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A list of all the posts and pages found on the site. For you robots out there is an XML version available for digesting as well.
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Crime Analysis Tool for Spatio-temporal and Contextual Link Interpretability
Published in , 1900
F. Ilhan, O. Karaahmetoglu, S. F. Tekin, I. Balaban and S. S. Kozat, “Crime Analysis Tool for Spatio-temporal and Contextual Link Interpretability”, Turkish Patent, 2020.
Causality Inference for Multivariate Time Series Prediction
Published in , 1900
F. Ilhan, “Causality Inference for Multivariate Time Series Prediction”, to be submitted to Advances in Neural Information Processing Systems 34, 2021.
Stability of the Decoupled Extended Kalman Filter in LSTM-Based Online Learning
Published in , 1900
N. M. Vural, F. Ilhan and S. S. Kozat, “Stability of the Decoupled Extended Kalman Filter in LSTM-Based Online Learning”, Digital Signal Processing, 2020.
Energy Consumption Forecasting with Time Series Clusterings
Published in , 1900
F. Ilhan, O. Karaahmetoglu, S. F. Tekin, I. Balaban and S. S. Kozat, “Energy Consumption Forecasting with Time Series Clustering”, Turkish Patent, 2020.
LSTM-Based Online Learning with Extended Kalman Filter Based Training Algorithm
Published in , 1900
F. Ilhan, N. M. Vural and S. S. Kozat, “LSTM-Based Online Learning with Extended Kalman Filter Based Training Algorithm”, 28th IEEE Signal Processing and Communications Applications, 2020.
Spatio-temporal Sparse Event Prediction with Hierarchical Expert Models
Published in , 1900
F. Ilhan, O. Karaahmetoglu, S. F. Tekin, I. Balaban and S. S. Kozat, “Spatio-temporal Sparse Event Prediction with Hierarchical Expert Models”, Turkish Patent, 2020.
Contextually Hierarchical Online Time Series Anomaly Detection using Weakly Labeled Data
Published in , 1900
F. Ilhan and S. S. Kozat, “Contextually Hierarchical Online Time Series Anomaly Detection using Weakly Labeled Data”, to be submitted to IEEE Transactions on Neural Networks and Learning Systems, 2020.
Accelerating Min-Max Optimization with Application to Minimal Bounding Sphere
Published in , 1900
H. Gokcesu, F. Ilhan, K. Gokcesu and S. S. Kozat, “Accelerating Min-Max Optimization with Application to Minimal Bounding Sphere”, IEEE Transactions on Signal Processing, 2020.
Memory-Augmented Multi-Switching Time Series Prediction
Published in , 1900
F. Ilhan, “Memory-Augmented Multi-Switching Time Series Prediction”, to be submitted to Advances in Neural Information Processing Systems 34, 2021.
5G Channel State Estimation in MIMO Networks with Deep Learning
Published in , 1900
F. Ilhan, O. Karaahmetoglu and A. T. Koc, “5G Channel State Estimation in MIMO Networks with Deep Learning”, to be submitted to IEEE Transactions on Signal Processing, 2020.
Minimax Optimal Online Stochastic Learning for Sequences of Convex Functions under Sub-Gradient Observation Failures
Published in , 1900
H. Gokcesu, F. Ilhan, O. Karaahmetoglu and S. S. Kozat, “Minimax Optimal Online Stochastic Learning for Sequences of Convex Functions under Sub-Gradient Observation Failures”, IEEE Transactions on Signal Processing, 2020.
RNN-Based Online Learning: An Efficient First-Order Optimization Algorithm with a Convergence Guarantee
Published in , 1900
N. M. Vural, S. F. Yilmaz, F. Ilhan and S. S. Kozat, “RNN-Based Online Learning: An Efficient First-Order Optimization Algorithm with a Convergence Guarantee”, IEEE Transactions on Signal Processing, 2020.
