AISTATS 2015

126 papers

A Bayes Consistent 1-NN Classifier Aryeh Kontorovich, Roi Weiss
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A Consistent Method for Graph Based Anomaly Localization Satoshi Hara, Tetsuro Morimura, Toshihiro Takahashi, Hiroki Yanagisawa, Taiji Suzuki
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A Dirichlet Process Mixture Model for Spherical Data Julian Straub, Jason Chang, Oren Freifeld, John W. Fisher Iii
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A Greedy Homotopy Method for Regression with Nonconvex Constraints Fabian L. Wauthier, Peter Donnelly
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A La Carte - Learning Fast Kernels Zichao Yang, Andrew Gordon Wilson, Alexander J. Smola, Le Song
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A Rate of Convergence for Mixture Proportion Estimation, with Application to Learning from Noisy Labels Clayton Scott
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A Scalable Algorithm for Structured Kernel Feature Selection Shaogang Ren, Shuai Huang, John A. Onofrey, Xenios Papademetris, Xiaoning Qian
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A Simple Homotopy Algorithm for Compressive Sensing Lijun Zhang, Tianbao Yang, Rong Jin, Zhi-Hua Zhou
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A Spectral Algorithm for Inference in Hidden Semi-Markov Models Igor Melnyk, Arindam Banerjee
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A Sufficient Statistics Construction of Exponential Family Levy Measure Densities for Nonparametric Conjugate Models Robert Finn, Brian Kulis
A Topic Modeling Approach to Ranking Weicong Ding, Prakash Ishwar, Venkatesh Saligrama
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A Totally Unimodular View of Structured Sparsity Marwa El Halabi, Volkan Cevher
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Accurate and Conservative Estimates of MRF Log-Likelihood Using Reverse Annealing Yuri Burda, Roger B. Grosse, Ruslan Salakhutdinov
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Active Pointillistic Pattern Search Yifei Ma, Danica J. Sutherland, Roman Garnett, Jeff G. Schneider
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Averaged Least-Mean-Squares: Bias-Variance Trade-Offs and Optimal Sampling Distributions Alexandre Défossez, Francis R. Bach
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Back to the past: Source Identification in Diffusion Networks from Partially Observed Cascades Mehrdad Farajtabar, Manuel Gomez-Rodriguez, Mohammad Zamani, Nan Du, Hongyuan Zha, Le Song
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Bayesian Hierarchical Clustering with Exponential Family: Small-Variance Asymptotics and Reducibility Juho Lee, Seungjin Choi
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Calibration of Conditional Composite Likelihood for Bayesian Inference on Gibbs Random Fields Julien Stoehr, Nial Friel
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Column Subset Selection with Missing Data via Active Sampling Yining Wang, Aarti Singh
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Compressed Sensing with Very Sparse Gaussian Random Projections Ping Li, Cun-Hui Zhang
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Computational Complexity of Linear Large Margin Classification with Ramp Loss Søren Frejstrup Maibing, Christian Igel
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Conditional Restricted Boltzmann Machines for Multi-Label Learning with Incomplete Labels Xin Li, Feipeng Zhao, Yuhong Guo
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Consensus Message Passing for Layered Graphical Models Varun Jampani, S. M. Ali Eslami, Daniel Tarlow, Pushmeet Kohli, John M. Winn
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Consistent Collective Matrix Completion Under Joint Low Rank Structure Suriya Gunasekar, Makoto Yamada, Dawei Yin, Yi Chang
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Convex Multi-Task Learning by Clustering Aviad Barzilai, Koby Crammer
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Cross-Domain Recommendation Without Shared Users or Items by Sharing Latent Vector Distributions Tomoharu Iwata, Koh Takeuchi
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DART: Dropouts Meet Multiple Additive Regression Trees Korlakai Vinayak Rashmi, Ran Gilad-Bachrach
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Data Modeling with the Elliptical Gamma Distribution Suvrit Sra, Reshad Hosseini, Lucas Theis, Matthias Bethge
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Deep Exponential Families Rajesh Ranganath, Linpeng Tang, Laurent Charlin, David M. Blei
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Deeply-Supervised Nets Chen-Yu Lee, Saining Xie, Patrick W. Gallagher, Zhengyou Zhang, Zhuowen Tu
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Dimensionality Estimation Without Distances Matthäus Kleindessner, Ulrike von Luxburg
