Maria Fonoberova

Publication Activity (10 Years)

Years Active: 2004-2023
Publications (10 Years): 15

Top Topics

Machine Learning

Support Vector Regression

Top Venues

AAAI Spring Symposium: MLPS

Publications

William T. Redman, Dean Huang, Maria Fonoberova, Igor Mezic
Koopman Learning with Episodic Memory. CoRR (2023)
William T. Redman, Juan M. Bello-Rivas, Maria Fonoberova, Ryan Mohr, Ioannis G. Kevrekidis, Igor Mezic
On Equivalent Optimization of Machine Learning Methods. CoRR (2023)
William T. Redman, Maria Fonoberova, Ryan Mohr, Ioannis G. Kevrekidis, Igor Mezic
Algorithmic (Semi-)Conjugacy via Koopman Operator Theory. CDC (2022)
William T. Redman, Maria Fonoberova, Ryan Mohr, Yannis G. Kevrekidis, Igor Mezic
An Operator Theoretic View On Pruning Deep Neural Networks. ICLR (2022)
William T. Redman, Maria Fonoberova, Ryan Mohr, Ioannis G. Kevrekidis, Igor Mezic
Algorithmic (Semi-)Conjugacy via Koopman Operator Theory. CoRR (2022)
Ryan Mohr, Maria Fonoberova, Iva Manojlovic, Aleksandr Andrejcuk, Zlatko Drmac, Yannis Kevrekidis, Igor Mezic
Applications of Koopman Mode Analysis to Neural Networks. AAAI Spring Symposium: MLPS (2021)
Ryan Mohr, Allan M. Avila, Soham Ghosh, Ananta Bhattarai, Muqiao Yang, Xintian Feng, Martin Head-Gordon, Ruslan Salakhutdinov, Maria Fonoberova, Igor Mezic
Combining Programmable Potentials and Neural Networks for Materials Problems. AAAI Spring Symposium: MLPS (2021)
Ryan Mohr, Maria Fonoberova, Zlatko Drmac, Iva Manojlovic, Igor Mezic
Predicting the Critical Number of Layers for Hierarchical Support Vector Regression. Entropy 23 (1) (2021)
William T. Redman, Maria Fonoberova, Ryan Mohr, Ioannis G. Kevrekidis, Igor Mezic
An Operator Theoretic Perspective on Pruning Deep Neural Networks. CoRR (2021)
Allan M. Avila, Maria Fonoberova, João P. Hespanha, Igor Mezic, Daniel Clymer, Jonathan Goldstein, Marco A. Pravia, Daniel Javorsek
Game Balancing using Koopman-based Learning. ACC (2021)
Carl Folkestad, Daniel Pastor, Igor Mezic, Ryan Mohr, Maria Fonoberova, Joel Burdick
Extended Dynamic Mode Decomposition with Learned Koopman Eigenfunctions for Prediction and Control. ACC (2020)
Ryan Mohr, Maria Fonoberova, Zlatko Drmac, Iva Manojlovic, Igor Mezic
Predicting the Critical Number of Layers for Hierarchical Support Vector Regression. CoRR (2020)
Iva Manojlovic, Maria Fonoberova, Ryan Mohr, Aleksandr Andrejcuk, Zlatko Drmac, Yannis Kevrekidis, Igor Mezic
Applications of Koopman Mode Analysis to Neural Networks. CoRR (2020)
Carl Folkestad, Daniel Pastor, Igor Mezic, Ryan Mohr, Maria Fonoberova, Joel Burdick
Extended Dynamic Mode Decomposition with Learned Koopman Eigenfunctions for Prediction and Control. CoRR (2019)
Igor Mezic, Vladimir A. Fonoberov, Maria Fonoberova, Tuhin Sahai
Spectral Complexity of Directed Graphs and Application to Structural Decomposition. Complex. 2019 (2019)
Maria Fonoberova, Vladimir A. Fonoberov, Igor Mezic
Global sensitivity/uncertainty analysis for agent-based models. Reliab. Eng. Syst. Saf. 118 (2013)
Maria Fonoberova, Vladimir A. Fonoberov, Igor Mezic, Jadranka Mezic, P. Jeffrey Brantingham
Nonlinear Dynamics of Crime and Violence in Urban Settings. J. Artif. Soc. Soc. Simul. 15 (1) (2012)
Dmitrii Lozovanu, Maria Fonoberova
Optimal Dynamic Multicommodity Flows in Networks. Electron. Notes Discret. Math. 25 (2006)
Maria Fonoberova, Dmitrii Lozovanu
The minimum cost multicommodity flow problem in dynamic networks and an algorithm for its solving. Comput. Sci. J. Moldova 13 (1) (2005)
Maria Fonoberova, Dmitrii Lozovanu
Game-Theoretic Approach for Solving Multiobjective Flow Problems on Networks. Comput. Sci. J. Moldova 13 (2) (2005)
Maria Fonoberova, Dmitrii Lozovanu
The maximum flow in dynamic networks. Comput. Sci. J. Moldova 12 (3) (2004)