Journal of Computer and System Sciences

By R. Janicki, J. Kleijn, M. Koutny, Lukasz Mikulski. 2017

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In Algorithms & Complexity

Citations in the corpus

Visualisation and 'diagnostic classifiers' reveal how recurrent and recursive neural networks process hierarchical structure (2017, neutral): “As we argue in the full paper, neither theoretical results [Siegelmann and Sontag, 1995], nor handcrafted examples [Gers and Schmidhuber, 2001; Rodriguez, 2001], nor large-scale NLP applications [Sutskever et al.”
Learning Optimal Decision Trees with MaxSAT and its Integration in AdaBoost (2020, neutral): “As a typical Boosting method, AdaBoost [Freund and Schapire, 1997] constructs T learners in a sequence of T iterations.”
Self-Paced Boost Learning for Classification (2016, methodology): “Examples of boosting methods include Adaboost [Freund and Schapire, 1997], SoftBoost [Rätsch et al., 2007], TotalBoost [Warmuth et al., 2006], LPBoost [Demiriz et al., 2002], Logit- Boost [Friedman et al., 2000], and MadaBoost [Domingo and Watanabe, 2000].”
Visualisation and 'Diagnostic Classifiers' Reveal how Recurrent and Recursive Neural Networks Process Hierarchical Structure (Extended Abstract) (2018, unknown): “As we argue in the full paper, neither theoretical results [Siegelmann and Sontag, 1995], nor handcrafted examples [Gers and Schmidhuber, 2001; Rodriguez, 2001], nor large-scale NLP applications [Sutskever et al.”
Count-Based Exploration in Feature Space for Reinforcement Learning (2017, methodology): “In the MDP setting, the tabular OFU algorithm most closely resembling our method is Model-Based Interval Estimation with Exploration Bonuses (MBIE-EB) [Strehl and Littman, 2008].”
Coupling proofs are probabilistic product programs (2016, methodology): “By applying Theorem 10 to this random walk, we ﬁnd that in the product program c 0 , Then, we can conclude by Proposition 9.”