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Direct Density-Derivative Estimation and Its Application in KL-Divergence Approximation Hiroaki Sasaki, Yung-Kyun Noh, Masashi Sugiyama
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Efficient Estimation of Mutual Information for Strongly Dependent Variables Shuyang Gao, Greg Ver Steeg, Aram Galstyan
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Efficient Second-Order Gradient Boosting for Conditional Random Fields Tianqi Chen, Sameer Singh, Ben Taskar, Carlos Guestrin
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Efficient Sparse Clustering of High-Dimensional Non-Spherical Gaussian Mixtures Martin Azizyan, Aarti Singh, Larry A. Wasserman
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Efficient Training of Structured SVMs via Soft Constraints Ofer Meshi, Nathan Srebro, Tamir Hazan
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Estimating the Accuracies of Multiple Classifiers Without Labeled Data Ariel Jaffe, Boaz Nadler, Yuval Kluger
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Estimation from Pairwise Comparisons: Sharp Minimax Bounds with Topology Dependence Nihar B. Shah, Sivaraman Balakrishnan, Joseph K. Bradley, Abhay Parekh, Kannan Ramchandran, Martin J. Wainwright
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Exact Bayesian Learning of Ancestor Relations in Bayesian Networks Yetian Chen, Lingjian Meng, Jin Tian
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Exploiting Symmetries to Construct Efficient MCMC Algorithms with an Application to SLAM Roshan Shariff, András György, Csaba Szepesvári
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Falling Rule Lists Fulton Wang, Cynthia Rudin
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Fast Function to Function Regression Junier B. Oliva, Willie Neiswanger, Barnabás Póczos, Eric P. Xing, Hy Trac, Shirley Ho, Jeff G. Schneider
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Feature Selection for Linear SVM with Provable Guarantees Saurabh Paul, Malik Magdon-Ismail, Petros Drineas
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Filtered Search for Submodular Maximization with Controllable Approximation Bounds Wenlin Chen, Yixin Chen, Kilian Q. Weinberger
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Gamma Processes, Stick-Breaking, and Variational Inference Anirban Roychowdhury, Brian Kulis
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Gaussian Processes for Bayesian Hypothesis Tests on Regression Functions Alessio Benavoli, Francesca Mangili
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Generalized Linear Models for Aggregated Data Avradeep Bhowmik, Joydeep Ghosh, Oluwasanmi Koyejo
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Global Multi-Armed Bandits with Hölder Continuity Onur Atan, Cem Tekin, Mihaela van der Schaar
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Graph Approximation and Clustering on a Budget Ethan Fetaya, Ohad Shamir, Shimon Ullman
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Implementable Confidence Sets in High Dimensional Regression Alexandra Carpentier
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Inference of Cause and Effect with Unsupervised Inverse Regression Eleni Sgouritsa, Dominik Janzing, Philipp Hennig, Bernhard Schölkopf
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Inferring Block Structure of Graphical Models in Exponential Families Siqi Sun, Hai Wang, Jinbo Xu
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Infinite Edge Partition Models for Overlapping Community Detection and Link Prediction Mingyuan Zhou
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Latent Feature Regression for Multivariate Count Data Arto Klami, Abhishek Tripathi, Johannes Sirola, Lauri Väre, Frédéric Roulland
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Learning Deep Sigmoid Belief Networks with Data Augmentation Zhe Gan, Ricardo Henao, David E. Carlson, Lawrence Carin
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Learning Efficient Anomaly Detectors from K-NN Graphs Jonathan Root, Jing Qian, Venkatesh Saligrama
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Learning from Data with Heterogeneous Noise Using SGD Shuang Song, Kamalika Chaudhuri, Anand D. Sarwate
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Learning of Non-Parametric Control Policies with High-Dimensional State Features Herke van Hoof, Jan Peters, Gerhard Neumann
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Learning Where to Sample in Structured Prediction Tianlin Shi, Jacob Steinhardt, Percy Liang
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Low-Rank Spectral Learning with Weighted Loss Functions Alex Kulesza, Nan Jiang, Satinder Singh
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Majorization-Minimization for Manifold Embedding Zhirong Yang, Jaakko Peltonen, Samuel Kaski
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Max-Margin Zero-Shot Learning for Multi-Class Classification Xin Li, Yuhong Guo
