Paper Title Author Names
Scoring anomalies: a M-estimation formulation Stéphan Clémençon, Telecom ParisTech; Jérémie Jakubowicz, Telecom Sud Management
Evidence Estimation for Bayesian Partially Observed MRFs Yutian Chen, UC Irvine; Max Welling, "University of California, Irvine"
High-dimensional Inference via Lipschitz Sparsity-Yielding Regularizers Zheng Pan, Tsinghua Univ.; Changshui Zhang, Tsinghua Univ.
Learning to Top-K Search using Pairwise Comparisons Brian Eriksson, Technicolor
Stochastic blockmodeling of relational event dynamics Christopher DuBois, UC Irvine; Carter Butts, UC Irvine; Padhraic Smyth, University of California Irvine
Unsupervised Link Selection in Networks Quanquan Gu, CS, UIUC; Charu Aggarwal, IBM Research; Jiawei Han, UIUC
Beyond Sentiment: The Manifold of Human Emotions Seungyeon Kim, Georgia Institute of Technolog; Fuxin Li, Georgia Institute of Technology; Guy Lebanon, Georgia Institute of Technology; Irfan Essa, Georgia Institute of Technology
Greedy Bilateral Sketch, Completion \& Smoothing Tianyi Zhou, Universityof Technology Sydney; Dacheng Tao, University of Technology, Sydney
Further Optimal Regret Bounds for Thompson Sampling Shipra Agrawal, MSR India; Navin Goyal, MSR India
Faster Training of Structural SVMs with Diverse M-Best Cutting-Planes Abner Guzman-Rivera, University of Illinois; Pushmeet Kohli, Microsoft Research Cambridge; Dhruv Batra, Virginia Tech
Structural Expectation Propagation (SEP): Bayesian structure learning for networks with latent variables Nevena Lazic, Microsoft Research; Christopher Bishop, ; John Winn,
DYNA-CARE: Dynamic Cardiac Arrest Risk Estimation Joyce Ho, University of Texas at Austin; Yubin Park, University of Texas at Austin; Carlos Carvalho, University of Texas at Austin; Joydeep Ghosh, University of Texas at Austin
Competing with an Infinite Set of Models in Reinforcement Learning Phuong Nguyen, Australian National University; Odalric-Ambrym Maillard, Montanuniversität Leoben; Daniil Ryabko, INRIA, Lille; Ronald Ortner, Montanuniversitaet Leoben
Central Limit Theorems for Conditional Markov Chains Mathieu Sinn, IBM Research; Bei Chen, IBM Research - Ireland
Efficient Variational Inference for Gaussian Process Regression Networks Trung Nguyen, ANU and NICTA; Edwin Bonilla, NICTA and ANU
Active Learning for Interactive Visualization Tomoharu Iwata, University of Cambridge; Neil Houlsby, University of Cambridge; Zoubin Ghahramani, University of Cambridge
ODE parameter inference using adaptive gradient matching with Gaussian processes Frank Dondelinger, Biomathematics and Statistics Scotland; Dirk Husmeier, University of Glasgow; Simon Rogers, University of Glasgow; Maurizio Filippone, University of Glasgow
Exact Learning of Bounded Tree-width Bayesian Networks Janne Korhonen, University of Helsinki; Pekka Parviainen,
Completeness Results for Lifted Variable Elimination Nima Taghipour, KU Leuven; Daan Fierens, KU LEUVEN; Guy Van den Broeck, UCLA; Jesse Davis, KU LEUVEN; Hendrik Blockeel, KU LEUVEN
Fast Near-GRID Gaussian Process Regression Yuancheng Luo, University of Maryland; Ramani Duraiswami, University of Maryland
Convex Collective Matrix Factorization Guillaume Bouchard, "Xerox Research Centre, Europe"; Dawei Yin, Lehigh University; Shengbo Guo, Samsung Research America
Meta-Transportability of Causal Effects: A Formal Approach Elias Bareinboim, UCLA; Judea Pearl, UCLA
Why Steiner-tree type algorithms work for community detection Mung Chiang, Princeton University; Henry Lam, Boston University; Zhenming Liu, Princeton University; Harold Poor, Princeton University
Clustering Oligarchies Margareta Ackerman, Caltech; Shai Ben David, ; David Loker, University of Waterloo; Sivan Sabato, Microsoft Research
Structure Learning of Mixed Graphical Models Jason Lee, Computational Math & Engineeri; Trevor Hastie, Stanford University
A Simple Criterion for Controlling Selection Bias Eunice Yuh-Jie Chen, UCLA; Judea Pearl, UCLA
Clustered Support Vector Machine Quanquan Gu, CS, UIUC; Jiawei Han, UIUC
A Competitive Test for Uniformity of Monotone Distributions Jayadev Acharya, University of California, San Diego; Ashkan Jafarpour, Univ. of California, San Diego; Alon Orlitsky, University of California, San Diego; Ananda Suresh, University of California, San Diego
Deep Gaussian Processes Andreas Damianou, University of Sheffield; Neil Lawrence, University of Sheffield
Permutation estimation and minimax rates of identifiability Olivier Collier, IMAGINE-ENPC / CREST-ENSAE; Arnak Dalalyan, Ecole des Ponts ParisTech
Bayesian Structure Learning for Functional Neuroimaging Oluwasanmi Koyejo, University of Texas at Austin; Mijung Park, UT Austin; Russell Poldrack, University of Texas at Austin; Joydeep Ghosh, University of Texas at Austin; Jonathan Pillow, The University of Texas at Austin
Dual Decomposition for Joint Discrete-Continuous Optimization Christopher Zach, Microsoft Research
Distribution-Free Distribution Regression Barnabas Poczos, Carnegie Mellon University; Aarti Singh, Carnegie Mellon University; Alessandro Rinaldo, Carnegie Mellon University; Larry Wasserman,
A Last-Step Regression Algorithm for Non-Stationary Online Learning Edward Moroshko, Technion; Koby Crammer, Technion University
Efficiently Sampling Probabilistic Programs via Program Analysis Arun Chaganty, ; Aditya Nori, Microsoft Research India; Sriram Rajamani,