Elena Mocanu

发表

Effectiveness of neural language models for word prediction of textual mammography reports

Mihai David Marin, Elena Mocanu, Christin Seifert, 2020, 2020 IEEE International Conference on Systems, Man, and Cybernetics (SMC).

Big) data analytics in smart grids

Madeleine Gibescu, Elena Mocanu, H. P. Nguyen, 2016 .

Machine learning to estimate energy demands and user behavior related to buildings in the smart grid context

Elena Mocanu, 2015 .

Airport Restroom Cleanliness Prediction Using Real Time User Feedback Data

Christin Seifert, Elena Mocanu, Kilian Ros, 2019, 2019 IEEE 5th International Conference on Collaboration and Internet Computing (CIC).

Collaborative learning for classiﬁcation and prediction of building energy ﬂexibility

Phuong H. Nguyen, Anil Kumar, Elena Mocanu, 2019 .

Deep learning methods for on-line flexibility prediction and optimal resource allocation in smart buildings

J. G. Slootweg, Madeleine Gibescu, Elena Mocanu, 2017 .

Statistical Learning versus Deep Learning: Performance Comparison for Building Energy Prediction Methods

Madeleine Gibescu, Elena Mocanu, Paige A. Mynhoff, 2018 .

Deep learning for estimating building energy consumption

Madeleine Gibescu, Wil L. Kling, Elena Mocanu, 2016 .

Unsupervised energy prediction in a Smart Grid context using reinforcement cross-building transfer learning

Madeleine Gibescu, Elena Mocanu, Hp Phuong Nguyen, 2016 .

Demand forecasting at low aggregation levels using Factored Conditional Restricted Boltzmann Machine

Madeleine Gibescu, Elena Mocanu, Pierre Pinson, 2016, 2016 Power Systems Computation Conference (PSCC).

Inexpensive user tracking using Boltzmann Machines (Type B paper)

Decebal Constantin Mocanu, Zoran Zivkovic, Elena Mocanu, 2015 .

Optimized parameter selection for assessing building energy efficiency

Madeleine Gibescu, Elena Mocanu, Hp Phuong Nguyen, 2014 .

Collaborative learning for classification and prediction of building energy flexibility

Phuong H. Nguyen, Anil Kumar, Elena Mocanu, 2019, 2019 IEEE PES Innovative Smart Grid Technologies Europe (ISGT-Europe).

Inexpensive user tracking using Boltzmann Machines

Haitham Bou-Ammar, Decebal Constantin Mocanu, Antonio Liotta, 2014, 2014 IEEE International Conference on Systems, Man, and Cybernetics (SMC).

Deep reinforcement learning for scheduling

Madeleine Gibescu, Elena Mocanu, H. P. Nguyen, 2018 .

Quick and Robust Feature Selection: the Strength of Energy-efficient Sparse Training for Autoencoders pdf

Raymond Veldhuis, Decebal Constantin Mocanu, Ghada Sokar, 2020, ArXiv.

Deep Learning to estimate building energy demands in the smart grid context

Madeleine Gibescu, Wil L. Kling, Elena Mocanu, 2015 .

Machine learning applied to smart grids

Elena Mocanu, Elena Mocanu, 2017 .

A topological insight into restricted Boltzmann machines

Antonio Liotta, Madeleine Gibescu, Decebal Constantin Mocanu, 2016, Machine Learning.

Deep learning for power system data analysis

Madeleine Gibescu, Elena Mocanu, Hp Phuong Nguyen, 2018 .

Deep Ensembling with No Overhead for either Training or Testing: The All-Round Blessings of Dynamic Sparsity

Mykola Pechenizkiy, Zhangyang Wang, Decebal Constantin Mocanu, 2021 .

Quick and robust feature selection: the strength of energy-efficient sparse training for autoencoders pdf

Mykola Pechenizkiy, Raymond Veldhuis, Decebal Constantin Mocanu, 2020, Machine Learning.

FreeTickets: Accurate, Robust and Efficient Deep Ensemble by Training with Dynamic Sparsity pdf

Mykola Pechenizkiy, Zhangyang Wang, Decebal Constantin Mocanu, 2021, ArXiv.

Sparse Training Theory for Scalable and Efficient Agents

Damien Ernst, Zita A. Vale, Madeleine Gibescu, 2021, AAMAS.

Dynamic Sparse Training for Deep Reinforcement Learning pdf

Mykola Pechenizkiy, Peter Stone, Decebal Constantin Mocanu, 2021, ArXiv.