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Maximally Informative Hierarchical Representations of High-Dimensional Data Greg Ver Steeg, Aram Galstyan
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Metric Recovery from Directed Unweighted Graphs Tatsunori B. Hashimoto, Yi Sun, Tommi S. Jaakkola
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Minimizing Nonconvex Non-Separable Functions Yaoliang Yu, Xun Zheng, Micol Marchetti-Bowick, Eric P. Xing
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Missing at Random in Graphical Models Jin Tian
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Model Selection for Topic Models via Spectral Decomposition Dehua Cheng, Xinran He, Yan Liu
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Modeling Skill Acquisition over Time with Sequence and Topic Modeling José P. González-Brenes
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Modelling Policies in MDPs in Reproducing Kernel Hilbert Space Guy Lever, Ronnie Stafford
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Multi-Manifold Modeling in Non-Euclidean Spaces Xu Wang, Konstantinos Slavakis, Gilad Lerman
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Near-Optimal Max-Affine Estimators for Convex Regression Gábor Balázs, András György, Csaba Szepesvári
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Non-Uniform Stochastic Average Gradient Method for Training Conditional Random Fields Mark Schmidt, Reza Babanezhad, Mohamed Osama Ahmed, Aaron Defazio, Ann Clifton, Anoop Sarkar
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Nonparametric Bayesian Factor Analysis for Dynamic Count Matrices Ayan Acharya, Joydeep Ghosh, Mingyuan Zhou
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On Anomaly Ranking and Excess-Mass Curves Nicolas Goix, Anne Sabourin, Stéphan Clémençon
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On Approximate Non-Submodular Minimization via Tree-Structured Supermodularity Yoshinobu Kawahara, Rishabh K. Iyer, Jeff A. Bilmes
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On Estimating L22 Divergence Akshay Krishnamurthy, Kirthevasan Kandasamy, Barnabás Póczos, Larry A. Wasserman
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On the High Dimensional Power of a Linear-Time Two Sample Test Under Mean-Shift Alternatives Sashank J. Reddi, Aaditya Ramdas, Barnabás Póczos, Aarti Singh, Larry A. Wasserman
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On Theoretical Properties of Sum-Product Networks Robert Peharz, Sebastian Tschiatschek, Franz Pernkopf, Pedro M. Domingos
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One-Bit Compressed Sensing with the K-Support Norm Sheng Chen, Arindam Banerjee
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Online Optimization : Competing with Dynamic Comparators Ali Jadbabaie, Alexander Rakhlin, Shahin Shahrampour, Karthik Sridharan
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Online Ranking with Top-1 Feedback Sougata Chaudhuri, Ambuj Tewari
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Parameter Estimation of Generalized Linear Models Without Assuming Their Link Function Sreangsu Acharyya, Joydeep Ghosh
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Particle Gibbs for Bayesian Additive Regression Trees Balaji Lakshminarayanan, Daniel M. Roy, Yee Whye Teh
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Particle Gibbs with Ancestor Sampling for Probabilistic Programs Jan-Willem van de Meent, Hongseok Yang, Vikash Mansinghka, Frank D. Wood
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Power-Law Graph Cuts Xiangyang Zhou, Jiaxin Zhang, Brian Kulis
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Predicting Preference Reversals via Gaussian Process Uncertainty Aversion Rikiya Takahashi, Tetsuro Morimura
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Predictive Inverse Optimal Control for Linear-Quadratic-Gaussian Systems Xiangli Chen, Brian D. Ziebart
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Preferential Attachment in Graphs with Affinities Jay Lee, Manzil Zaheer, Stephan Günnemann, Alexander J. Smola
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Preserving Privacy of Continuous High-Dimensional Data with Minimax Filters Jihun Hamm
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Reactive Bandits with Attitude Pedro A. Ortega, Kee-Eung Kim, Daniel D. Lee
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Reliable and Scalable Variational Inference for the Hierarchical Dirichlet Process Michael C. Hughes, Dae Il Kim, Erik B. Sudderth
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Revisiting the Limits of MAP Inference by MWSS on Perfect Graphs Adrian Weller
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Robust Cost Sensitive Support Vector Machine Shuichi Katsumata, Akiko Takeda
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Robust Sketching for Multiple Square-Root LASSO Problems Vu Pham, Laurent El Ghaoui
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Scalable Nonparametric Multiway Data Analysis Shandian Zhe, Zenglin Xu, Xinqi Chu, Yuan (Alan) Qi, Youngja Park
