Decebal Constantin Mocanu

ORCID

Publication Activity (10 Years)

Years Active: 2013-2024
Publications (10 Years): 93

Top Venues

Publications

Qiao Xiao, Pingchuan Ma, Adriana Fernandez-Lopez, Boqian Wu, Lu Yin, Stavros Petridis, Mykola Pechenizkiy, Maja Pantic, Decebal Constantin Mocanu, Shiwei Liu
Dynamic Data Pruning for Automatic Speech Recognition. CoRR (2024)
Bram Grooten, Tristan Tomilin, Gautham Vasan, Matthew E. Taylor, A. Rupam Mahmood, Meng Fang, Mykola Pechenizkiy, Decebal Constantin Mocanu
MaDi: Learning to Mask Distractions for Generalization in Visual Deep Reinforcement Learning. AAMAS (2024)
Murat Onur Yildirim, Elif Ceren Gok Yildirim, Decebal Constantin Mocanu, Joaquin Vanschoren
FOCIL: Finetune-and-Freeze for Online Class Incremental Learning by Training Randomly Pruned Sparse Experts. CoRR (2024)
Calarina Muslimani, Bram Grooten, Deepak Ranganatha Sastry Mamillapalli, Mykola Pechenizkiy, Decebal Constantin Mocanu, Matthew E. Taylor
Boosting Robustness in Preference-Based Reinforcement Learning with Dynamic Sparsity. CoRR (2024)
Kaiting Liu, Zahra Atashgahi, Ghada Sokar, Mykola Pechenizkiy, Decebal Constantin Mocanu
Supervised Feature Selection via Ensemble Gradient Information from Sparse Neural Networks. AISTATS (2024)
Shiwei Liu, Tianlong Chen, Xiaohan Chen, Xuxi Chen, Qiao Xiao, Boqian Wu, Tommi Kärkkäinen, Mykola Pechenizkiy, Decebal Constantin Mocanu, Zhangyang Wang
More ConvNets in the 2020s: Scaling up Kernels Beyond 51x51 using Sparsity. ICLR (2023)
Murat Onur Yildirim, Elif Ceren Gok Yildirim, Ghada Sokar, Decebal Constantin Mocanu, Joaquin Vanschoren
Continual Learning with Dynamic Sparse Training: Exploring Algorithms for Effective Model Updates. CoRR (2023)
Zahra Atashgahi, Mykola Pechenizkiy, Raymond N. J. Veldhuis, Decebal Constantin Mocanu
Adaptive Sparsity Level during Training for Efficient Time Series Forecasting with Transformers. CoRR (2023)
Karine Miras, Decebal Constantin Mocanu, A. E. Eiben
Hu-bot: promoting the cooperation between humans and mobile robots. Neural Comput. Appl. 35 (23) (2023)
Aleksandra Nowak, Bram Grooten, Decebal Constantin Mocanu, Jacek Tabor
Fantastic Weights and How to Find Them: Where to Prune in Dynamic Sparse Training. NeurIPS (2023)
Zahra Atashgahi, Xuhao Zhang, Neil Kichler, Shiwei Liu, Lu Yin, Mykola Pechenizkiy, Raymond N. J. Veldhuis, Decebal Constantin Mocanu
Supervised Feature Selection with Neuron Evolution in Sparse Neural Networks. CoRR (2023)
Bram Grooten, Ghada Sokar, Shibhansh Dohare, Elena Mocanu, Matthew E. Taylor, Mykola Pechenizkiy, Decebal Constantin Mocanu
Automatic Noise Filtering with Dynamic Sparse Training in Deep Reinforcement Learning. CoRR (2023)
Zahra Atashgahi, Xuhao Zhang, Neil Kichler, Shiwei Liu, Lu Yin, Mykola Pechenizkiy, Raymond N. J. Veldhuis, Decebal Constantin Mocanu
Supervised Feature Selection with Neuron Evolution in Sparse Neural Networks. Trans. Mach. Learn. Res. 2023 (2023)
Bram Grooten, Ghada Sokar, Shibhansh Dohare, Elena Mocanu, Matthew E. Taylor, Mykola Pechenizkiy, Decebal Constantin Mocanu
Automatic Noise Filtering with Dynamic Sparse Training in Deep Reinforcement Learning. AAMAS (2023)