Online Shortest Path Learning via Convex Optimization
Published in , 1900
N. M. Vural, B. Altas, F. Ilhan and S. S. Kozat, “Online Shortest Path Learning via Convex Optimization”, 28th IEEE Signal Processing and Communications Applications, 2020.
Shortest Path Learning in Non-Stationary Environments via Online Convex Optimization
Published in , 1900
N. M. Vural, B. Altas, F. Ilhan and S. S. Kozat, “Shortest Path Learning in Non-Stationary Environments via Online Convex Optimization”, 28th IEEE Signal Processing and Communications Applications, 2020.
Performance Analysis of Semi-Supervised Learning Methods under Different Missing Label Patterns
Published in , 1900
F. Ilhan and E. Mumcuoglu, “Performance Analysis of Semi-Supervised Learning Methods under Different Missing Label Patterns”, 28th IEEE Signal Processing and Communications Applications, 2020.
Self-Supervised Multi-Contextual Representation Learning for Time Series
Published in , 1900
F. Ilhan, “Self-Supervised Multi-Contextual Representation Learning for Time Series”, to be submitted to Advances in Neural Information Processing Systems 34, 2021.
Modeling of Spatio-Temporal Hawkes Processes with Randomized Kernels
Published in , 1900
F. Ilhan and S. S. Kozat, “Modeling of Spatio-Temporal Hawkes Processes with Randomized Kernels”, IEEE Transactions on Signal Processing, 2020.
Short-Term Time Series Prediction with Side Information-based Switching using RNNs
Published in , 1900
F. Ilhan and S. S. Kozat, “Short-Term Time Series Prediction with Side Information-based Switching using RNNs”, to be submitted to IEEE Transactions on Neural Networks and Learning Systems, 2020.
Spatio-Temporal Weather Forecasting and Attention Mechanism on Convolutional LSTMs
Published in , 1900
S. F. Tekin, O. Karaahmetoglu, F. Ilhan and S. S. Kozat, “Spatio-Temporal Weather Forecasting and Attention Mechanism on Convolutional LSTMs”, IEEE Transactions on Pattern Analysis and Machine Intelligence, 2021.
Spatio-Temporal Crime Prediction via Temporally Hierarchical Convolutional Neural Networks
Published in , 1900
F. Ilhan, S. F. Tekin and B. Aksoy, “Spatio-Temporal Crime Prediction via Temporally Hierarchical Convolutional Neural Networks”, 28th IEEE Signal Processing and Communications Applications, 2020.
A Two-Stage Multi-Class Classification Approach Based on Anomaly Detection
Published in , 1900
F. Ilhan, S. F. Yilmaz and S. S. Kozat, “A Two-Stage Multi-Class Classification Approach Based on Anomaly Detection”, 28th IEEE Signal Processing and Communications Applications, 2020.
Unsupervised Online Anomaly Detection On Irregularly Sampled Or Missing Valued Time-Series Data Using LSTM Networks
Published in , 1900
O. Karaahmetoglu, F. Ilhan and S. S. Kozat, “Unsupervised Online Anomaly Detection On Irregularly Sampled Or Missing Valued Time-Series Data Using LSTM Networks”, IEEE Transactions on Neural Networks and Learning Systems, 2020.
Markovian RNN: An Adaptive Time Series Prediction Network with HMM-based Switching for Nonstationary Environments
Published in , 1900
F. Ilhan, O. Karaahmetoglu, Ismail Balaban and S. S. Kozat, “Markovian RNN: An Adaptive Time Series Prediction Network with HMM-based Switching for Nonstationary Environments”, IEEE Transactions on Neural Networks and Learning Systems, 2020.
Achieving Online Regression Performance of LSTMs with Simple RNNs
Published in , 1900
N. M. Vural, F. Ilhan, S. F. Yilmaz and S. S. Kozat, “Achieving Online Regression Performance of LSTMs with Simple RNNs”, IEEE Transactions on Neural Networks and Learning Systems, 2020.