Covid-19 2019. [.pdf]
  70. M. Harmon and D. Klabjan. Activation Ensembles for Deep Neural Networks. IEEE International Conference on Big Data, Los Angeles, CA 2019. [.pdf]
  71. Y. Xue, D. Klabjan, and Y. Luo. Mixture-based Multiple Imputation Models for Clinical Data with a Temporal Dimension. IEEE International Conference on Big Data, Los Angeles, CA 2019. [.pdf]
  72. S. Demediuk, R. Joshi, Z. Wang, V. Gupta, X. Li, Y. Cui, D. Klabjan, A. Parsaeian, A. Drachen. A Team Based Player Versus Player Recommender Systems Framework for Player Improvement. Australasian Computer Science Week, Sydney, Australia 2019. Best paper award [.pdf]
  73. X. Teng, A. Zufle, G. Trajcevski, and  D. Klabjan. Location-Awareness in Time Series Compression. 22nd European Conference on Advances in Databases and Information Systems, Budapest, Hungary 2018. [.pdf]
  74. E. M. Rantanen, L. Hochberg, D. Ming, D., and D. Klabjan. Decluttering Geographic Data View Displays. Proceedings of the Human Factors and Ergonomics Society 2018 Annual Meeting, Philadelphia, PA. [.pdf]
  75. X. Wang and D. Klabjan. Competitive Multi-agent Inverse Reinforcement Learning with Sub-optimal Demonstrations. ICML, Stockholm, Sweden 2018. [.pdf]
  76. A. Drachen, E. Pawlakos, K. Zhai, S. Haran, R. Jha, R. Sifa, and D. Klabjan, Controlling the Crucible: A Novel PvP Recommender Systems Framework for Destiny. Australasian Computer Science Week, Brisbane, Australia 2018. [.pdf]
  77. A. Drachen, J. Runge, R. Sifa, M. Pastor, A. Liu, D. J. Fontaine, Y. Chang, and D. Klabjan (2018), To Be or Not to Be Social: Incorporating Simple Social Features in Mobile Game Customer Lifetime Value Predictions. Australasian Computer Science Week, Brisbane, Australia. [.pdf]
  78. C. Qin, D. Russo, and D. Klabjan (2017), Improving the Expected Improvement Algorithm. NIPS, Long Beach, CA. [.pdf]
  79. X. Zhu, D. Klabjan, and P. Bless (2017).  Semantic Document Distance Measures and Unsupervised Document Revision Detection. International Joint Conference on Natural Language Processing, Taipei, Taiwan. [.pdf]
  80. P. Wognchaisuwat, D. Klabjan, and J. McGinnis (2017). Predicting Litigation Likelihood and Time to Litigate for Patents The 16th International Conference on Artificial Intelligence and Law, London, UK [.pdf]
  81. B. Wang and D. Klabjan (2017). Regularization for Unsupervised Deep Neural Nets. AAIA, San Francisco, CA. [.pdf]
  82. A. Drachen, E. Lundquist, Y. Kung, P. Rao, D. Klabjan, R. Sifa, and J. Runge (2016). Rapid Prediction of Player Retention in Free-to-Play Mobile Games. The Twelfth Annual AAAI Conference of Artificial Intelligence and Interactive Digital Entertainment, San Francisco, CA. [.pdf]
  83. A. Drachen, J. Green, C. Gray, E. Harik, P. Lu, R. Sifa, and D. Klabjan (2016). Guns and Guardians: Comparative Cluster Analysis and Behavioral Profiling in Destiny. IEEE Computational Intelligence and Games Conference, Santorini, Greece. [.pdf]
  84. B. Wang and D. Klabjan. Time-Dependent Topic Analysis with Endogenous and Exogenous Processes. AAAI Phoenix, AX 2015. [.pdf]
  85. M. Dixon, D. Klabjan, and J.H. Bang. Implementing Deep Neural Networks for Financial Market Prediction on the Intel Xeon Phi. Supercomputing, Austin, TX 2015. [.pdf]
  86. A. Drachen, D. Klabjan, M. Yancey, D. Chu, J. Maguire, Y. Wang. Skill-Based Differences in Spatio-Temporal Team Behavior in Defense of the Ancients 2. 6th IEEE Consumer Electronics Society Games, Entertainment, Media Conference, Toronto, 2014. [.pdf]
  87. E. Ko, D. Klabjan.  Semantic Properties of Customer Sentiment in Tweets. The 28th IEEE International Conference on Advanced Information Networking and Applications. Victoria, Canada, 2014. [.pdf]