Bram Grooten, Tristan Tomilin, Gautham Vasan, Matthew E. Taylor, A. Rupam Mahmood, Meng Fang, Mykola Pechenizkiy, Decebal Constantin Mocanu
MaDi: Learning to Mask Distractions for Generalization in Visual Deep Reinforcement Learning. CoRR (2023)
Aleksandra Nowak, Bram Grooten, Decebal Constantin Mocanu, Jacek Tabor
Fantastic Weights and How to Find Them: Where to Prune in Dynamic Sparse Training. CoRR (2023)
Boqian Wu, Qiao Xiao, Shiwei Liu, Lu Yin, Mykola Pechenizkiy, Decebal Constantin Mocanu, Maurice van Keulen, Elena Mocanu
E2ENet: Dynamic Sparse Feature Fusion for Accurate and Efficient 3D Medical Image Segmentation. CoRR (2023)
Shiwei Liu, Tianlong Chen, Xiaohan Chen, Li Shen, Decebal Constantin Mocanu, Zhangyang Wang, Mykola Pechenizkiy
The Unreasonable Effectiveness of Random Pruning: Return of the Most Naive Baseline for Sparse Training. CoRR (2022)
Manuel Muñoz Sánchez, Denis Pogosov, Emilia Silvas, Decebal Constantin Mocanu, Jos Elfring, René van de Molengraft
Situation-Aware Drivable Space Estimation for Automated Driving. IEEE Trans. Intell. Transp. Syst. 23 (7) (2022)
Zahra Atashgahi, Ghada Sokar, Tim van der Lee, Elena Mocanu, Decebal Constantin Mocanu, Raymond N. J. Veldhuis, Mykola Pechenizkiy
Quick and robust feature selection: the strength of energy-efficient sparse training for autoencoders. Mach. Learn. 111 (1) (2022)
Shiwei Liu, Tianlong Chen, Zahra Atashgahi, Xiaohan Chen, Ghada Sokar, Elena Mocanu, Mykola Pechenizkiy, Zhangyang Wang, Decebal Constantin Mocanu
Deep Ensembling with No Overhead for either Training or Testing: The All-Round Blessings of Dynamic Sparsity. ICLR (2022)
Shiwei Liu, Tianlong Chen, Xiaohan Chen, Li Shen, Decebal Constantin Mocanu, Zhangyang Wang, Mykola Pechenizkiy
The Unreasonable Effectiveness of Random Pruning: Return of the Most Naive Baseline for Sparse Training. ICLR (2022)
Qiao Xiao, Boqian Wu, Yu Zhang, Shiwei Liu, Mykola Pechenizkiy, Elena Mocanu, Decebal Constantin Mocanu
Dynamic Sparse Network for Time Series Classification: Learning What to "See". NeurIPS (2022)
Zahra Atashgahi, Decebal Constantin Mocanu, Raymond N. J. Veldhuis, Mykola Pechenizkiy
Memory-free Online Change-point Detection: A Novel Neural Network Approach. CoRR (2022)
Ghada Sokar, Zahra Atashgahi, Mykola Pechenizkiy, Decebal Constantin Mocanu
Where to Pay Attention in Sparse Training for Feature Selection? NeurIPS (2022)
Ghada Sokar, Zahra Atashgahi, Mykola Pechenizkiy, Decebal Constantin Mocanu
Where to Pay Attention in Sparse Training for Feature Selection? CoRR (2022)
Qiao Xiao, Boqian Wu, Yu Zhang, Shiwei Liu, Mykola Pechenizkiy, Elena Mocanu, Decebal Constantin Mocanu
Dynamic Sparse Network for Time Series Classification: Learning What to "see". CoRR (2022)
Ghada Sokar, Elena Mocanu, Decebal Constantin Mocanu, Mykola Pechenizkiy, Peter Stone
Dynamic Sparse Training for Deep Reinforcement Learning. IJCAI (2022)
Zahra Atashgahi, Joost Pieterse, Shiwei Liu, Decebal Constantin Mocanu, Raymond N. J. Veldhuis, Mykola Pechenizkiy
A brain-inspired algorithm for training highly sparse neural networks. Mach. Learn. 111 (12) (2022)
Shiwei Liu, Tianlong Chen, Xiaohan Chen, Xuxi Chen, Qiao Xiao, Boqian Wu, Mykola Pechenizkiy, Decebal Constantin Mocanu, Zhangyang Wang
More ConvNets in the 2020s: Scaling up Kernels Beyond 51x51 using Sparsity. CoRR (2022)
