Paper Title	Author Names
On the Asymptotic Optimality of Maximum Margin Bayesian Networks	Sebastian Tschiatschek, TU Graz; Franz Pernkopf, TU Graz
Ultrahigh Dimensional Feature Screening via RKHS Embeddings	Krishnakumar Balasubramanian, Gatech; Bharath Sriperumbudur, Cambridge University ; Guy Lebanon, Georgia Institute of Technology
Data-driven covariate selection for nonparametric estimation of causal effects	Doris Entner, University of Helsinki; Patrik Hoyer, ; Peter Spirtes,
Mixed LICORS: A Nonparametric Algorithm for Predictive State Reconstruction	Georg Goerg, Carnegie Mellon University; Cosma Shalizi, Carnegie Mellon University
Thompson Sampling in Switching Environments with Bayesian Online Change Detection	Joseph Mellor, University of Manchester; Jonathan Shapiro, University of Manchester
Collapsed Variational Bayesian Inference for Hidden Markov Models	Pengyu Wang, University of Oxford; Phil Blunsom, University of Oxford
Supervised Sequential Classification Under Budget Constraints	Kirill Trapeznikov, Boston University; Venkatesh Saligrama, Boston University
Computing the M Most Probable Modes of a Graphical Model	Chao Chen, Rutgers University; Vladimir Kolmogorov, IST Austria; Yan Zhu, Rutgers University; Dimitris Metaxas, Rutgers University; Christoph Lampert, IST Austria
Estimating the Partition Function of Graphical Models Using Langevin Importance Sampling	Jianzhu Ma, TTIC; Jian Peng, ; Sheng Wang, TTIC; Jinbo Xu, TTIC
Random Projections for Support Vector Machines	Saurabh Paul, Rensselaer Polytechnic Inst; Christos Boutsidis, IBM; Malik Magdon-Ismail, ; Petros Drineas, RPI
A unifying representation for a class of dependent random measures	Nicholas Foti, Dartmouth College; Sinead Williamson, Carnegie Mellon University; Daniel Rockmore, Dartmouth College; Joseph Futoma, Dartmouth College
Dynamic Copula Networks for Modeling Real-valued Time Series	Elad Eban, Hebrew University; gideon Rothschild, Hebrew University; Adi Mizrahi, Hebrew University; Israel Nelken, Hebrew University; Gal Elidan, Hebrew University
A Parallel, Block Greedy Method for Sparse Inverse Covariance Estimation for Ultra-high Dimensionsns	Prabhanjan Kambadur, IBM TJ Watson Research Center; Aurelie Lozano,
A recursive estimate for the predictive likelihood in a topic model	James Scott, ; Jason Baldridge, University of Texas at Austin
Nystrom Approximation for Large-Scale Determinantal Processes	Raja Hafiz Affandi, University of Pennsylvania; Emily Fox, ; Ben Taskar, University of Pennsylvania; Alex Kulesza,
A simple sketching algorithm for entropy estimation over streaming data	Ioana Cosma, University of Ottawa; Peter Clifford, University of Oxford
Detecting Activations over Graphs using Spanning Tree Wavelet Bases	James Sharpnack, Carnegie Mellon University; Aarti Singh, Carnegie Mellon University; Akshay Krishnamurthy, CMU
Learning Social Infectivity in Sparse Low-rank Networks Using Multi-dimensional Hawkes Processess	Ke Zhou, Georgia institute of technolog; Le Song, Georgia institute of technology; Hongyuan Zha, Georgia institute of technology
Changepoint Detection over Graphs with the Spectral Scan Statistic	James Sharpnack, Carnegie Mellon University; Aarti Singh, Carnegie Mellon University; Alessandro Rinaldo, Carnegie Mellon University
Statistical Tests for Contagion in Observational Social Network Studies	Greg Ver Steeg, Information Sciences Institute; Aram Galstyan, Information Sciences Institute, USC
Diagnonal Orthant Multinomial Probit Models	James Johndrow, Duke University; Kristian Lum, Virginia Tech; David Dunson, Duke University
Reconstructing ecological networks with hierarchical Bayesian regression and Mondrian processes	Andrej Aderhold, University of St Andrews; Dirk Husmeier, University of Glasgow; V. Anne Smith, University of St Andrews
Bayesian learning of joint distributions of objects	Anjishnu Banerjee, Duke University; Jared Murray, Duke University; David Dunson, Duke University
Consensus Ranking with Signed Permutations	Raman Arora, TTIC; Marina Meila, University of Washington
Sparse Principal Component Analysis for High Dimensional Multivariate Time Series	Zhaoran Wang, Princeton University; Fang Han, Johns Hopkins University; Han Liu,
Texture Modeling with Convolutional Spike-and-Slab RBMs and Deep Extensions	Heng Luo, Université de Montréal; Pierre Luc Carrier, Université de Montréal; Aaron Courville, Université de Montréal; Yoshua Bengio, Université de Montréal
Block Regularized Lasso for Multivariate Multi-Response Linear Regression	Weiguang Wang, Syracuse University; Yingbin Liang, Syracuse University; Eric Xing, Carnegie Mellon University
Predictive Correlation Screening: Application to Two-stage Predictor Design in High Dimension	Hamed Firouzi, University of Michigan; Alfred Hero III, University of Michigan
Distributed Learning of Gaussian Graphical Models via Marginal Likelihoods	Zhaoshi Meng, University of Michigan; Dennis Wei, University of Michigan; Ami Wiesel, The Hebrew University of Jerusalem ; Alfred Hero III, University of Michigan
Dynamic Scaled Sampling for Deterministic Constraints	Lei Li, UC Berkeley; Bharath Ramsundar, Stanford; Stuart Russell, UC Berkeley
Localization and Adaptation in Online Learning	Alexander (Sasha) Rakhlin, University of Pennsylvania; Ohad Shamir, ; Karthik Sridharan, University of Pennsylvania
Recursive Karcher Expectation Estimators And Geometric Law of Large Numbers	Hesamoddin Salehian, University of Florida; Guang Cheng, ; Jeffrey Ho, UFL; Baba Vemuri, University of Florida
Distributed and Adaptive Darting Monte Carlo through Regenerations	Sungjin Ahn, UCI; Yutian Chen, UC Irvine; Max Welling, University of Amsterdam
Uncover Topic-Sensitive Information Diffusion Networks	Nan Du, GATECH; Le Song, Georgia institute of technology; Hyenkyun Woo, ; Hongyuan Zha, Georgia institute of technology
Learning Markov Networks With Arithmetic Circuits	Daniel Lowd, University of Oregon; Amirmohammad Rooshenas, University of Oregon
Bethe Bounds and Approximating the Global Optimum	Adrian Weller, Columbia University; Tony Jebara, Columbia University