Reports

  1. X. Liu and D.Klabjan. Unsupervised Player Tracking in Sport Videos. 2024. [.pdf]
  2. N. Wang, H. Liu, and D. Klabjan. Large-Scale Multi-Document Summarization with Information Extraction and Compression. 2022. [.pdf]
  3. X. Liu, D. Klabjan and P. Bless. Data and Trend Extraction from Time Series Graphs. 2022 [.pdf]
  4. B. Fang, K. Rajshekhar, T. Vo and D. Klabjan. Topic Analysis for Text with Side Data. 2021 [.pdf]
  5. B. Fang and D. Klabjan. Convergence Analyses of Online ADAM Algorithm in Convex Setting and Two-Layer ReLU Neural Network. 2019. [.pdf]
  6. X. Liu, D. Klabjan, and P. Bless. Data Extraction from Charts via Single Deep Neural Network 2019. [.pdf]
  7. A. Stec, D. Klabjan, and J. Utke. Unified Recurrent Neural Network for Many Feature Types 2018. [.pdf]
  8. A. Stec and D. Klabjan. Forecasting Crime with Deep Learning. 2017. [.pdf]
  9. B. Wang and D. Klabjan. An Attention-Based Deep Net for Learning to Rank. 2017. [.pdf]
  10. T. Jeong, D. Klabjan, and J. Starren. Predictive Analytics Using Smartphone Sensors for Depressive Episodes. HIAI 2016, Expanding the Boundaries of Health Informatics using AI, Phoenix, AZ [.pdf]

Operations Research

Transportation

  1. C. Borraz-Sanchez, D. Klabjan, and A. Uygur. An Approach for the Railway Multi-terrritory Dispatching Problem.To appear in Transportation Science 2019. [.pdf]
  2. F. Schneider, U. Thonemann, and D. Klabjan. Optimization of Battery Charging and Purchasing at Electric Vehicle Battery Swap Stations. To appear in Transportation Science 2017. [.pdf]
  3. D. Zhang and D. Klabjan. Optimization for Gate Re-assignment. To appear in Transportation Research Part B. 2016. [.pdf]
  4. C. Pun, D. Klabjan, F. Karaesmen, S. Shebalov. Itinerary-Based Nesting Control with Upsell. To appear in Journal of Revenue and Pricing Management. 2015. [.pdf]
  5. D. Wang, S. Shebalov, D. Klabjan. Attractiveness-Based Airline Network Models with Embedded Spill and Recapture. Journal of Airline and Airport Management. Vol. 4, No. 1, p1-25. 2013. [.pdf]
  6. A. Wald, M. Harmon and D. Klabjan. Structural Deplaning via Simulation and Optimization. To appear in Journal of Air Transport Management (2013). [.pdf]
  7. A. Seth, D. Klabjan, and P. Ferreira. Analyses of Advanced Iterated Tour Partitioning Heuristics for Generalized Vehicle Routing Problems. To appear in Networks. 2012. [.pdf]
  8. J. Ahn, O. de Weck, Y. Gang, and D. Klabjan. Generalized Location Routing Problem with Profits. European Journal of Operational Research, vol 223, p47-59. 2012. [.pdf]
  9. M. Sohoni, Y-C. Lee, and D. Klabjan. Block Time Estimation and Robust Airline Scheduling. Transportation Science, vol. 45, p451-464. 2010. [.pdf]
  10. S. Choo, D. Klabjan, and D. Simchi-Levi. Multi-ship Crane Sequencing with Yard Congestion Constraints. Transportation Science, vol. 44, p98-115. 2010. [.pdf]
  11. L. Schenk and D. Klabjan. Intra market Optimization for Express Package Carriers with Station to Station Travel and Proportional Sorting. Computers and Operations Research, vol. 37, p1749-1761. 2010. [.pdf]
  12. L. Schenk and D. Klabjan. Intra market Optimization for Express Package Carriers. Transportation Science, vol. 42, p 530-545. 2008. [.pdf]
  13. R. Sandhu and D. Klabjan. Fleeting with Passenger and Cargo Origin-Destination Booking Control. Transportation Science, vol 40, p 517-528. 2006. [.pdf]
  14. R. Sandhu and D. Klabjan. Integrated Airline Fleeting and Crew Pairing Decisions. Operations Research, vol. 55, p 439-456. 2006. [.pdf]
  15. S. Shebalov and D. Klabjan. Robust Airline Crew Pairing: Move-up Crews. Transportation Science, vol. 40, p 300-312. 2006 [.pdf]
  16. A. Makri and D. Klabjan. A New Pricing Scheme for Airline Crew Scheduling. INFORMS Journal on Computing, vol. 16, p 56-67. 2004. [.pdf]
  17. D. Klabjan, E.L. Johnson, G.L. Nemhauser, E. Gelman, and S. Ramaswamy. Airline Crew Scheduling with Time Windows and Plane Count Constraints. Transportation Science, vol 36, p 337-348. 2002. [.pdf] [extended version .pdf]
  18. D. Klabjan, E.L. Johnson, G.L. Nemhauser, E. Gelman, and S. Ramaswamy. Airline Crew Scheduling with Regularity. Transportation Science, vol 35, p 359-374. 2001. [.pdf]
  19. D. Klabjan, E.L. Johnson, G.L. Nemhauser, E. Gelman, and S. Ramaswamy. Solving Large Airline Crew Scheduling Problems: Random Pairing Generation and Strong Branching. Computational Optimization and Applications, vol 20, p 73-91. 2000. [.pdf]

