Proceedings of the 25th international conference on Machine learning

By William W. Cohen, Andrew McCallum, Sam T. Roweis. 2008

172 citations recorded by the source corpus.

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Citations in the corpus

Pretraining Deep Actor-Critic Reinforcement Learning Algorithms With Expert Demonstrations (2018, methodology): “Apprenticeship learning inspired many similar algorithms ([Syed and Schapire, 2008], [Syed et al., 2008], [Piot et al.”
Counterfactual States for Atari Agents via Generative Deep Learning (2019, background): “The majority of these techniques provide explanations as to why the agent chose a particular action (e.g. [Greydanus et al. , 2018]).”
Imaging Time-Series to Improve Classification and Imputation (2015, background): “Along with the success of unsupervised pretraining applied in deep learning, others are studying unsupervised learning algorithms for generative models, such as Deep Belief Networks (DBN) and Denoised Auto-encoders (DA) [Hinton et al., 2006; Vincent et al., 2008].”
Sampling with Minimum Sum of Squared Similarities for Nystrom-Based Large Scale Spectral Clustering (2015, methodology): “…subsampling percentages, γ = 0 and 10, (MSSS and MSSS-10, respectively), and compared its performance to the results of three state-of-the-art approaches described in Section 2: random sampling (RS), kmeans sampling (KS) [Zhang et al., 2008] and minimum similarity sampling (SS) [Zeng et al., 2014].”
Transfer Learning in Multi-Armed Bandits: A Causal Approach (2017, unknown): “[Mehta et al., 2008; 2011] assumed a causal model for the underlying task and performed the transfer of probabilistic knowledge leveraging the invariance encoded in the causal model.”