Ghada Sokar, Decebal Constantin Mocanu, Mykola Pechenizkiy
Avoiding Forgetting and Allowing Forward Transfer in Continual Learning via Sparse Networks. ECML/PKDD (3) (2022)
Lu Yin, Vlado Menkovski, Meng Fang, Tianjin Huang, Yulong Pei, Mykola Pechenizkiy, Decebal Constantin Mocanu, Shiwei Liu
Superposing Many Tickets into One: A Performance Booster for Sparse Neural Network Training. CoRR (2022)
Tianjin Huang, Tianlong Chen, Meng Fang, Vlado Menkovski, Jiaxu Zhao, Lu Yin, Yulong Pei, Decebal Constantin Mocanu, Zhangyang Wang, Mykola Pechenizkiy, Shiwei Liu
You Can Have Better Graph Neural Networks by Not Training Weights at All: Finding Untrained GNNs Tickets. LoG (2022)
Tianjin Huang, Tianlong Chen, Meng Fang, Vlado Menkovski, Jiaxu Zhao, Lu Yin, Yulong Pei, Decebal Constantin Mocanu, Zhangyang Wang, Mykola Pechenizkiy, Shiwei Liu
You Can Have Better Graph Neural Networks by Not Training Weights at All: Finding Untrained GNNs Tickets. CoRR (2022)
Shiwei Liu, Decebal Constantin Mocanu, Amarsagar Reddy Ramapuram Matavalam, Yulong Pei, Mykola Pechenizkiy
Sparse evolutionary deep learning with over one million artificial neurons on commodity hardware. Neural Comput. Appl. 33 (7) (2021)
Shiwei Liu, Tianlong Chen, Zahra Atashgahi, Xiaohan Chen, Ghada Sokar, Elena Mocanu, Mykola Pechenizkiy, Zhangyang Wang, Decebal Constantin Mocanu
FreeTickets: Accurate, Robust and Efficient Deep Ensemble by Training with Dynamic Sparsity. CoRR (2021)
Ghada Sokar, Decebal Constantin Mocanu, Mykola Pechenizkiy
Self-Attention Meta-Learner for Continual Learning. AAMAS (2021)
Ghada Sokar, Decebal Constantin Mocanu, Mykola Pechenizkiy
Addressing the Stability-Plasticity Dilemma via Knowledge-Aware Continual Learning. CoRR (2021)
Shiwei Liu, Lu Yin, Decebal Constantin Mocanu, Mykola Pechenizkiy
Do We Actually Need Dense Over-Parameterization? In-Time Over-Parameterization in Sparse Training. CoRR (2021)
Shiwei Liu, Tianlong Chen, Xiaohan Chen, Zahra Atashgahi, Lu Yin, Huanyu Kou, Li Shen, Mykola Pechenizkiy, Zhangyang Wang, Decebal Constantin Mocanu
Sparse Training via Boosting Pruning Plasticity with Neuroregeneration. NeurIPS (2021)
Ghada Sokar, Decebal Constantin Mocanu, Mykola Pechenizkiy
Self-Attention Meta-Learner for Continual Learning. CoRR (2021)
Ghada Sokar, Elena Mocanu, Decebal Constantin Mocanu, Mykola Pechenizkiy, Peter Stone
Dynamic Sparse Training for Deep Reinforcement Learning. CoRR (2021)
Anil Yaman, Giovanni Iacca, Decebal Constantin Mocanu, Matt Coler, George Fletcher, Mykola Pechenizkiy
Evolving Plasticity for Autonomous Learning under Changing Environmental Conditions. Evol. Comput. 29 (3) (2021)
Shiwei Liu, Tianlong Chen, Xiaohan Chen, Zahra Atashgahi, Lu Yin, Huanyu Kou, Li Shen, Mykola Pechenizkiy, Zhangyang Wang, Decebal Constantin Mocanu
Sparse Training via Boosting Pruning Plasticity with Neuroregeneration. CoRR (2021)
Selima Curci, Decebal Constantin Mocanu, Mykola Pechenizkiy
Truly Sparse Neural Networks at Scale. CoRR (2021)
Decebal Constantin Mocanu, Elena Mocanu, Tiago Pinto, Selima Curci, Phuong H. Nguyen, Madeleine Gibescu, Damien Ernst, Zita A. Vale
Sparse Training Theory for Scalable and Efficient Agents. AAMAS (2021)