Integer Programming

  1. S. Shebalov, Y. W. Park, and D. Klabjan (2015), Lifting for Mixed Integer Programs with Variable Upper Bounds. Discrete Applied Mathematics (2015) Volume 186, pp226-250. [.pdf] [appendix.pdf]
  2. Y.W. Park, D. Klabjan. Lot Sizing with Minimum Order Quantity. To Appear in Discrete Applied Mathematics. 2013. [.pdf]
  3. Y. Zhao and D. Klabjan. A Polyhedral Study of Lot-sizing with Supplier Selection. Discrete Optimization, vol. 9, p 65-76. 2012. [.pdf]
  4. A. Seth, D. Klabjan, and P. Ferreira. A Novel Local Search Integer-Programming-Based Heuristic for PCB Assembly on Collect-and-Place machines.To appeared in Mathematical Programming Computation. 2009. [.pdf]
  5. C. Almeder, D. Klabjan, and B. Almada-Lobo. Lead Time Considerations for the Multi-Level Capacitated Lot-sizing Problem.To appear in European Journal of Operational Research. 2009. [.pdf]
  6. B. Almada-Lobo, D. Klabjan, M.A. Carravilla, and J.F. Oliveira. Multiple Machine Multi-Item Continuous Setup Lotsizing with Sequence-dependent Setups. Computational Optimization and Applications, vol. 47, p 529-552. 2007. [.pdf]
  7. B. Almada-Lobo, D. Klabjan, M.A. Carravilla, and J.F. Oliveira. Single Machine Multi-product Capacitated Lotsizing with Sequence-dependent Setups, International Journal of Production Research, vol 45, p 4873-4894. 2007. [.pdf]
  8. D. Klabjan. Subadditive Approaches in Integer Programming. European Journal of Operational Research, vol. 183, p 525-545. 2007. [.pdf] [extended version .pdf]
  9. Y. Zhao and D. Klabjan. Sequence Independent Lifting for Mixed Integer Programs with Variable Upper Bonds. Mathematical Programming, vol. 105, p 523-561. 2006. [.pdf]
  10. D. Klabjan. Practical Algorithm for Computing the Subadditive Dual Function for Set Partitioning. Computational Optimization and Applications, vol 29, p 347-368. 2004 [.pdf]
  11. D. Klabjan and G.L. Nemhauser. A Polyhedral Study of Integer Variable Upper Bonds. Mathematics of Operations Research, vol 27, p 711-739. 2002. [.pdf]

