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Diego Klabjan
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- affiliation: Northwestern University, Illinois, USA
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2020 – today
- 2024
- [j68]Yintai Ma
, Diego Klabjan
Diminishing Batch Normalization. IEEE Trans. Neural Networks Learn. Syst. 35(5): 6544-6557 (2024) - [c66]Tom Overman, Garrett Blum, Diego Klabjan:
A Primal-Dual Algorithm for Hybrid Federated Learning. AAAI 2024: 14482-14489 - [c65]Huiyu Wu, Diego Klabjan:
Robust Softmax Aggregation on Blockchain based Federated Learning with Convergence Guarantee. COINS 2024: 1-4 - [c64]Shuyang Wang, Diego Klabjan:
An Ensemble Method of Deep Reinforcement Learning for Automated Cryptocurrency Trading. ICBC 2024: 461-463 - [c63]Taejong Joo, Diego Klabjan:
IW-GAE: Importance weighted group accuracy estimation for improved calibration and model selection in unsupervised domain adaptation. ICML 2024 - [c62]Siqiao Mu, Diego Klabjan:
On the Second-Order Convergence of Biased Policy Gradient Algorithms. ICML 2024 - [i92]Mengfan Xu, Diego Klabjan:
Decentralized Blockchain-based Robust Multi-agent Multi-armed Bandit. CoRR abs/2402.04417 (2024) - [i91]Jaeyeon Jang, Diego Klabjan, Veena Mendiratta, Fanfei Meng:
Hybrid FedGraph: An efficient hybrid federated learning algorithm using graph convolutional neural network. CoRR abs/2404.09443 (2024) - [i90]Tom Overman, Diego Klabjan, Jean Utke:
IIFE: Interaction Information Based Automated Feature Engineering. CoRR abs/2409.04665 (2024) - [i89]Siqiao Mu, Diego Klabjan:
Rewind-to-Delete: Certified Machine Unlearning for Nonconvex Functions. CoRR abs/2409.09778 (2024) - [i88]Haemin Park, Diego Klabjan:
Communication-Efficient Federated Low-Rank Update Algorithm and its Connection to Implicit Regularization. CoRR abs/2409.12371 (2024) - [i87]Jaeyeon Jang, Diego Klabjan, Han Liu, Nital S. Patel, Xiuqi Li, Balakrishnan Ananthanarayanan, Husam Dauod, Tzung-Han Juang:
Scalable Multi-agent Reinforcement Learning for Factory-wide Dynamic Scheduling. CoRR abs/2409.13571 (2024) - [i86]Shuyang Wang, Diego Klabjan:
A Mirror Descent Perspective of Smoothed Sign Descent. CoRR abs/2410.14158 (2024) - [i85]Huiyu Wu, Diego Klabjan:
LanFL: Differentially Private Federated Learning with Large Language Models using Synthetic Samples. CoRR abs/2410.19114 (2024) - [i84]Yintai Ma, Diego Klabjan, Jean Utke:
Video to Video Generative Adversarial Network for Few-shot Learning Based on Policy Gradient. CoRR abs/2410.20657 (2024) - [i83]Taejong Joo, Diego Klabjan:
Improving self-training under distribution shifts via anchored confidence with theoretical guarantees. CoRR abs/2411.00586 (2024) - 2023
- [j67]Alexander Cao, Diego Klabjan, Yuan Luo:
Open-set recognition of breast cancer treatments. Artif. Intell. Medicine 135: 102451 (2023) - [j66]Jaehoon Koo
An inverse classification framework with limited budget and maximum number of perturbed samples. Expert Syst. Appl. 212: 118761 (2023) - [j65]Cheolmin Kim, Youngseok Kim, Diego Klabjan:
Scale Invariant Power Iteration. J. Mach. Learn. Res. 24: 321:1-321:47 (2023) - [j64]Qiang Gao
Efficient Architecture Search for Continual Learning. IEEE Trans. Neural Networks Learn. Syst. 34(11): 8555-8565 (2023) - [c61]Yintai Ma, Diego Klabjan:
Semi-supervised 3D Video Information Retrieval with Deep Neural Network and Bi-directional Dynamic-time Warping Algorithm. IEEE Big Data 2023: 758-767 - [c60]Stephanie Ger, Yegna Subramanian Jambunath, Diego Klabjan:
Autoencoders and Generative Adversarial Networks for Imbalanced Sequence Classification. IEEE Big Data 2023: 1101-1108 - [c59]Stephanie Ger, Yegna Subramanian Jambunath, Diego Klabjan, Jean Utke:
Cohesive Attention-Based Explanations for Sequences and Explainability in Presence of Event Types. IEEE Big Data 2023: 1109-1116 - [c58]Sungsoo Lim, Diego Klabjan, Mark Shapiro:
Feature Acquisition Using Monte Carlo Tree Search. IEEE Big Data 2023: 1188-1193 - [c57]Alexander Cao, Jean Utke, Diego Klabjan:
A Policy for Early Sequence Classification. ICANN (1) 2023: 50-61 - [c56]Andrea Treviño Gavito
Gradient-Boosted Based Structured and Unstructured Learning. ICANN (3) 2023: 439-451 - [c55]Alexander Cao