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Scalable Optimization of Randomized Operational Decisions in Adversarial Classification Settings Bo Li, Yevgeniy Vorobeychik
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Scalable Variational Gaussian Process Classification James Hensman, Alexander G. de G. Matthews, Zoubin Ghahramani
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Sensor Selection for Crowdsensing Dynamical Systems François Schnitzler, Jia Yuan Yu, Shie Mannor
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Sequential Kernel Herding: Frank-Wolfe Optimization for Particle Filtering Simon Lacoste-Julien, Fredrik Lindsten, Francis R. Bach
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Similarity Learning for High-Dimensional Sparse Data Kuan Liu, Aurélien Bellet, Fei Sha
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Sparse Dueling Bandits Kevin G. Jamieson, Sumeet Katariya, Atul Deshpande, Robert D. Nowak
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Sparse Solutions to Nonnegative Linear Systems and Applications Aditya Bhaskara, Ananda Theertha Suresh, Morteza Zadimoghaddam
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Sparse Submodular Probabilistic PCA Rajiv Khanna, Joydeep Ghosh, Russell A. Poldrack, Oluwasanmi Koyejo
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Sparsistency of 1-Regularized M-Estimators Yen-Huan Li, Jonathan Scarlett, Pradeep Ravikumar, Volkan Cevher
Spectral Gap Error Bounds for Improving CUR Matrix Decomposition and the Nyström Method David G. Anderson, Simon S. Du, Michael W. Mahoney, Christopher Melgaard, Kunming Wu, Ming Gu
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State Space Methods for Efficient Inference in Student-T Process Regression Arno Solin, Simo Särkkä
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Stochastic Block Transition Models for Dynamic Networks Kevin S. Xu
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Stochastic Spectral Descent for Restricted Boltzmann Machines David E. Carlson, Volkan Cevher, Lawrence Carin
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Stochastic Structured Variational Inference Matthew D. Hoffman, David M. Blei
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Streaming Variational Inference for Bayesian Nonparametric Mixture Models Alex Tank, Nicholas J. Foti, Emily B. Fox
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Submodular Point Processes with Applications to Machine Learning Rishabh K. Iyer, Jeff A. Bilmes
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Symmetric Iterative Proportional Fitting Sven Kurras
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Tensor Factorization via Matrix Factorization Volodymyr Kuleshov, Arun Tejasvi Chaganty, Percy Liang
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The Bayesian Echo Chamber: Modeling Social Influence via Linguistic Accommodation Fangjian Guo, Charles Blundell, Hanna M. Wallach, Katherine A. Heller
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The Log-Shift Penalty for Adaptive Estimation of Multiple Gaussian Graphical Models Yuancheng Zhu, Rina Foygel Barber
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The Loss Surfaces of Multilayer Networks Anna Choromanska, Mikael Henaff, Michaël Mathieu, Gérard Ben Arous, Yann LeCun
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The Security of Latent Dirichlet Allocation Shike Mei, Xiaojin Zhu
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Tight Regret Bounds for Stochastic Combinatorial Semi-Bandits Branislav Kveton, Zheng Wen, Azin Ashkan, Csaba Szepesvári
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Toward Minimax Off-Policy Value Estimation Lihong Li, Rémi Munos, Csaba Szepesvári
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Tradeoffs for Space, Time, Data and Risk in Unsupervised Learning Mario Lucic, Mesrob I. Ohannessian, Amin Karbasi, Andreas Krause
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Trend Filtering on Graphs Yu-Xiang Wang, James Sharpnack, Alexander J. Smola, Ryan J. Tibshirani
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Two-Stage Sampled Learning Theory on Distributions Zoltán Szabó, Arthur Gretton, Barnabás Póczos, Bharath K. Sriperumbudur
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Understanding and Evaluating Sparse Linear Discriminant Analysis Yi Wu, David P. Wipf, Jeong-Min Yun
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Unifying Local Consistency and MAX SAT Relaxations for Scalable Inference with Rounding Guarantees Stephen H. Bach, Bert Huang, Lise Getoor
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Variance Reduction via Antithetic Markov Chains James Neufeld, Dale Schuurmans, Michael H. Bowling
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WASP: Scalable Bayes via Barycenters of Subset Posteriors Sanvesh Srivastava, Volkan Cevher, Quoc Tran-Dinh, David B. Dunson
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