Supply Chain Management

  1. N. Craig, N. DeHoratius and D. Klabjan, Execution Quality and Chargeback Penalties in Retail Supply Chains. To appear in Journal of Operations Management. 2020. [.pdf]
  2. C. Kim, D. Klabjan, and D. Simchi-Levi. Optimal Expediting Policies for an Invetory System with Stochastic Lead Time under Radio Frequency Identification. To appear in Production and Operations Management. 2015 [.pdf]
  3. C. Kim, D. Klabjan, and D. Simchi-Levi. Optimal Expediting Policies for an Inventory System with Expiry. To appear in Production and Operations Management. 2015. [.pdf]
  4. N. Craig, J. Yan, N. DiHoratius and D. Klabjan (2015). An Analysis of Fulfillment Errors in a Retail Distribution Center. To appear in Journal of Operations Management [.pdf]
  5. F. Schneider, and D. Klabjan. Inventory Control in Multi-channel Retail. European Journal of Operational Research, vol. 227, p 101-111. 2013. [.pdf]
  6. M. Song, D. Klabjan, and D. Simchi-Levi. Robust Stochastic Lot-Sizing by Means of Histograms. Production and Operations Management, vol. 22, p 691-710. 2013. [.pdf]
  7. D. Klabjan and J. Pei. In-store One-to-One Marketing. Journal of Retailing and Consumer Services, vol 18, p 64-73. 2011. [.pdf]
  8. J. Pei and D. Klabjan. Inventory Control in Serial Systems under Radio Frequency Identification. International Journal of Production in Economics, vol 123, p 118-136. 2010 [.pdf]
  9. S. Chang, D. Klabjan, and T. Vossen. Optimal Radio Frequency Identification Deployment in a Supply Chain Network. International Journal of Production Economics, vol. 125, p 71-83. 2010. [.pdf]
  10. D. Adelman and D. Klabjan. Computing Near Optimal Policies in Generalized Joint Replenishment. INFORMS Journal on Computing, vol 24, p 148-164. 2010. [.pdf]
  11. N. Halman, D. Klabjan, M. Mostagir, J. Orlin, D. Simchi-Levi, A Fully Polynomial Time Approximation Scheme for Single-Item Stochastic Inventory Control Problems with Discrete Demand. Mathematics of Operations Research 34 (2009) 674-685 [.pdf]
  12. D. Klabjan and D. Adelman, A Convergent Infinite Dimensional Linear Programming Algorithm for Deterministic Semi-Markov Decision Processes on Borel Spaces. Mathematics of Operations Research, vol 32, p 528-550. 2007. [.pdf]
  13. D. Klabjan and D. Adelman. Existence of Optimal Policies for Semi-Markov Decision Processes Using Duality for Infinite Linear Programming. SIAM Journal on Control and Optimization, vol 44, p 2104-2122. 2006 [.pdf]
  14. D. Adelman and D. Klabjan. Duality and Existence of Optimal Policies in Generalized Joint Replenishment. Mathematics of Operations Research, vol. 30, p 28-50. 2005. [.pdf]