Early Classifying Multimodal Sequences. ICMI 2023: 183-189 - [c54]Mengfan Xu, Diego Klabjan:
Pareto Regret Analyses in Multi-objective Multi-armed Bandit. ICML 2023: 38499-38517 - [c53]Abdolghani Ebrahimi, Diego Klabjan:
Neuron-based Pruning of Deep Neural Networks with Better Generalization using Kronecker Factored Curvature Approximation. IJCNN 2023: 1-9 - [c52]Mengfan Xu, Diego Klabjan:
Decentralized Randomly Distributed Multi-agent Multi-armed Bandit with Heterogeneous Rewards. NeurIPS 2023 - [i82]Andrea Treviño Gavito, Diego Klabjan, Jean Utke:
Multi-Layer Attention-Based Explainability via Transformers for Tabular Data. CoRR abs/2302.14278 (2023) - [i81]Andrea Treviño Gavito, Diego Klabjan, Jean Utke:
Gradient-Boosted Based Structured and Unstructured Learning. CoRR abs/2302.14299 (2023) - [i80]Alexander Cao, Jean Utke, Diego Klabjan:
A Policy for Early Sequence Classification. CoRR abs/2304.03463 (2023) - [i79]Alexander Cao, Jean Utke, Diego Klabjan:
Early Classifying Multimodal Sequences. CoRR abs/2305.01151 (2023) - [i78]Mengfan Xu, Diego Klabjan:
Decentralized Randomly Distributed Multi-agent Multi-armed Bandit with Heterogeneous Rewards. CoRR abs/2306.05579 (2023) - [i77]Ye Xue, Diego Klabjan, Jean Utke:
S-Omninet: Structured Data Enhanced Universal Multimodal Learning Architecture. CoRR abs/2307.00226 (2023) - [i76]Jaeyeon Jang, Diego Klabjan, Han Liu, Nital S. Patel, Xiuqi Li, Balakrishnan Ananthanarayanan
Learning Multiple Coordinated Agents under Directed Acyclic Graph Constraints. CoRR abs/2307.07529 (2023) - [i75]Mengfan Xu, Diego Klabjan:
Regret Lower Bounds in Multi-agent Multi-armed Bandit. CoRR abs/2308.08046 (2023) - [i74]Shuyang Wang, Diego Klabjan:
An Ensemble Method of Deep Reinforcement Learning for Automated Cryptocurrency Trading. CoRR abs/2309.00626 (2023) - [i73]Yintai Ma, Diego Klabjan:
Semi-supervised 3D Video Information Retrieval with Deep Neural Network and Bi-directional Dynamic-time Warping Algorithm. CoRR abs/2309.01063 (2023) - [i72]Taejong Joo, Diego Klabjan:
IW-GAE: Importance weighted group accuracy estimation for improved calibration and model selection in unsupervised domain adaptation. CoRR abs/2310.10611 (2023) - [i71]Siqiao Mu, Diego Klabjan:
Preliminary Analysis on Second-Order Convergence for Biased Policy Gradient Methods. CoRR abs/2311.02546 (2023) - [i70]Hanqing Li, Diego Klabjan, Jean Utke:
Unsupervised Video Summarization. CoRR abs/2311.03745 (2023) - [i69]Huiyu Wu, Diego Klabjan:
Robust softmax aggregation on blockchain based federated learning with convergence guarantee. CoRR abs/2311.07027 (2023) - [i68]Garrett Blum, Ryan Doris, Diego Klabjan, Horacio Espinosa, Ron Szalkowski:
Use of Deep Neural Networks for Uncertain Stress Functions with Extensions to Impact Mechanics. CoRR abs/2311.16135 (2023) - 2022
- [j63]Papis Wongchaisuwat
Truth validation with evidence. Knowl. Inf. Syst. 64(5): 1187-1209 (2022) - [c51]Xin Qian, Rafet Sifa, Xuefei Liu, Shreyashi Ganguly, Borchuluun Yadamsuren, Diego Klabjan, Anders Drachen
Anomaly Detection in Player Performances in Multiplayer Online Battle Arena Games. ACSW 2022: 23-30 - [c50]Ye Xue, Diego Klabjan, Yuan Luo:
Aggregation Delayed Federated Learning. IEEE Big Data 2022: 85-94 - [c49]Xin Qian, Matthew Kennedy, Diego Klabjan:
Dynamic Cell Structure via Recursive-Recurrent Neural Networks. IEEE Big Data 2022: 1336-1349 - [c48]Yiming Xu, Diego Klabjan:
Open Set Domain Adaptation by Extreme Value Theory. IEEE Big Data 2022: 1395-1400 - [c47]Cheng Hao Ke, Haozhang Deng, Congda Xu, Jiong Li, Xingyun Gu, Borchuluun Yadamsuren, Diego Klabjan, Rafet Sifa, Anders Drachen
DOTA 2 match prediction through deep learning team fight models. CoG 2022: 96-103 - [c46]Abdolghani Ebrahimi, Alexander Stec, Diego Klabjan, Jean Utke:
Nested Multi-view Image Classification. ICPR 2022: 5125-5131 - [i67]Alexander Cao, Diego Klabjan, Yuan Luo:
Open-Set Recognition of Breast Cancer Treatments. CoRR abs/2201.02923 (2022) - [i66]Biyi Fang, Jean Utke, Diego Klabjan:
Tricks and Plugins to GBM on Images and Sequences. CoRR abs/2203.00761 (2022) - [i65]Biyi Fang, Kripa Rajshekhar, Diego Klabjan:
Topic Analysis for Text with Side Data. CoRR abs/2203.00762 (2022) - [i64]Ning Wang, Han Liu, Diego Klabjan:
Large-Scale Multi-Document Summarization with Information Extraction and Compression. CoRR abs/2205.00548 (2022) - [i63]Ruiqi Wang, Diego Klabjan:
Divergence Results and Convergence of a Variance Reduced Version of ADAM. CoRR abs/2210.05607 (2022) - [i62]Tom Overman, Garrett Blum, Diego Klabjan:
A Primal-Dual Algorithm for Hybrid Federated Learning. CoRR abs/2210.08106 (2022) - [i61]Mengfan Xu, Diego Klabjan:
Pareto Regret Analyses in Multi-objective Multi-armed Bandit. CoRR abs/2212.00884 (2022) - [i60]Sungsoo Lim, Diego Klabjan, Mark Shapiro:
Feature Acquisition using Monte Carlo Tree Search. CoRR abs/2212.11360 (2022) - 2021
- [j62]Jie Yang
Bayesian Active Learning for Choice Models With Deep Gaussian Processes. IEEE Trans. Intell. Transp. Syst. 22(2): 1080-1092 (2021) - [c45]Alexander Cao, Yuan Luo, Diego Klabjan:
Open-Set Recognition with Gaussian Mixture Variational Autoencoders. AAAI 2021: 6877-6884 - [c44]Rafet Sifa, Anders Drachen
Archetypal Analysis Based Anomaly Detection for Improved Storytelling in Multiplayer Online Battle Arena Games. ACSW 2021: 24:1-24:8 - [c43]Huiyu Wu, Diego Klabjan:
Logit-based Uncertainty Measure in Classification. IEEE BigData 2021: 948-956 - [c42]Xingyu Wang, Lida Zhang, Diego Klabjan:
Keyword-based Topic Modeling and Keyword Selection. IEEE BigData 2021: 1148-1154 - [c41]Xiaofeng Zhu, Diego Klabjan:
Continual Neural Network Model Retraining. IEEE BigData 2021: 1163-1171 - [c40]Yiming Xu, Diego Klabjan:
Concept Drift and Covariate Shift Detection Ensemble with Lagged Labels. IEEE BigData 2021: 1504-1513 - [c39]Stephanie Ger
Classification Models for Partially Ordered Sequences. ICANN (1) 2021: 294-305 - [c38]Xin Qian, Diego Klabjan:
A Probabilistic Approach to Neural Network Pruning. ICML 2021: 8640-8649 - [c37]Yiming Xu, Diego Klabjan:
k-Nearest Neighbors by Means of Sequence to Sequence Deep Neural Networks and Memory Networks. IJCAI 2021: 3214-3220 - [c36]Abdolghani Ebrahimi, Diego Klabjan, Baiyang Wang:
Generative Adversarial Nets for Multiple Text Corpora. IJCNN 2021: 1-8 - [c35]Lida Zhang, Abdolghani Ebrahimi, Diego Klabjan:
Layer Flexible Adaptive Computation Time. IJCNN 2021: 1-9 - [i59]Yiming Xu, Diego Klabjan:
Open Set Domain Adaptation by Extreme Value Theory. CoRR abs/2101.02561 (2021) - [i58]Stephanie Ger, Diego Klabjan, Jean Utke:
Classification Models for Partially Ordered Sequences. CoRR abs/2102.00380 (2021) - [i57]Adam Sandler, Diego Klabjan, Yuan Luo:
Non-Convex Optimization with Spectral Radius Regularization. CoRR abs/2102.11210 (2021) - [i56]Xin Qian, Diego Klabjan:
A Probabilistic Approach to Neural Network Pruning. CoRR abs/2105.10065 (2021) - [i55]Huiyu Wu, Diego Klabjan:
Logit-based Uncertainty Measure in Classification. CoRR abs/2107.02845 (2021) - [i54]Ye Xue, Diego Klabjan, Yuan Luo:
Aggregation Delayed Federated Learning. CoRR abs/2108.07433 (2021) - [i53]Abdolghani Ebrahimi, Diego Klabjan:
Neuron-based Pruning of Deep Neural Networks with Better Generalization using Kronecker Factored Curvature Approximation. CoRR abs/2111.08577 (2021) - 2020
- [j61]Young Woong Park
Subset selection for multiple linear regression via optimization. J. Glob. Optim. 77(3): 543-574 (2020) - [j60]Cheolmin Kim
A Simple and Fast Algorithm for L1-Norm Kernel PCA. IEEE Trans. Pattern Anal. Mach. Intell. 42(8): 1842-1855 (2020) - [j59]Conrado Borraz-Sánchez, Diego Klabjan
An Approach for the Railway Multiterritory Dispatching Problem. Transp. Sci. 54(3): 721-739 (2020) - [c34]Cheolmin Kim, Diego Klabjan:
Stochastic Variance-Reduced Algorithms for PCA with Arbitrary Mini-Batch Sizes. AISTATS 2020: 4302-4312 - [c33]Jaehoon Koo
Combined Convolutional and Recurrent Neural Networks for Hierarchical Classification of Images. IEEE BigData 2020: 1354-1361 - [c32]Yiming Xu, Dnyanesh Rajpathak, Ian Gibbs, Diego Klabjan:
Automatic Ontology Learning from Domain-specific Short Unstructured Text Data. KMIS 2020: 29-39 - [c31]Diego Klabjan, Mark Harmon:
Dynamic prediction length for time series with sequence to sequence network. ICAIF 2020: 4:1-4:9 - [c30]Jaehoon Koo
