Papers
Central Limit Theorems for Conditional Markov Chains
Mathieu Sinn, Bei Chen
Changepoint Detection over Graphs with the Spectral Scan Statistic
James Sharpnack, Aarti Singh, Alessandro Rinaldo
Detecting Activations over Graphs using Spanning Tree Wavelet Bases
James Sharpnack, Aarti Singh, Akshay Krishnamurthy
A recursive estimate for the predictive likelihood in a topic model
James Scott, Jason Baldridge
Localization and Adaptation in Online Learning
Alexander Rakhlin, Ohad Shamir, Karthik Sridharan
Distribution-Free Distribution Regression
Barnabas Poczos, Aarti Singh, Alessandro Rinaldo et al.
Random Projections for Support Vector Machines
Saurabh Paul, Christos Boutsidis, Malik Magdon-Ismail et al.
Bayesian Structure Learning for Functional Neuroimaging
Mijung Park, Oluwasanmi Koyejo, Joydeep Ghosh et al.
High-dimensional Inference via Lipschitz Sparsity-Yielding Regularizers
Zheng Pan, Changshui Zhang
Efficient Variational Inference for Gaussian Process Regression Networks
Trung Nguyen, Edwin Bonilla
Competing with an Infinite Set of Models in Reinforcement Learning
Phuong Nguyen, Odalric-Ambrym Maillard, Daniil Ryabko et al.
A Last-Step Regression Algorithm for Non-Stationary Online Learning
Edward Moroshko, Koby Crammer
Thompson Sampling in Switching Environments with Bayesian Online Change Detection
Joseph Mellor, Jonathan Shapiro
Estimating the Partition Function of Graphical Models Using Langevin Importance Sampling
Jianzhu Ma, Jian Peng, Sheng Wang et al.
Fast Near-GRID Gaussian Process Regression
Yuancheng Luo, Ramani Duraiswami
Texture Modeling with Convolutional Spike-and-Slab RBMs and Deep Extensions
Heng Luo, Pierre Luc Carrier, Aaron Courville et al.
Learning Markov Networks With Arithmetic Circuits
Daniel Lowd, Amirmohammad Rooshenas
Dynamic Scaled Sampling for Deterministic Constraints
Lei Li, Bharath Ramsundar, Stuart Russell
Structure Learning of Mixed Graphical Models
Jason Lee, Trevor Hastie
Structural Expectation Propagation (SEP): Bayesian structure learning for networks with latent variables
Nevena Lazic, Christopher Bishop, John Winn
Exact Learning of Bounded Tree-width Bayesian Networks
Janne Korhonen, Pekka Parviainen
Beyond Sentiment: The Manifold of Human Emotions
Seungyeon Kim, Fuxin Li, Guy Lebanon et al.
A Parallel, Block Greedy Method for Sparse Inverse Covariance Estimation for Ultra-high Dimensions
Prabhanjan Kambadur, Aurelie Lozano
Active Learning for Interactive Visualization
Tomoharu Iwata, Neil Houlsby, Zoubin Ghahramani
DYNACARE: Dynamic Cardiac Arrest Risk Estimation
Joyce Ho, Yubin Park, Carlos Carvalho et al.