Miscellaneous

  1. Y. Zeng and D. Klabjan. Portfolio Optimization of American Options. To appear in Journal of Computational Finance. 2019. [.pdf]
  2. J. Mays and D. Klabjan. Optimization of Time-Varying Electricity Rates. To appear in The Energy Journal. 2016. [.pdf]
  3. T. Sweda, I. Dolinskaya, D. Klabjan. Optimal Recharging Policies for Electric Vehicles. To appear in Transportation Science. 2016. [.pdf]
  4. T. Sweda, I. Dolinskaya, D. Klabjan. Adaptive Routing and Recharging Policies for Electric Vehicles. To appear in Transportation Science. 2016. [.pdf]
  5. Y. Zeng, D. Klabjan, J. Arinez. Distributed Solar Renewable Generation: Option Contracts with Renewable Energy Credit Uncertainty. Energy Economics. 2014. [.pdf]
  6. T. Sweda and D. Klabjan, An Agent-Based Information System for Electric Vehicle Charging Infrastructure Deployment, To appear in ASCE Journal of Infrastructure Systems 2014. [.pdf]
  7. N. Halman, D. Klabjan, C-L. Li, J. Orlin and D. Simchi-Levi (2014), Fully Polynomial Time Approximation Schemes for Convex and Monotone Stochastic Dynamic Programming. To appear in SIAM Journal on Discrete Mathematics. [.pdf]
  8. L. Guimaraes, D. Klabjan, B. Almada-Lobo. Modeling Lotsizing and Scheduling Problems with Sequence Dependent Setups. To appear in European Journal of Operational Research. 2013. [.pdf]
  9. L. Guimaraes, D. Klabjan, B. Almada-Lobo. Pricing, Relaxing, and Fixing under Lotsizing and Scheduling. European Journal of Operational Research, vol 230. p 399-411. 2013. [.pdf]
  10. D. Klabjan and C. Borraz. Optimal Placement of Reconfigurable Optical Add/Drop Multiplexers with Packing, Blocking, and Signal Loss. Computer Networks, vol. 57, p 1443-1458. 2013. [.pdf]
  11. D. Klabjan, W. Olszewski, A.Wolinsky. Attributes. To appear in Games and Economic Behavior. 2012. [.pdf]
  12. P. Pei, D. Klabjan. Approximations to Auctions for Digital Goods with Externality. To appear in Electronic Commerce Research and Applications. 2012. [.pdf]
  13. L. Guimaraes, D. Klabjan, B. Almada-Lobo. Annual Production Budget in the Beverage Industry. International Scientific Journal Engineering Applications of Artificial Intelligence, vol. 25, p 229-241. 2012. [.pdf]
  14. P. Bless, D. Klabjan, and S. Chang. Automated Knowledge Source Selection and Service Composition. Computational Optimization and Applications, vol. 52, p 507-535. 2011. [.pdf]
  15. P. Bless, D. Klabjan, and S. Chang. Heuristics for Automated Knowledge Source Selection and Service Composition. Computers and Operations Research, vol. 35, p 1292-1314. 2008. [.pdf]
  16. P.N. Bless, S.G. Kapoor, R.E. DeVor, and D. Klabjan. An Algorithmic Strategy for Automated Development of Multi-component Software Tools for Virtual manufacturing. Journal of Manufacturing Science and Engineering, vol. 127, p 866-874. 2005. [.pdf]
  17. A. Makri and D. Klabjan. Algorithms for Source-to-all Maximum Cost to Time Ratio Problem in Acyclic networks. Networks, vol 42, p 1-14. 2003. [.pdf]
  18. A. Arora and D. Klabjan. A Model for Budget Allocation in Multi-unit libraries. Library Collections, Acquisitions, and Technical Services, vol. 26, p 423-438. 2002. [.pdf]
  19. D. Klabjan, E.L. Johnson, and G.L. Nemhauser. A Parallel Primal-Dual Simplex Algorithm. Operations Research Letters, vol. 27, p 47-55. 2000. [.pdf]
  20. D. Klabjan and B. Mohar. The Number of Matchings of Low Order in Hexagonal Systems. Discrete Mathematics, vol 186, p 167-175. 1998. [.pdf]
  21. D. Klabjan, C. Tovey, and G.L. Nemhauser. Cover Inequality Separation is NP-hard. Operations Research Letters, vol. 23, p 35-40. 1998. [.pdf]

Peer-Reviewed Proceedings

  1. O. Worley and D. Klabjan (2012), "Simultaneous Vehicle Routing and Charging Station Siting for Commercial Electric Vehicles", IEEE International Electric Vehicle Conference, Greenville, NC. [.pdf]
  2. T. Sweda and D. Klabjan (2012), "Finding Minimum-Cost Paths for Electric Vehicles", IEEE International Electric Vehicle Conference, Greenville, NC. [.pdf]
  3. T. Sweda and D. Klabjan (2011), "An Agent-Based Decision Support System for Electric Vehicle Charging Infrastructure Deployment," 7th IEEE Vehicle Power and Propulsion Conference, Chicago, Illinois. [.pdf]
  4. S. Ruangpattana, D. Klabjan, J. Arinez, and S. Biller (2011), "Optimization of On-site Renewable Energy Generation for Industrial Sites," Proceedings of IEEE Power Systems 2011, Phoenix, AZ. [.pdf]
  5. C. Cheng, C. Chekuri, and D. Klabjan (2009), "Topology Formation for Wireless Mesh Network Planning," Proceedings of IEEE Infocom 2009 Mini-conference, Rio de Janeiro, Brazil. [.pdf]
  6. J. Han, H. Gonzalez, X. Li, and Diego Klabjan (2006), "Warehousing and Mining Massive RFID Data Sets," Proceedings of the International Conference on Advanced Data Mining and Applications, Xi'An, China. [.pdf]
  7. H. Gonzales, J. Han, X. Li, and D. Klabjan (2006), "Warehousing and Analyzing Massive RFID Data Sets,"  Proceedings of the 22nd International Conference on Data Engineering, Atlanta, GA. [.pdf]
  8. D. Klabjan (2002), "A New Subadditive Approach to Integer Programming: Theory and Algorithms," Proceedings of the 9th Integer Programming and Combinatorial Optimization Conference, 384-400. [.pdf]
  9. D. Klabjan and K. Schwan (2001), "Airline Crew Pairing Generation in Parallel," Proceedings of the 10th SIAM Conference on Parallel Processing for Scientific Computing [.pdf]