Decebal Constantin Mocanu, Elena Mocanu, Tiago Pinto, Selima Curci, Phuong H. Nguyen, Madeleine Gibescu, Damien Ernst, Zita A. Vale
Sparse Training Theory for Scalable and Efficient Agents. CoRR (2021)
Shiwei Liu, Lu Yin, Decebal Constantin Mocanu, Mykola Pechenizkiy
Do We Actually Need Dense Over-Parameterization? In-Time Over-Parameterization in Sparse Training. ICML (2021)
Shiwei Liu, Iftitahu Ni'mah, Vlado Menkovski, Decebal Constantin Mocanu, Mykola Pechenizkiy
Efficient and effective training of sparse recurrent neural networks. Neural Comput. Appl. 33 (15) (2021)
Ghada Sokar, Decebal Constantin Mocanu, Mykola Pechenizkiy
SpaceNet: Make Free Space for Continual Learning. Neurocomputing 439 (2021)
Shiwei Liu, Decebal Constantin Mocanu, Yulong Pei, Mykola Pechenizkiy
Selfish Sparse RNN Training. ICML (2021)
Ghada Sokar, Decebal Constantin Mocanu, Mykola Pechenizkiy
Learning Invariant Representation for Continual Learning. CoRR (2021)
Shiwei Liu, Decebal Constantin Mocanu, Yulong Pei, Mykola Pechenizkiy
Selfish Sparse RNN Training. CoRR (2021)
Zahra Atashgahi, Ghada Sokar, Tim van der Lee, Elena Mocanu, Decebal Constantin Mocanu, Raymond N. J. Veldhuis, Mykola Pechenizkiy
Quick and Robust Feature Selection: the Strength of Energy-efficient Sparse Training for Autoencoders. CoRR (2020)
Sibylle Hess, Wouter Duivesteijn, Decebal Constantin Mocanu
Softmax-based Classification is k-means Clustering: Formal Proof, Consequences for Adversarial Attacks, and Improvement through Centroid Based Tailoring. CoRR (2020)
Ghada Sokar, Decebal Constantin Mocanu, Mykola Pechenizkiy
SpaceNet: Make Free Space For Continual Learning. CoRR (2020)
Manuel Muñoz Sánchez, Emilia Silvas, Denis Pogosov, Decebal Constantin Mocanu
A Hybrid Framework Combining Vehicle System Knowledge with Machine Learning Methods for Improved Highway Trajectory Prediction. SMC (2020)
Anil Yaman, Giovanni Iacca, Decebal Constantin Mocanu, George H. L. Fletcher, Mykola Pechenizkiy
Novelty Producing Synaptic Plasticity. CoRR (2020)
Shiwei Liu, Tim van der Lee, Anil Yaman, Zahra Atashgahi, Davide Ferraro, Ghada Sokar, Mykola Pechenizkiy, Decebal Constantin Mocanu
Topological Insights in Sparse Neural Networks. CoRR (2020)
Shiwei Liu, Tim van der Lee, Anil Yaman, Zahra Atashgahi, Davide Ferraro, Ghada Sokar, Mykola Pechenizkiy, Decebal Constantin Mocanu
Topological Insights into Sparse Neural Networks. ECML/PKDD (3) (2020)
Anil Yaman, Giovanni Iacca, Decebal Constantin Mocanu, George Fletcher, Mykola Pechenizkiy
Novelty producing synaptic plasticity. GECCO Companion (2020)
Shiwei Liu, Decebal Constantin Mocanu, Mykola Pechenizkiy
Intrinsically Sparse Long Short-Term Memory Networks. CoRR (2019)
Francesco Cauteruccio, Giancarlo Fortino, Antonio Guerrieri, Antonio Liotta, Decebal Constantin Mocanu, Cristian Perra, Giorgio Terracina, Maria Torres Vega
Short-long term anomaly detection in wireless sensor networks based on machine learning and multi-parameterized edit distance. Inf. Fusion 52 (2019)
Anil Yaman, Giovanni Iacca, Decebal Constantin Mocanu, George H. L. Fletcher, Mykola Pechenizkiy
Learning with Delayed Synaptic Plasticity. CoRR (2019)
Elena Mocanu, Decebal Constantin Mocanu, Phuong H. Nguyen, Antonio Liotta, Michael E. Webber, Madeleine Gibescu, Johannes G. Slootweg
