Papers
Discovering Latent Network Structure in Point Process Data
Scott Linderman, Ryan Adams
Variational Inference for Sequential Distance Dependent Chinese Restaurant Process
Sergey Bartunov, Dmitry Vetrov
Effective Bayesian Modeling of Groups of Related Count Time Series
Nicolas Chapados
Methods of Moments for Learning Stochastic Languages: Unified Presentation and Empirical Comparison
Borja Balle, William Hamilton, Joelle Pineau
Transductive Learning with Multi-class Volume Approximation
Gang Niu, Bo Dai, Christoffel Plessis et al.
High Order Regularization for Semi-Supervised Learning of Structured Output Problems
Yujia Li, Rich Zemel
Randomized Nonlinear Component Analysis
David Lopez-Paz, Suvrit Sra, Alex Smola et al.
Time-Regularized Interrupting Options (TRIO)
Timothy Mann, Daniel Mankowitz, Shie Mannor
Memory and Computation Efficient PCA via Very Sparse Random Projections
Farhad Pourkamali Anaraki, Shannon Hughes
Sample Efficient Reinforcement Learning with Gaussian Processes
Robert Grande, Thomas Walsh, Jonathan How
Stable and Efficient Representation Learning with Nonnegativity Constraints
Tsung-Han Lin, H. T. Kung
Approximate Policy Iteration Schemes: A Comparison
Bruno Scherrer
Active Transfer Learning under Model Shift
Xuezhi Wang, Tzu-Kuo Huang, Jeff Schneider
Robust and Efficient Kernel Hyperparameter Paths with Guarantees
Joachim Giesen, Soeren Laue, Patrick Wieschollek
One Practical Algorithm for Both Stochastic and Adversarial Bandits
Yevgeny Seldin, Aleksandrs Slivkins
Stochastic Backpropagation and Approximate Inference in Deep Generative Models
Danilo Jimenez Rezende, Shakir Mohamed, Daan Wierstra
Learning Latent Variable Gaussian Graphical Models
Zhaoshi Meng, Brian Eriksson, Al Hero
Inferning with High Girth Graphical Models
Uri Heinemann, Amir Globerson
A Convergence Rate Analysis for LogitBoost, MART and Their Variant
Peng Sun, Tong Zhang, Jie Zhou
Deep AutoRegressive Networks
Karol Gregor, Ivo Danihelka, Andriy Mnih et al.
Discrete Chebyshev Classifiers
Elad Eban, Elad Mezuman, Amir Globerson
Learning the Parameters of Determinantal Point Process Kernels
Raja Hafiz Affandi, Emily Fox, Ryan Adams et al.
Affinity Weighted Embedding
Jason Weston, Ron Weiss, Hector Yee
Online Multi-Task Learning for Policy Gradient Methods
Haitham Bou Ammar, Eric Eaton, Paul Ruvolo et al.
Understanding Protein Dynamics with L1-Regularized Reversible Hidden Markov Models
Robert McGibbon, Bharath Ramsundar, Mohammad Sultan et al.