Technical Reports

  1. M. F. Dixon, D. Klabjan and L Wei. OSTSC: Over Sampling for Time Series Classification in R. 2017. [.pdf]
  2. M. Di, D. Klabjan, and S. Shebalov. Solving Attractiveness-based Stochastic Fleeting by MapReduce 2016. [.pdf]
  3. M. Di, D. Klabjan, and E. Rantanen. Power Grid Visualization by Means of Optimization. 2016 [.pdf]
  4. J. Yang, D. Klabjan, and J. Schoenbeck. The Economics of Same-day Delivery by Means of a Variable Neighborhood-based Heuristic. 2016. [.pdf]
  5. L. Guimaraes, D. Klabjan and B. Almada-Lobo. Rolling Horizon Formulations for Short-to-Medium Term Production Planning. 2015. [.pdf]
  6. Y. Geng, D. Klabjan. Freight Consolidation on a Single Lane. 2014. [.pdf]
  7. F. Schneider, D. Klabjan, U. Thonemann. Optimal Incorporating Demand Response with Load Shifting into Stochastic Unit Commitment. 2013. [.pdf]
  8. C. Lindsey, A. Frei, H. S. Mahmassani, H. Alibabai, Y.W. Park, D. Klabjan, M. Reed, G. Langheim, T. Keating. Online Pricing and Capacity Sourcing for Third Party Logistics Providers. 2013. [.pdf]
  9. C.S. Pun, D. Klabjan. Air Cargo Allotment Planning. 2013. [.pdf]
  10. C. Lindsey, A. Frei, H. Alibabai, H. S. Mahmassani, Y.W. Park, D. Klabjan, M. Reed, G. Langheim, T. Keating. Modeling Carrier Truckload Freight Rates in Spot Markets. 2013. [.pdf]
  11. Y. Geng, D. Klabjan. Approximate Dynamic Programming Based Approaches for Green Supply Chain Design. 2013. [.pdf]
  12. J. Pei, D. Klabjan, F. Karaesmen. Pricing of Digital Goods vs. Physical Goods. 2013. [.pdf]
  13. Y. Jiang, D. Klabjan. Optimal Emissions Reduction Investment under Green House gas Emissions Regulations. 2012. [.pdf]
  14. P. Pei, D. Klabjan, F. Karaesmen. Auctions under Shareability and Externality. 2012 [.pdf]
  15. A. Seth, D. Klabjan, and P. Ferreira. Assembly Optimization for High-Volume High-Flexibility Robotic PCB Assembly. 2009. [.pdf]
  16. O. de Weck, D. Klabjan, C. Taylor, D. Simchi-Levi, J. Ahn, E. Gralla, and S. Shull. Interplanetary Supply Chain Management and Logistics at NASA. 2008. [.pdf]
  17. L. Li, C.S. Pun, and D. Klabjan. Single Item Lot-Sizing Problem with Minimum Order Quantity. 2008. [.pdf]
  18. D. Klabjan. Algorithms for Lot-sizing with Supplier Selection. 2008 [.pdf]
  19. D. Klabjan, Economic Order Quantity for Business-to-Consumer Fulfillment. 2007. [.pdf]
  20. C. Kim, D. Klabjan, and D. Simchi-Levi. Optimal Policy for Expediting Orders in Transit. 2006. [.pdf]
  21. Y. Jiang, and D. Klabjan. Business-to-Consumer Single Period Fulfillment Strategies. 2005. [.pdf]
  22. M. Bundschuh, D. Klabjan, P. Pei, and D. Thurston. Modeling Robust and Reliable Supply Chains. 2003. [.pdf]