On-Line Building Energy Optimization Using Deep Reinforcement Learning. IEEE Trans. Smart Grid 10 (4) (2019)
Shiwei Liu, Decebal Constantin Mocanu, Mykola Pechenizkiy
On improving deep learning generalization with adaptive sparse connectivity. CoRR (2019)
Joost Pieterse, Decebal Constantin Mocanu
Evolving and Understanding Sparse Deep Neural Networks using Cosine Similarity. CoRR (2019)
Anil Yaman, Decebal Constantin Mocanu, Giovanni Iacca, Matt Coler, George H. L. Fletcher, Mykola Pechenizkiy
Evolving Plasticity for Autonomous Learning under Changing Environmental Conditions. CoRR (2019)
Shiwei Liu, Decebal Constantin Mocanu, Amarsagar Reddy Ramapuram Matavalam, Yulong Pei, Mykola Pechenizkiy
Sparse evolutionary Deep Learning with over one million artificial neurons on commodity hardware. CoRR (2019)
Anil Yaman, Giovanni Iacca, Decebal Constantin Mocanu, George H. L. Fletcher, Mykola Pechenizkiy
Learning with delayed synaptic plasticity. GECCO (2019)
Decebal Constantin Mocanu, Elena Mocanu
One-Shot Learning using Mixture of Variational Autoencoders: a Generalization Learning approach. CoRR (2018)
Anil Yaman, Decebal Constantin Mocanu, Giovanni Iacca, George H. L. Fletcher, Mykola Pechenizkiy
Limited Evaluation Cooperative Co-evolutionary Differential Evolution for Large-scale Neuroevolution. CoRR (2018)
Decebal Constantin Mocanu
Synopsis of the PhD Thesis - Network Computations in Artificial Intelligence. ITC (1) (2018)
Decebal Constantin Mocanu, Elena Mocanu
One-Shot Learning using Mixture of Variational Autoencoders: a Generalization Learning approach. AAMAS (2018)
Anil Yaman, Decebal Constantin Mocanu, Giovanni Iacca, George H. L. Fletcher, Mykola Pechenizkiy
Limited evaluation cooperative co-evolutionary differential evolution for large-scale neuroevolution. GECCO (2018)
Maria Torres Vega, Decebal Constantin Mocanu, Jeroen Famaey, Stavros Stavrou, Antonio Liotta
Deep Learning for Quality Assessment in Live Video Streaming. IEEE Signal Process. Lett. 24 (6) (2017)
Maria Torres Vega, Cristian Perra, Decebal Constantin Mocanu, Antonio Liotta
Effect of lossy networks on stereoscopic 3D-video streams. BMSB (2017)
Maria Torres Vega, Decebal Constantin Mocanu, Stavros Stavrou, Antonio Liotta
Predictive no-reference assessment of video quality. Signal Process. Image Commun. 52 (2017)
Maria Torres Vega, Decebal Constantin Mocanu, Antonio Liotta
Unsupervised deep learning for real-time assessment of video streaming services. Multim. Tools Appl. 76 (21) (2017)
Decebal Constantin Mocanu, Elena Mocanu, Peter Stone, Phuong H. Nguyen, Madeleine Gibescu, Antonio Liotta
Evolutionary Training of Sparse Artificial Neural Networks: A Network Science Perspective. CoRR (2017)
Decebal Constantin Mocanu, Haitham Bou-Ammar, Luis Puig, Eric Eaton, Antonio Liotta
Estimating 3D trajectories from 2D projections via disjunctive factored four-way conditional restricted Boltzmann machines. Pattern Recognit. 69 (2017)
Elena Mocanu, Decebal Constantin Mocanu, Phuong H. Nguyen, Antonio Liotta, Michael E. Webber, Madeleine Gibescu, Johannes G. Slootweg
On-line Building Energy Optimization using Deep Reinforcement Learning. CoRR (2017)
