Papers
On Sampling from the Gibbs Distribution with Random Maximum A-Posteriori Perturbations
Tamir Hazan, Subhransu Maji, Tommi Jaakkola
On Stochastic Optimal Control and Reinforcement Learning by Approximate Inference (Extended Abstract)
Konrad Rawlik, Marc Toussaint, Sethu Vijayakumar
On the Approximation Ability of Evolutionary Optimization with Application to Minimum Set Cover: Extended Abstract
Yang Yu, Xin Yao, Zhi-Hua Zhou
On the Asymptotic Optimality of Maximum Margin Bayesian Networks
Sebastian Tschiatschek, Franz Pernkopf
On the Complexity and Approximation of Binary Evidence in Lifted Inference
Guy Van den Broeck, Adnan Darwiche
On the Complexity of Global Scheduling Constraints under Structural Restrictions
Geoffrey Chu, Serge Gaspers, Nina Narodytska et al.
On the Complexity of Probabilistic Abstract Argumentation
Bettina Fazzinga, Sergio Flesca, Francesco Parisi
On the Complexity of Trick-Taking Card Games
Édouard Bonnet, Florian Jamain, Abdallah Saffidine
On the Convergence of Maximum Variance Unfolding
Ery Arias-Castro, Bruno Pelletier
On the difficulty of training recurrent neural networks
Razvan Pascanu, Tomas Mikolov, Yoshua Bengio
On the Effectiveness of Using Syntactic and Shallow Semantic Tree Kernels for Automatic Assessment of Essays
Yllias Chali, Sadid A. Hasan
On the Generalization Ability of Online Learning Algorithms for Pairwise Loss Functions
Purushottam Kar, Bharath Sriperumbudur, Prateek Jain et al.
On the importance of initialization and momentum in deep learning
Ilya Sutskever, James Martens, George Dahl et al.
On the Learnability of Shuffle Ideals
Dana Angluin, James Aspnes, Sarah Eisenstat et al.
On the Linear Convergence of the Proximal Gradient Method for Trace Norm Regularization
Ke Hou, Zirui Zhou, Anthony Man-Cho So et al.
On the Mean Curvature Flow on Graphs with Applications in Image and Manifold Processing
Abdallah El Chakik, Abderrahim Elmoataz, Ahcene Sadi
On the Mutual Nearest Neighbors Estimate in Regression
Arnaud Guyader, Nick Hengartner
On the Relationship Between Binary Classification, Bipartite Ranking, and Binary Class Probability Estimation
Harikrishna Narasimhan, Shivani Agarwal
On the Representational Efficiency of Restricted Boltzmann Machines
James Martens, Arkadev Chattopadhya, Toni Pitassi et al.
On the Sample Complexity of Subspace Learning
Alessandro Rudi, Guillermo D Canas, Lorenzo Rosasco
On the Statistical Consistency of Algorithms for Binary Classification under Class Imbalance
Aditya Menon, Harikrishna Narasimhan, Shivani Agarwal et al.
Ontology-Based Data Access with Closed Predicates Is Inherently Intractable (Sometimes)
Carsten Lutz, Inanç Seylan, Frank Wolter