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Toggle navigation. Toggle navigation Toggle navigation Login. Year Toggle Poster Visibility. In Algorithms -- Adversarial Learning. Efficient online learning with kernels for adversarial large scale problems.
In Algorithms -- Bandit Algorithms. In Algorithms -- Clustering. In Algorithms -- Components Analysis e. In Algorithms -- Density Estimation. In Algorithms -- Dynamical Systems. In Algorithms -- Kernel Methods. In Algorithms -- Missing Data. In Algorithms -- Representation Learning. Learning low-dimensional state embeddings and metastable clusters from time series data. In Algorithms -- Similarity and Distance Learning.
Jamaloddin Golestani. In Applications -- Game Playing. In Applications -- Privacy, Anonymity, and Security. Differentially Private Bagging: Improved utility and cheaper privacy than subsample-and-aggregate. In Applications -- Recommender Systems. In Deep Learning -- Deep Autoencoders. Edward Suh. In Deep Learning -- Generative Models. In Deep Learning -- Predictive Models. In Deep Learning -- Recurrent Networks. Non-normal Recurrent Neural Network nnRNN : learning long time dependencies while improving expressivity with transient dynamics.
Reverse engineering recurrent networks for sentiment classification reveals line attractor dynamics. One ticket to win them all: generalizing lottery ticket initializations across datasets and optimizers. In Optimization -- Combinatorial Optimization. In Probabilistic Methods -- Causal Inference.
In Reinforcement Learning and Planning -- Exploration. In Reinforcement Learning and Planning -- Navigation. In Theory -- Computational Complexity. In Theory -- Frequentist Statistics. In Theory -- Hardness of Learning and Approximations. In Theory -- Learning Theory. Globally optimal score-based learning of directed acyclic graphs in high-dimensions. Uniform convergence may be unable to explain generalization in deep learning.