Improved Classification Based on Deep Belief Networks. ICANN (1) 2020: 541-552 - [c29]Rafet Sifa, Michael Fedell
Retention Prediction in Sandbox Games with Bipartite Tensor Factorization. SAI (1) 2020: 297-308 - [c28]Xiaofeng Zhu, Diego Klabjan:
Listwise Learning to Rank by Exploring Unique Ratings. WSDM 2020: 798-806 - [i52]Xiaofeng Zhu, Diego Klabjan:
Listwise Learning to Rank by Exploring Unique Ratings. CoRR abs/2001.01828 (2020) - [i51]Xingyu Wang, Lida Zhang, Diego Klabjan:
Keyword-based Topic Modeling and Keyword Selection. CoRR abs/2001.07866 (2020) - [i50]Xin Qian, Diego Klabjan:
The Impact of the Mini-batch Size on the Variance of Gradients in Stochastic Gradient Descent. CoRR abs/2004.13146 (2020) - [i49]Diego Klabjan, Xiaofeng Zhu:
Neural Network Retraining for Model Serving. CoRR abs/2004.14203 (2020) - [i48]Alexander Cao, Yuan Luo, Diego Klabjan:
Open-Set Recognition with Gaussian Mixture Variational Autoencoders. CoRR abs/2006.02003 (2020) - [i47]Qiang Gao, Zhipeng Luo, Diego Klabjan:
Efficient Architecture Search for Continual Learning. CoRR abs/2006.04027 (2020) - [i46]Mengfan Xu, Diego Klabjan:
Regret Bounds and Reinforcement Learning Exploration of EXP-based Algorithms. CoRR abs/2009.09538 (2020) - [i45]Jaehoon Koo, Diego Klabjan, Jean Utke:
Inverse Classification with Limited Budget and Maximum Number of Perturbed Samples. CoRR abs/2009.14111 (2020) - [i44]Yiming Xu, Diego Klabjan:
Concept Drift and Covariate Shift Detection Ensemble with Lagged Labels. CoRR abs/2012.04759 (2020)
2010 – 2019
- 2019
- [j58]Ye Xue, Diego Klabjan, Yuan Luo
Predicting ICU readmission using grouped physiological and medication trends. Artif. Intell. Medicine 95: 27-37 (2019) - [j57]Yaxiong Zeng, Diego Klabjan:
Online adaptive machine learning based algorithm for implied volatility surface modeling. Knowl. Based Syst. 163: 376-391 (2019) - [j56]Jie Yang
Semi-Supervised Learning for Discrete Choice Models. IEEE Trans. Intell. Transp. Syst. 20(11): 4145-4159 (2019) - [c27]Rishabh Joshi, Varun Gupta, Xinyue Li, Yue Cui, Ziwen Wang, Yaser Norouzzadeh Ravari, Diego Klabjan, Rafet Sifa, Azita Parsaeian, Anders Drachen
A Team Based Player Versus Player Recommender Systems Framework For Player Improvement. ACSW 2019: 45:1-45:7 - [c26]Diego Klabjan, Mark Harmon:
Activation Ensembles for Deep Neural Networks. IEEE BigData 2019: 206-214 - [c25]Ye Xue, Diego Klabjan, Yuan Luo
Mixture-based Multiple Imputation Model for Clinical Data with a Temporal Dimension. IEEE BigData 2019: 245-252 - [c24]Myat Aung, Simon Demediuk, Yuan Sun, Ye Tu, Yu Ang, Siva Nekkanti, Shantanu Raghav, Diego Klabjan, Rafet Sifa, Anders Drachen
The trails of Just Cause 2: spatio-temporal player profiling in open-world games. FDG 2019: 41:1-41:11 - [i43]Stephanie Ger, Diego Klabjan:
Autoencoders and Generative Adversarial Networks for Anomaly Detection for Sequences. CoRR abs/1901.02514 (2019) - [i42]Yiming Xu, Dnyanesh Rajpathak, Ian Gibbs, Diego Klabjan:
Automatic Ontology Learning from Domain-Specific Short Unstructured Text Data. CoRR abs/1903.04360 (2019) - [i41]Biyi Fang, Diego Klabjan:
Convergence Analyses of Online ADAM Algorithm in Convex Setting and Two-Layer ReLU Neural Network. CoRR abs/1905.09356 (2019) - [i40]Cheolmin Kim, Youngseok Kim, Diego Klabjan:
Scale Invariant Power Iteration. CoRR abs/1905.09882 (2019) - [i39]Xin Qian, Matthew Kennedy, Diego Klabjan:
Dynamic Cell Structure via Recursive-Recurrent Neural Networks. CoRR abs/1905.10540 (2019) - [i38]Xiaoyi Liu, Diego Klabjan, Patrick N. Bless:
Data Extraction from Charts via Single Deep Neural Network. CoRR abs/1906.11906 (2019) - [i37]Ye Xue, Diego Klabjan, Yuan Luo:
Mixture-based Multiple Imputation Model for Clinical Data with a Temporal Dimension. CoRR abs/1908.04209 (2019) - [i36]Adam Sandler, Diego Klabjan, Yuan Luo:
Conditional Hierarchical Bayesian Tucker Decomposition. CoRR abs/1911.12426 (2019) - 2018
- [j55]Young Woong Park
Three iteratively reweighted least squares algorithms for L1 -norm principal component analysis. Knowl. Inf. Syst. 54(3): 541-565 (2018) - [j54]Mingyang Di, Diego Klabjan, Long Sha, Patrick Lucey:
Large-Scale Adversarial Sports Play Retrieval with Learning to Rank. ACM Trans. Knowl. Discov. Data 12(6): 69:1-69:18 (2018) - [j53]Frank Schneider, Ulrich W. Thonemann
