Vitaly Kuznetsov

According to our database1, Vitaly Kuznetsov authored at least 23 papers between 2014 and 2020.

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Bibliography

2020
Discrepancy-Based Theory and Algorithms for Forecasting Non-Stationary Time Series.
Ann. Math. Artif. Intell., 2020

2019
AdaNet: A Scalable and Flexible Framework for Automatically Learning Ensembles.
CoRR, 2019

Online Non-Additive Path Learning under Full and Partial Information.
Proceedings of the Algorithmic Learning Theory, 2019

Foundations of Sequence-to-Sequence Modeling for Time Series.
Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

2018
Theory and Algorithms for Forecasting Time Series.
CoRR, 2018

Efficient Gradient Computation for Structured Output Learning with Rational and Tropical Losses.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

2017
Generalization bounds for non-stationary mixing processes.
Mach. Learn., 2017

Discriminative State Space Models.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

AdaNet: Adaptive Structural Learning of Artificial Neural Networks.
Proceedings of the 34th International Conference on Machine Learning, 2017

2016
Structured Prediction Theory and Voted Risk Minimization.
CoRR, 2016

Structured Prediction Theory Based on Factor Graph Complexity.
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Learning N-Gram Language Models from Uncertain Data.
Proceedings of the Interspeech 2016, 2016

Time series prediction and online learning.
Proceedings of the 29th Conference on Learning Theory, 2016

2015
Voted Kernel Regularization.
CoRR, 2015

Learning Theory and Algorithms for Forecasting Non-stationary Time Series.
Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

Kernel Extraction via Voted Risk Minimization.
Proceedings of the 1st Workshop on Feature Extraction: Modern Questions and Challenges, 2015

Structural Maxent Models.
Proceedings of the 32nd International Conference on Machine Learning, 2015

On-Line Learning Algorithms for Path Experts with Non-Additive Losses.
Proceedings of The 28th Conference on Learning Theory, 2015

2014
Nested Recursions, Simultaneous Parameters and Tree Superpositions.
Electron. J. Comb., 2014

Multi-Class Deep Boosting.
Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

Ensemble Methods for Structured Prediction.
Proceedings of the 31th International Conference on Machine Learning, 2014

Generalization Bounds for Time Series Prediction with Non-stationary Processes.
Proceedings of the Algorithmic Learning Theory - 25th International Conference, 2014

Learning Ensembles of Structured Prediction Rules.
Proceedings of the 52nd Annual Meeting of the Association for Computational Linguistics, 2014


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