Maria Torres Vega, Decebal Constantin Mocanu, Antonio Liotta
Predictive No-Reference Assessment of Video Quality. CoRR (2016)
Decebal Constantin Mocanu, Elena Mocanu, Phuong H. Nguyen, Madeleine Gibescu, Antonio Liotta
A topological insight into restricted Boltzmann machines. Mach. Learn. 104 (2-3) (2016)
Kathrin Borchert, Matthias Hirth, Thomas Zinner, Decebal Constantin Mocanu
Correlating QoE and Technical Parameters of an SAP System in an Enterprise Environment. QCMan@ITC (2016)
Decebal Constantin Mocanu, Elena Mocanu, Phuong H. Nguyen, Madeleine Gibescu, Antonio Liotta
A topological insight into restricted Boltzmann machines. CoRR (2016)
Decebal Constantin Mocanu, Elena Mocanu, Phuong H. Nguyen, Madeleine Gibescu, Antonio Liotta
Big IoT data mining for real-time energy disaggregation in buildings. SMC (2016)
Michele Chincoli, Aly Aamer Syed, Decebal Constantin Mocanu, Antonio Liotta
Predictive Power Control in Wireless Sensor Networks. IoTDI (2016)
Maria Torres Vega, Vittorio Sguazzo, Decebal Constantin Mocanu, Antonio Liotta
An experimental survey of no-reference video quality assessment methods. Int. J. Pervasive Comput. Commun. 12 (1) (2016)
Decebal Constantin Mocanu
On the Synergy of Network Science and Artificial Intelligence. IJCAI (2016)
Decebal Constantin Mocanu, Haitham Bou-Ammar, Luis Puig, Eric Eaton, Antonio Liotta
Estimating 3D Trajectories from 2D Projections via Disjunctive Factored Four-Way Conditional Restricted Boltzmann Machines. CoRR (2016)
Decebal Constantin Mocanu, Maria Torres Vega, Eric Eaton, Peter Stone, Antonio Liotta
Online Contrastive Divergence with Generative Replay: Experience Replay without Storing Data. CoRR (2016)
Maria Torres Vega, Decebal Constantin Mocanu, Antonio Liotta
A Regression Method for real-time video quality evaluation. MoMM (2016)
Maria Torres Vega, Vittorio Sguazzo, Decebal Constantin Mocanu, Antonio Liotta
Accuracy of No-Reference Quality Metrics in Network-impaired Video Streams. MoMM (2015)
Maria Torres Vega, Emanuele Giordano, Decebal Constantin Mocanu, Dian Tjondronegoro, Antonio Liotta
Cognitive no-reference video quality assessment for mobile streaming services. QoMEX (2015)
Decebal Constantin Mocanu, Georgios Exarchakos, Haitham Bou-Ammar, Antonio Liotta
Reduced reference image quality assessment via Boltzmann Machines. IM (2015)
Decebal Constantin Mocanu, Haitham Bou-Ammar, Dietwig Lowet, Kurt Driessens, Antonio Liotta, Gerhard Weiss, Karl Tuyls
Factored four way conditional restricted Boltzmann machines for activity recognition. Pattern Recognit. Lett. 66 (2015)
Decebal Constantin Mocanu, Jeevan Pokhrel, Juan Pablo Garella, Janne Seppänen, Eirini Liotou, Manish Narwaria
No-reference video quality measurement: added value of machine learning. J. Electronic Imaging 24 (6) (2015)
Maria Torres Vega, Decebal Constantin Mocanu, Rosario Barresi, Giancarlo Fortino, Antonio Liotta
Cognitive streaming on android devices. IM (2015)
Decebal Constantin Mocanu, Maria Torres Vega, Antonio Liotta
Redundancy Reduction in Wireless Sensor Networks via Centrality Metrics. ICDM Workshops (2015)

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Publication Activity (10 Years)

Top Topics

Top Venues

Decebal Constantin Mocanu