Papers
A Clockwork RNN
Jan Koutnik, Klaus Greff, Faustino Gomez et al.
Stochastic Variational Inference for Bayesian Time Series Models
Matthew Johnson, Alan Willsky
Learning from Contagion (Without Timestamps)
Kareem Amin, Hoda Heidari, Michael Kearns
Robust Distance Metric Learning via Simultaneous L1-Norm Minimization and Maximization
Hua Wang, Feiping Nie, Heng Huang
Saddle Points and Accelerated Perceptron Algorithms
Adams Wei Yu, Fatma Kilinc-Karzan, Jaime Carbonell
Learning Character-level Representations for Part-of-Speech Tagging
Cicero Dos Santos, Bianca Zadrozny
Beta Diffusion Trees
Creighton Heaukulani, David Knowles, Zoubin Ghahramani
Scalable Bayesian Low-Rank Decomposition of Incomplete Multiway Tensors
Piyush Rai, Yingjian Wang, Shengbo Guo et al.
Neural Variational Inference and Learning in Belief Networks
Andriy Mnih, Karol Gregor
Efficient Gradient-Based Inference through Transformations between Bayes Nets and Neural Nets
Diederik Kingma, Max Welling
Multi-period Trading Prediction Markets with Connections to Machine Learning
Jinli Hu, Amos Storkey
Towards End-To-End Speech Recognition with Recurrent Neural Networks
Alex Graves, Navdeep Jaitly
Learning the Irreducible Representations of Commutative Lie Groups
Taco Cohen, Max Welling
Learning Ordered Representations with Nested Dropout
Oren Rippel, Michael Gelbart, Ryan Adams
Active Learning of Parameterized Skills
Bruno Da Silva, George Konidaris, Andrew Barto
Nonnegative Sparse PCA with Provable Guarantees
Megasthenis Asteris, Dimitris Papailiopoulos, Alexandros Dimakis
Learning by Stretching Deep Networks
Gaurav Pandey, Ambedkar Dukkipati
Spectral Regularization for Max-Margin Sequence Tagging
Ariadna Quattoni, Borja Balle, Xavier Carreras et al.
Asynchronous Distributed ADMM for Consensus Optimization
Ruiliang Zhang, James Kwok
A Deep Semi-NMF Model for Learning Hidden Representations
George Trigeorgis, Konstantinos Bousmalis, Stefanos Zafeiriou et al.
Stochastic Gradient Hamiltonian Monte Carlo
Tianqi Chen, Emily Fox, Carlos Guestrin
Input Warping for Bayesian Optimization of Non-Stationary Functions
Jasper Snoek, Kevin Swersky, Rich Zemel et al.
Kernel Adaptive Metropolis-Hastings
Dino Sejdinovic, Heiko Strathmann, Maria Lomeli Garcia et al.
Scalable and Robust Bayesian Inference via the Median Posterior
Stanislav Minsker, Sanvesh Srivastava, Lizhen Lin et al.
Structured Recurrent Temporal Restricted Boltzmann Machines
Roni Mittelman, Benjamin Kuipers, Silvio Savarese et al.