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2020 – today
- 2023
[c15]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: 1932-1941- [i12]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 abs/2302.06548 (2023) - [i11]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 abs/2312.04727 (2023) - 2022
- [j4]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): 377-414 (2022) - [c14]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 - [c13]Ghada Sokar, Elena Mocanu, Decebal Constantin Mocanu, Mykola Pechenizkiy, Peter Stone:
Dynamic Sparse Training for Deep Reinforcement Learning. IJCAI 2022: 3437-3443 - [c12]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 - [i10]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 abs/2212.09840 (2022) - 2021
- [c11]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: 34-38 - [i9]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 abs/2103.01636 (2021) - [i8]Ghada Sokar, Elena Mocanu, Decebal Constantin Mocanu, Mykola Pechenizkiy, Peter Stone:
Dynamic Sparse Training for Deep Reinforcement Learning. CoRR abs/2106.04217 (2021) - [i7]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 abs/2106.14568 (2021) - 2020
- [c10]Mihai David Marin, Elena Mocanu, Christin Seifert:
Effectiveness of neural language models for word prediction of textual mammography reports. SMC 2020: 1596-1603 - [i6]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 abs/2012.00560 (2020)
2010 – 2019
- 2019
- [j3]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): 3698-3708 (2019) - [c9]Kilian Ros, Elena Mocanu, Christin Seifert:
Airport Restroom Cleanliness Prediction Using Real Time User Feedback Data. CIC 2019: 1-10 - [c8]Anil Kumar, Elena Mocanu, Muhammad Babar, Phuong H. Nguyen:
Collaborative learning for classification and prediction of building energy flexibility. ISGT Europe 2019: 1-5 - 2018
- [j2]L. A. Hurtado Munoz, Elena Mocanu, Phuong H. Nguyen, Madeleine Gibescu, I. G. Kamphuis:
Enabling Cooperative Behavior for Building Demand Response Based on Extended Joint Action Learning. IEEE Trans. Ind. Informatics 14(1): 127-136 (2018) - [c7]Decebal Constantin Mocanu, Elena Mocanu:
One-Shot Learning using Mixture of Variational Autoencoders: a Generalization Learning approach. AAMAS 2018: 2016-2018 - [i5]Decebal Constantin Mocanu, Elena Mocanu:
One-Shot Learning using Mixture of Variational Autoencoders: a Generalization Learning approach. CoRR abs/1804.07645 (2018) - 2017
- [c6]Nikolaos G. Paterakis, Elena Mocanu, Madeleine Gibescu, Bart Stappers, Walter van Alst:
Deep learning versus traditional machine learning methods for aggregated energy demand prediction. ISGT Europe 2017: 1-6 - [i4]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 abs/1707.04780 (2017) - [i3]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 abs/1707.05878 (2017) - 2016
- [j1]Decebal Constantin Mocanu, Elena Mocanu, Phuong H. Nguyen, Madeleine Gibescu, Antonio Liotta:
A topological insight into restricted Boltzmann machines. Mach. Learn. 104(2-3): 243-270 (2016) - [c5]Elena Mocanu, Phuong H. Nguyen, Madeleine Gibescu, Emil Mahler Larsen, Pierre Pinson:
Demand forecasting at low aggregation levels using Factored Conditional Restricted Boltzmann Machine. PSCC 2016: 1-7 - [c4]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: 3765-3769 - [i2]Decebal Constantin Mocanu, Elena Mocanu, Phuong H. Nguyen, Madeleine Gibescu, Antonio Liotta:
A topological insight into restricted Boltzmann machines. CoRR abs/1604.05978 (2016) - [i1]Elena Mocanu, Phuong H. Nguyen, Madeleine Gibescu:
Energy Disaggregation for Real-Time Building Flexibility Detection. CoRR abs/1605.01939 (2016) - 2015
- [c3]L. A. Hurtado Munoz, Elena Mocanu, Phuong H. Nguyen, Madeleine Gibescu, Wil L. Kling:
Comfort-constrained Demand Flexibility Management for Building Aggregations using a Decentralized Approach. SMARTGREENS 2015: 157-166 - 2014
- [c2]Elena Mocanu, Decebal Constantin Mocanu, Haitham Bou-Ammar, Zoran Zivkovic, Antonio Liotta, Evgueni N. Smirnov:
Inexpensive user tracking using Boltzmann Machines. SMC 2014: 1-6
2000 – 2009
- 2008
- [c1]Elena Mocanu, Paul E. Sterian:
Acquisition and Algorithms for Fluorescence Applications. BIRD 2008: 546-555
Coauthor Index
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