Papers
Open Problem: Adversarial Multiarmed Bandits with Limited Advice
Yevgeny Seldin, Koby Crammer, Peter Bartlett
Scoring anomalies: a M-estimation formulation
Stéphan Clémençon, Jérémie Jakubowicz
Greedy Bilateral Sketch, Completion & Smoothing
Tianyi Zhou, Dacheng Tao
Learning Social Infectivity in Sparse Low-rank Networks Using Multi-dimensional Hawkes Processes
Ke Zhou, Hongyuan Zha, Le Song
Dual Decomposition for Joint Discrete-Continuous Optimization
Christopher Zach
Bethe Bounds and Approximating the Global Optimum
Adrian Weller, Tony Jebara
Block Regularized Lasso for Multivariate Multi-Response Linear Regression
Weiguang Wang, Yingbin Liang, Eric Xing
Collapsed Variational Bayesian Inference for Hidden Markov Models
Pengyu Wang, Phil Blunsom
On the Asymptotic Optimality of Maximum Margin Bayesian Networks
Sebastian Tschiatschek, Franz Pernkopf
Supervised Sequential Classification Under Budget Constraints
Kirill Trapeznikov, Venkatesh Saligrama
Completeness Results for Lifted Variable Elimination
Nima Taghipour, Daan Fierens, Guy Van den Broeck et al.
Statistical Tests for Contagion in Observational Social Network Studies
Greg Ver Steeg, Aram Galstyan
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