Optimization of Battery Charging and Purchasing at Electric Vehicle Battery Swap Stations. Transp. Sci. 52(5): 1211-1234 (2018) - [c23]Rafet Sifa, Eric Pawlakos, Kevin Zhai, Sai Haran, Rohan Jha, Diego Klabjan, Anders Drachen
Controlling the crucible: a novel PvP recommender systems framework for destiny. ACSW 2018: 39:1-39:10 - [c22]Anders Drachen
To be or not to be...social: incorporating simple social features in mobile game customer lifetime value predictions. ACSW 2018: 40:1-40:10 - [c21]Xu Teng
Location-Awareness in Time Series Compression. ADBIS 2018: 82-95 - [c20]Xingyu Wang, Diego Klabjan:
Competitive Multi-agent Inverse Reinforcement Learning with Sub-optimal Demonstrations. ICML 2018: 5130-5138 - [p1]Conrado Borraz-Sánchez, Diego Klabjan, Emir Pasalic, Molham Aref:
SolverBlox: algebraic modeling in datalog. Declarative Logic Programming 2018: 331-354 - [i35]Xingyu Wang, Diego Klabjan:
Competitive Multi-agent Inverse Reinforcement Learning with Sub-optimal Demonstrations. CoRR abs/1801.02124 (2018) - [i34]Papis Wongchaisuwat, Diego Klabjan:
Truth Validation with Evidence. CoRR abs/1802.05786 (2018) - [i33]Biyi Fang, Diego Klabjan:
A Stochastic Large-scale Machine Learning Algorithm for Distributed Features and Observations. CoRR abs/1803.11287 (2018) - [i32]Jaehoon Koo, Diego Klabjan:
Improved Classification Based on Deep Belief Networks. CoRR abs/1804.09812 (2018) - [i31]Yiming Xu, Diego Klabjan:
k-Nearest Neighbors by Means of Sequence to Sequence Deep Neural Networks and Memory Networks. CoRR abs/1804.11214 (2018) - [i30]Jie Yang, Diego Klabjan:
Bayesian active learning for choice models with deep Gaussian processes. CoRR abs/1805.01867 (2018) - [i29]Alexander Stec, Diego Klabjan:
Forecasting Crime with Deep Learning. CoRR abs/1806.01486 (2018) - [i28]Mark Harmon, Diego Klabjan:
Dynamic Prediction Length for Time Series with Sequence to Sequence Networks. CoRR abs/1807.00425 (2018) - [i27]Alexander Stec, Diego Klabjan, Jean Utke:
Nested multi-instance classification. CoRR abs/1808.10430 (2018) - [i26]Alexander Stec, Diego Klabjan, Jean Utke:
Unified recurrent neural network for many feature types. CoRR abs/1809.08717 (2018) - [i25]Jaehoon Koo, Diego Klabjan, Jean Utke:
Combined convolutional and recurrent neural networks for hierarchical classification of images. CoRR abs/1809.09574 (2018) - [i24]Lida Zhang, Diego Klabjan:
Layer Flexible Adaptive Computational Time for Recurrent Neural Networks. CoRR abs/1812.02335 (2018) - 2017
- [j52]Matthew Dixon, Diego Klabjan, Jin Hoon Bang:
Classification-based financial markets prediction using deep neural networks. Algorithmic Finance 6(3-4): 67-77 (2017) - [j51]Young Woong Park
Algorithms for Generalized Clusterwise Linear Regression. INFORMS J. Comput. 29(2): 301-317 (2017) - [j50]Young Woong Park, Diego Klabjan:
Bayesian Network Learning via Topological Order. J. Mach. Learn. Res. 18: 99:1-99:32 (2017) - [j49]Timothy M. Sweda, Irina S. Dolinskaya, Diego Klabjan:
Optimal Recharging Policies for Electric Vehicles. Transp. Sci. 51(2): 457-479 (2017) - [j48]Timothy M. Sweda, Irina S. Dolinskaya, Diego Klabjan:
Adaptive Routing and Recharging Policies for Electric Vehicles. Transp. Sci. 51(4): 1326-1348 (2017) - [c19]Baiyang Wang, Diego Klabjan:
Regularization for Unsupervised Deep Neural Nets. AAAI 2017: 2681-2687 - [c18]P. Wongchaisuwat, Diego Klabjan, John O. McGinnis:
Predicting litigation likelihood and time to litigation for patents. ICAIL 2017: 257-260 - [c17]Xiaofeng Zhu, Diego Klabjan, Patrick N. Bless:
Semantic Document Distance Measures and Unsupervised Document Revision Detection. IJCNLP(1) 2017: 947-956 - [c16]Xiaofeng Zhu, Diego Klabjan, Patrick N. Bless:
Unsupervised Terminological Ontology Learning Based on Hierarchical Topic Modeling. IRI 2017: 32-41 - [c15]Alexandros Nathan, Diego Klabjan:
Optimization for Large-Scale Machine Learning with Distributed Features and Observations. MLDM 2017: 132-146 - [c14]Chao Qin, Diego Klabjan, Daniel Russo:
Improving the Expected Improvement Algorithm. NIPS 2017: 5381-5391 - [i23]Young Woong Park, Diego Klabjan:
Bayesian Network Learning via Topological Order. CoRR abs/1701.05654 (2017) - [i22]Jie Yang, Sergey Shebalov, Diego Klabjan:
Semi-supervised Learning for Discrete Choice Models. CoRR abs/1702.05137 (2017) - [i21]Baiyang Wang, Diego Klabjan:
An Attention-Based Deep Net for Learning to Rank. CoRR abs/1702.06106 (2017) - [i20]Mark Harmon, Diego Klabjan:
Activation Ensembles for Deep Neural Networks. CoRR abs/1702.07790 (2017) - [i19]Yintai Ma, Diego Klabjan:
Convergence Analysis of Batch Normalization for Deep Neural Nets. CoRR abs/1705.08011 (2017) - [i18]Chao Qin, Diego Klabjan, Daniel Russo:
Improving the Expected Improvement Algorithm. CoRR abs/1705.10033 (2017) - [i17]Yaxiong Zeng, Diego Klabjan:
Online Adaptive Machine Learning Based Algorithm for Implied Volatility Surface Modeling. CoRR abs/1706.01833 (2017) - [i16]Xiaofeng Zhu, Diego Klabjan, Patrick N. Bless:
Unsupervised Terminological Ontology Learning based on Hierarchical Topic Modeling. CoRR abs/1708.09025 (2017) - [i15]Xiaofeng Zhu, Diego Klabjan, Patrick N. Bless:
Semantic Document Distance Measures and Unsupervised Document Revision Detection. CoRR abs/1709.01256 (2017) - [i14]Cheolmin Kim, Diego Klabjan:
L1-norm Kernel PCA. CoRR abs/1709.10152 (2017) - [i13]Baiyang Wang, Diego Klabjan:
Generative Adversarial Nets for Multiple Text Corpora. CoRR abs/1712.09127 (2017) - 2016
- [j47]Young Woong Park
An aggregate and iterative disaggregate algorithm with proven optimality in machine learning. Mach. Learn. 105(2): 199-232 (2016) - [j46]Anupam Seth, Diego Klabjan, Placid M. Ferreira:
A new novel local search integer-programming-based heuristic for PCB assembly on collect-and-place machines. Math. Program. Comput. 8(1): 1-45 (2016) - [c13]Baiyang Wang, Diego Klabjan:
Temporal Topic Analysis with Endogenous and Exogenous Processes. AAAI 2016: 3045-3051 - [c12]Anders Drachen, Eric Thurston Lundquist, Yungjen Kung, Pranav Simha Rao, Rafet Sifa, Julian Runge, Diego Klabjan:
Rapid Prediction of Player Retention in Free-to-Play Mobile Games. AIIDE 2016: 23-29 - [c11]Anders Drachen
Guns and guardians: Comparative cluster analysis and behavioral profiling in destiny. CIG 2016: 1-8 - [c10]Young Woong Park, Diego Klabjan:
Iteratively Reweighted Least Squares Algorithms for L1-Norm Principal Component Analysis. ICDM 2016: 430-438 - [i12]Anders Drachen, Joseph Riley, Shawna Baskin, Diego Klabjan:
Going Out of Business: Auction House Behavior in the Massively Multi-Player Online Game. CoRR abs/1603.07610 (2016) - [i11]Eun Hee Ko, Diego Klabjan:
Semantic Properties of Customer Sentiment in Tweets. CoRR abs/1603.07624 (2016) - [i10]Taeheon Jeong, Diego Klabjan, Justin Starren:
Predictive Analytics Using Smartphone Sensors for Depressive Episodes. CoRR abs/1603.07692 (2016) - [i9]Matthew Dixon, Diego Klabjan, Jin Hoon Bang:
Classiffication-based Financial Markets Prediction using Deep Neural Networks. CoRR abs/1603.08604 (2016) - [i8]Baiyang Wang, Diego Klabjan:
Temporal Topic Analysis with Endogenous and Exogenous Processes. CoRR abs/1607.01274 (2016) - [i7]Young Woong Park, Diego Klabjan:
An Aggregate and Iterative Disaggregate Algorithm with Proven Optimality in Machine Learning. CoRR abs/1607.01400 (2016) - [i6]Young Woong Park, Yan Jiang, Diego Klabjan, Loren Williams:
Algorithms for Generalized Cluster-wise Linear Regression. CoRR abs/1607.01417 (2016) - [i5]Anders Drachen, Eric Thurston Lundquist, Yungjen Kung, Pranav Simha Rao, Diego Klabjan, Rafet Sifa, Julian Runge:
Rapid Prediction of Player Retention in Free-to-Play Mobile Games. CoRR abs/1607.03202 (2016) - [i4]Baiyang Wang, Diego Klabjan:
Regularization for Unsupervised Deep Neural Nets. CoRR abs/1608.04426 (2016) - [i3]Young Woong Park, Diego Klabjan:
Iteratively Reweighted Least Squares Algorithms for L1-Norm Principal Component Analysis. CoRR abs/1609.02997 (2016) - [i2]Mark Harmon, Patrick Lucey, Diego Klabjan:
Predicting Shot Making in Basketball using Convolutional Neural Networks Learnt from Adversarial Multiagent Trajectories. CoRR abs/1609.04849 (2016) - [i1]Alexandros Nathan, Diego Klabjan:
Optimization for Large-Scale Machine Learning with Distributed Features and Observations. CoRR abs/1610.10060 (2016) - 2015
