| Quick and robust feature selection: the strength of energy-efficient sparse training for autoencoders | 0 | 0.34 | 2022 |
| Superposing many tickets into one: A performance booster for sparse neural network training. | 0 | 0.34 | 2022 |
| Dynamic Sparse Training for Deep Reinforcement Learning. | 0 | 0.34 | 2022 |
| Dynamic Sparse Training for Deep Reinforcement Learning | 0 | 0.34 | 2022 |
| Deep Ensembling with No Overhead for either Training or Testing: The All-Round Blessings of Dynamic Sparsity | 0 | 0.34 | 2022 |
| Situation-Aware Drivable Space Estimation for Automated Driving | 0 | 0.34 | 2022 |
| The Unreasonable Effectiveness of Random Pruning: Return of the Most Naive Baseline for Sparse Training | 0 | 0.34 | 2022 |
| Self-Attention Meta-Learner for Continual Learning | 0 | 0.34 | 2021 |
| Do We Actually Need Dense Over-Parameterization? In-Time Over-Parameterization In Sparse Training | 0 | 0.34 | 2021 |
| Efficient And Effective Training Of Sparse Recurrent Neural Networks | 0 | 0.34 | 2021 |
| Selfish Sparse Rnn Training | 0 | 0.34 | 2021 |
| Sparse Training via Boosting Pruning Plasticity with Neuroregeneration. | 0 | 0.34 | 2021 |
| Evolving Plasticity For Autonomous Learning Under Changing Environmental Conditions | 0 | 0.34 | 2021 |
| Sparse Training Theory for Scalable and Efficient Agents | 0 | 0.34 | 2021 |
| SpaceNet: Make Free Space for Continual Learning | 1 | 0.37 | 2021 |
| A Hybrid Framework Combining Vehicle System Knowledge with Machine Learning Methods for Improved Highway Trajectory Prediction | 0 | 0.34 | 2020 |
| Evolving Plasticity for Autonomous Learning under Changing Environmental Conditions. | 0 | 0.34 | 2019 |
| Learning with delayed synaptic plasticity | 2 | 0.46 | 2019 |
| Sparse Evolutionary Deep Learning With Over One Million Artificial Neurons On Commodity Hardware | 0 | 0.34 | 2019 |
| One-Shot Learning using Mixture of Variational Autoencoders: a Generalization Learning approach. | 0 | 0.34 | 2018 |
| Limited Evaluation Cooperative Co-evolutionary Differential Evolution for Large-scale Neuroevolution. | 3 | 0.39 | 2018 |
| Synopsis of the PhD Thesis - Network Computations in Artificial Intelligence | 1 | 0.35 | 2018 |
| Effect of lossy networks on stereoscopic 3D-video streams | 0 | 0.34 | 2017 |
| Predictive No-Reference Assessment of Video Quality. | 6 | 0.50 | 2017 |
| On-Line Building Energy Optimization Using Deep Reinforcement Learning | 15 | 0.75 | 2017 |
| Deep Learning for Quality Assessment in Live Video Streaming | 11 | 0.66 | 2017 |
| Estimating 3D Trajectories from 2D Projections via Disjunctive Factored Four-Way Conditional Restricted Boltzmann Machines. | 4 | 0.40 | 2017 |
| Unsupervised deep learning for real-time assessment of video streaming services. | 3 | 0.38 | 2017 |
| Evolutionary Training of Sparse Artificial Neural Networks: A Network Science Perspective. | 1 | 0.35 | 2017 |
| On the Synergy of Network Science and Artificial Intelligence. | 0 | 0.34 | 2016 |
| A topological insight into restricted Boltzmann machines. | 11 | 0.54 | 2016 |
| Correlating QoE and Technical Parameters of an SAP System in an Enterprise Environment | 1 | 0.35 | 2016 |
| Predictive Power Control in Wireless Sensor Networks | 2 | 0.37 | 2016 |
| A Regression Method for real-time video quality evaluation. | 2 | 0.42 | 2016 |
| An Experimental Survey Of No-Reference Video Quality Assessment Methods | 8 | 0.58 | 2016 |
| Big Iot Data Mining For Real-Time Energy Disaggregation In Buildings | 0 | 0.34 | 2016 |
| Accuracy of No-Reference Quality Metrics in Network-impaired Video Streams. | 2 | 0.37 | 2015 |
| Factored four way conditional restricted Boltzmann machines for activity recognition | 18 | 0.68 | 2015 |
| Reduced Reference Image Quality Assessment Via Boltzmann Machines | 7 | 0.48 | 2015 |
| Redundancy reduction in wireless sensor networks via centrality metrics | 2 | 0.38 | 2015 |
| No-reference video quality measurement: added value of machine learning | 10 | 0.68 | 2015 |
| Inexpensive user tracking using Boltzmann Machines | 4 | 0.43 | 2014 |
| Node centrality awareness via swarming effects | 5 | 0.43 | 2014 |
| Deep learning for objective quality assessment of 3D images | 16 | 0.61 | 2014 |
| When does lower bitrate give higher quality in modern video services? | 12 | 0.70 | 2014 |
| Instantaneous Video Quality Assessment for lightweight devices | 11 | 0.69 | 2013 |
| Automatically Mapped Transfer between Reinforcement Learning Tasks via Three-Way Restricted Boltzmann Machines. | 5 | 0.43 | 2013 |