- [j45]Young Woong Park
Lot sizing with minimum order quantity. Discret. Appl. Math. 181: 235-254 (2015) - [j44]Sergey Shebalov, Young Woong Park
Lifting for mixed integer programs with variable upper bounds. Discret. Appl. Math. 186: 226-250 (2015) - [j43]Christian Almeder
Lead time considerations for the multi-level capacitated lot-sizing problem. Eur. J. Oper. Res. 241(3): 727-738 (2015) - [c9]Matthew Dixon, Diego Klabjan, Jin Hoon Bang:
Implementing deep neural networks for financial market prediction on the Intel Xeon Phi. WHPCF@SC 2015: 6:1-6:6 - 2014
- [j42]Jinxiang Pei, Diego Klabjan, Wei Xie:
Approximations to auctions of digital goods with share-averse bidders. Electron. Commer. Res. Appl. 13(2): 128-138 (2014) - [j41]Anders Drachen
Going out of business: Auction house behavior in the Massively Multi-player Online Game Glitch. Entertain. Comput. 5(4): 219-232 (2014) - [j40]Luís Guimarães
Modeling lotsizing and scheduling problems with sequence dependent setups. Eur. J. Oper. Res. 239(3): 644-662 (2014) - [j39]Diego Klabjan, Wojciech Olszewski, Asher Wolinsky:
Attributes. Games Econ. Behav. 88: 190-206 (2014) - [j38]Nir Halman, Diego Klabjan, Chung-Lun Li
Fully Polynomial Time Approximation Schemes for Stochastic Dynamic Programs. SIAM J. Discret. Math. 28(4): 1725-1796 (2014) - [j37]Diego Klabjan, Warren B. Powell:
Guest Editorial: Special Issue on Energy and Transportation. Transp. Sci. 48(4): 465-466 (2014) - [c8]Eun Hee Ko, Diego Klabjan:
Semantic Properties of Customer Sentiment in Tweets. AINA Workshops 2014: 657-663 - [c7]Anders Drachen
Skill-based differences in spatio-temporal team behaviour in defence of the Ancients 2 (DotA 2). GEM 2014: 1-8 - 2013
- [j36]Conrado Borraz-Sánchez, Diego Klabjan:
Optimal placement of reconfigurable optical add/drop multiplexers with packing, blocking, and signal loss. Comput. Networks 57(6): 1443-1458 (2013) - [j35]Frank Schneider, Diego Klabjan:
Inventory control in multi-channel retail. Eur. J. Oper. Res. 227(1): 101-111 (2013) - [j34]Luís Guimarães
Pricing, relaxing and fixing under lot sizing and scheduling. Eur. J. Oper. Res. 230(2): 399-411 (2013) - [j33]Anupam Seth, Diego Klabjan, Placid M. Ferreira:
Analyses of advanced iterated tour partitioning heuristics for generalized vehicle routing problems. Networks 61(4): 290-308 (2013) - 2012
- [j32]Patrick N. Bless, Diego Klabjan, Soo Y. Chang:
Automated knowledge source selection and service composition. Comput. Optim. Appl. 52(2): 507-535 (2012) - [j31]Yijia Zhao, Diego Klabjan:
A polyhedral study of lot-sizing with supplier selection. Discret. Optim. 9(2): 65-76 (2012) - [j30]Luís Guimarães
Annual production budget in the beverage industry. Eng. Appl. Artif. Intell. 25(2): 229-241 (2012) - [j29]Jaemyung Ahn, Olivier L. de Weck
Column generation based heuristics for a generalized location routing problem with profits arising in space exploration. Eur. J. Oper. Res. 223(1): 47-59 (2012) - [j28]Daniel Adelman, Diego Klabjan:
Computing Near-Optimal Policies in Generalized Joint Replenishment. INFORMS J. Comput. 24(1): 148-164 (2012) - 2011
- [j27]Milind G. Sohoni
Robust Airline Scheduling Under Block-Time Uncertainty. Transp. Sci. 45(4): 451-464 (2011) - 2010
- [j26]Bernardo Almada-Lobo
Multiple machine continuous setup lotsizing with sequence-dependent setups. Comput. Optim. Appl. 47(3): 529-552 (2010) - [j25]Luke Schenk, Diego Klabjan:
Intra market optimization for express package carriers with station to station travel and proportional sorting. Comput. Oper. Res. 37(10): 1749-1761 (2010) - [j24]Hector Gonzalez, Jiawei Han, Hong Cheng, Xiaolei Li, Diego Klabjan, Tianyi Wu:
Modeling Massive RFID Data Sets: A Gateway-Based Movement Graph Approach. IEEE Trans. Knowl. Data Eng. 22(1): 90-104 (2010) - [j23]Shawn Choo, Diego Klabjan, David Simchi-Levi:
Multiship Crane Sequencing with Yard Congestion Constraints. Transp. Sci. 44(1): 98-115 (2010)
2000 – 2009
- 2009
- [j22]Nir Halman, Diego Klabjan, Mohamed Mostagir, James B. Orlin
A Fully Polynomial-Time Approximation Scheme for Single-Item Stochastic Inventory Control with Discrete Demand. Math. Oper. Res. 34(3): 674-685 (2009) - [c6]Chun-cheng Chen, Chandra Chekuri, Diego Klabjan:
Topology Formation for Wireless Mesh Network Planning. INFOCOM 2009: 2671-2675 - 2008
- [j21]Patrick N. Bless, Diego Klabjan, Soo Y. Chang:
Heuristics for automated knowledge source integration and service composition. Comput. Oper. Res. 35(4): 1292-1314 (2008) - [j20]Luke Schenk, Diego Klabjan:
Intramarket Optimization for Express Package Carriers. Transp. Sci. 42(4): 530-545 (2008) - [c5]Nir Halman, Diego Klabjan, Chung-Lun Li, James B. Orlin, David Simchi-Levi:
Fully polynomial time approximation schemes for stochastic dynamic programs. SODA 2008: 700-709 - 2007
- [j19]Diego Klabjan:
Subadditive approaches in integer programming. Eur. J. Oper. Res. 183(2): 525-545 (2007) - [j18]Rivi Sandhu, Diego Klabjan:
Integrated Airline Fleeting and Crew-Pairing Decisions. Oper. Res. 55(3): 439-456 (2007) - [j17]Diego Klabjan, Daniel Adelman:
An Infinite-Dimensional Linear Programming Algorithm for Deterministic Semi-Markov Decision Processes on Borel Spaces. Math. Oper. Res. 32(3): 528-550 (2007) - 2006
- [j16]Sergey Shebalov, Diego Klabjan:
Sequence Independent Lifting for Mixed Integer Programs with Variable Upper Bounds. Math. Program. 105(2-3): 523-561 (2006) - [j15]Diego Klabjan, Daniel Adelman:
Existence of Optimal Policies for Semi-Markov Decision Processes Using Duality for Infinite Linear Programming. SIAM J. Control. Optim. 44(6): 2104-2122 (2006) - [j14]Sergey Shebalov, Diego Klabjan:
Robust Airline Crew Pairing: Move-up Crews. Transp. Sci. 40(3): 300-312 (2006) - [j13]Rivi Sandhu, Diego Klabjan:
Fleeting with Passenger and Cargo Origin-Destination Booking Control. Transp. Sci. 40(4): 517-528 (2006) - [c4]Jiawei Han, Hector Gonzalez, Xiaolei Li, Diego Klabjan:
Warehousing and Mining Massive RFID Data Sets. ADMA 2006: 1-18 - [c3]Hector Gonzalez, Jiawei Han, Xiaolei Li, Diego Klabjan:
Warehousing and Analyzing Massive RFID Data Sets. ICDE 2006: 83 - 2005
- [j12]Daniel Adelman, Diego Klabjan:
Duality and Existence of Optimal Policies in Generalized Joint Replenishment. Math. Oper. Res. 30(1): 28-50 (2005) - 2004
- [j11]Diego Klabjan:
A Practical Algorithm for Computing a Subadditive Dual Function for Set Partitioning. Comput. Optim. Appl. 29(3): 347-368 (2004) - [j10]Alexandra Makri, Diego Klabjan:
A New Pricing Scheme for Airline Crew Scheduling. INFORMS J. Comput. 16(1): 56-67 (2004) - 2003
- [j9]Alexandra Makri, Diego Klabjan:
Algorithms for source-to-all maximum cost-to-time ratio problem in acyclic networks. Networks 42(1): 1-14 (2003) - 2002
- [j8]Diego Klabjan, George L. Nemhauser:
A Polyhedral Study of Integer Variable Upper Bounds. Math. Oper. Res. 27(4): 711-739 (2002) - [j7]Diego Klabjan, Ellis L. Johnson, George L. Nemhauser, Eric Gelman, Srini Ramaswamy:
Airline Crew Scheduling with Time Windows and Plane-Count Constraints. Transp. Sci. 36(3): 337-348 (2002) - [c2]Diego Klabjan:
A New Subadditive Approach to Integer Programming. IPCO 2002: 384-400 - 2001
- [j6]Diego Klabjan, Ellis L. Johnson, George L. Nemhauser, Eric Gelman, Srini Ramaswamy:
Solving Large Airline Crew Scheduling Problems: Random Pairing Generation and Strong Branching. Comput. Optim. Appl. 20(1): 73-91 (2001) - [j5]Paolo Toth, Hillel Bar-Gera, Diego Klabjan, Roberto Baldacci, Cenk Çaliskan, Christina Diakaki, Lasse Fridström, Vijay S. Nori:
Abstracts for the 2000 Transportation Science Section Dissertation Prize Competition. Transp. Sci. 35(1): 99-103 (2001) - [j4]Diego Klabjan, Ellis L. Johnson, George L. Nemhauser, Eric Gelman, Srini Ramaswamy:
Airline Crew Scheduling with Regularity. Transp. Sci. 35(4): 359-374 (2001) - [c1]Diego Klabjan, Karsten Schwan:
Airline Crew Pairing Generation in Parallel. PP 2001 - 2000
- [j3]Diego Klabjan, Ellis L. Johnson, George L. Nemhauser:
A parallel primal-dual simplex algorithm. Oper. Res. Lett. 27(2): 47-55 (2000)
1990 – 1999
- 1998
- [j2]Diego Klabjan, Bojan Mohar:
The number of matchings of low order in hexagonal systems. Discret. Math. 186(1-3): 167-175 (1998) - [j1]Diego Klabjan, George L. Nemhauser, Craig A. Tovey:
The complexity of cover inequality separation. Oper. Res. Lett. 23(1-2): 35-40 (1998)
Coauthor Index
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