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Proceedings of Machine Learning Research

Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research
Proceedings of Machine Learning Research
PMLR · 2026-06-02 · via Proceedings of Machine Learning Research

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Volume 31: Artificial Intelligence and Statistics, 29-1 May 2013, Scottsdale, Arizona, USA

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Editors: Carlos M. Carvalho, Pradeep Ravikumar

[bib][citeproc]

Contents:

  • Part I: Notable Papers
  • Part II: Regular Papers

Filter Authors: Filter Titles:

Part I: Notable Papers

Bayesian learning of joint distributions of objects

; Proceedings of the Sixteenth International Conference on Artificial Intelligence and Statistics, PMLR 31:1-9

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Permutation estimation and minimax rates of identifiability

Olivier Collier, Arnak Dalalyan; Proceedings of the Sixteenth International Conference on Artificial Intelligence and Statistics, PMLR 31:10-19

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A unifying representation for a class of dependent random measures

Nicholas Foti, Joseph Futoma, Daniel Rockmore, Sinead Williamson; Proceedings of the Sixteenth International Conference on Artificial Intelligence and Statistics, PMLR 31:20-28

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Diagonal Orthant Multinomial Probit Models

James Johndrow, David Dunson, Kristian Lum; Proceedings of the Sixteenth International Conference on Artificial Intelligence and Statistics, PMLR 31:29-38

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Distributed Learning of Gaussian Graphical Models via Marginal Likelihoods

Zhaoshi Meng, Dennis Wei, Ami Wiesel, Alfred Hero III; Proceedings of the Sixteenth International Conference on Artificial Intelligence and Statistics, PMLR 31:39-47

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Sparse Principal Component Analysis for High Dimensional Multivariate Time Series

Zhaoran Wang, Fang Han, Han Liu; Proceedings of the Sixteenth International Conference on Artificial Intelligence and Statistics, PMLR 31:48-56

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Part II: Regular Papers

A Competitive Test for Uniformity of Monotone Distributions

Jayadev Acharya, Ashkan Jafarpour, Alon Orlitsky, Ananda Suresh; Proceedings of the Sixteenth International Conference on Artificial Intelligence and Statistics, PMLR 31:57-65

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Clustering Oligarchies

Margareta Ackerman, Shai Ben-David, David Loker, Sivan Sabato; Proceedings of the Sixteenth International Conference on Artificial Intelligence and Statistics, PMLR 31:66-74

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Reconstructing ecological networks with hierarchical Bayesian regression and Mondrian processes

Andrej Aderhold, Dirk Husmeier, V. Anne Smith; Proceedings of the Sixteenth International Conference on Artificial Intelligence and Statistics, PMLR 31:75-84

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Nyström Approximation for Large-Scale Determinantal Processes

Raja Hafiz Affandi, Alex Kulesza, Emily Fox, Ben Taskar; Proceedings of the Sixteenth International Conference on Artificial Intelligence and Statistics, PMLR 31:85-98

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Further Optimal Regret Bounds for Thompson Sampling

Shipra Agrawal, Navin Goyal; Proceedings of the Sixteenth International Conference on Artificial Intelligence and Statistics, PMLR 31:99-107

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Distributed and Adaptive Darting Monte Carlo through Regenerations

Sungjin Ahn, Yutian Chen, Max Welling; Proceedings of the Sixteenth International Conference on Artificial Intelligence and Statistics, PMLR 31:108-116

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Consensus Ranking with Signed Permutations

Raman Arora, Marina Meilă; Proceedings of the Sixteenth International Conference on Artificial Intelligence and Statistics, PMLR 31:117-125

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Ultrahigh Dimensional Feature Screening via RKHS Embeddings

Krishnakumar Balasubramanian, Bharath Sriperumbudur, Guy Lebanon; Proceedings of the Sixteenth International Conference on Artificial Intelligence and Statistics, PMLR 31:126-134

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Meta-Transportability of Causal Effects: A Formal Approach

Elias Bareinboim, Judea Pearl; Proceedings of the Sixteenth International Conference on Artificial Intelligence and Statistics, PMLR 31:135-143

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Convex Collective Matrix Factorization

Guillaume Bouchard, Dawei Yin, Shengbo Guo; Proceedings of the Sixteenth International Conference on Artificial Intelligence and Statistics, PMLR 31:144-152

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Efficiently Sampling Probabilistic Programs via Program Analysis

Arun Chaganty, Aditya Nori, Sriram Rajamani; Proceedings of the Sixteenth International Conference on Artificial Intelligence and Statistics, PMLR 31:153-160

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Computing the M Most Probable Modes of a Graphical Model

Chao Chen, Vladimir Kolmogorov, Yan Zhu, Dimitris Metaxas, Christoph Lampert; Proceedings of the Sixteenth International Conference on Artificial Intelligence and Statistics, PMLR 31:161-169

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A simple criterion for controlling selection bias

Eunice Yuh-Jie Chen, Judea Pearl; Proceedings of the Sixteenth International Conference on Artificial Intelligence and Statistics, PMLR 31:170-177

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Evidence Estimation for Bayesian Partially Observed MRFs

Yutian Chen, Max Welling; Proceedings of the Sixteenth International Conference on Artificial Intelligence and Statistics, PMLR 31:178-186

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Why Steiner-tree type algorithms work for community detection

Mung Chiang, Henry Lam, Zhenming Liu, Vincent Poor; Proceedings of the Sixteenth International Conference on Artificial Intelligence and Statistics, PMLR 31:187-195

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A simple sketching algorithm for entropy estimation over streaming data

Peter Clifford, Ioana Cosma; Proceedings of the Sixteenth International Conference on Artificial Intelligence and Statistics, PMLR 31:196-206

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Deep Gaussian Processes

Andreas Damianou, Neil D. Lawrence; Proceedings of the Sixteenth International Conference on Artificial Intelligence and Statistics, PMLR 31:207-215

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ODE parameter inference using adaptive gradient matching with Gaussian processes

Frank Dondelinger, Dirk Husmeier, Simon Rogers, Maurizio Filippone; Proceedings of the Sixteenth International Conference on Artificial Intelligence and Statistics, PMLR 31:216-228

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Uncover Topic-Sensitive Information Diffusion Networks

Nan Du, Le Song, Hyenkyun Woo, Hongyuan Zha; Proceedings of the Sixteenth International Conference on Artificial Intelligence and Statistics, PMLR 31:229-237

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Stochastic blockmodeling of relational event dynamics

Christopher DuBois, Carter Butts, Padhraic Smyth; Proceedings of the Sixteenth International Conference on Artificial Intelligence and Statistics, PMLR 31:238-246

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Dynamic Copula Networks for Modeling Real-valued Time Series

Elad Eban, Gideon Rothschild, Adi Mizrahi, Israel Nelken, Gal Elidan; Proceedings of the Sixteenth International Conference on Artificial Intelligence and Statistics, PMLR 31:247-255

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Data-driven covariate selection for nonparametric estimation of causal effects

Doris Entner, Patrik Hoyer, Peter Spirtes; Proceedings of the Sixteenth International Conference on Artificial Intelligence and Statistics, PMLR 31:256-264

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Learning to Top-K Search using Pairwise Comparisons

Brian Eriksson; Proceedings of the Sixteenth International Conference on Artificial Intelligence and Statistics, PMLR 31:265-273

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Predictive Correlation Screening: Application to Two-stage Predictor Design in High Dimension

Hamed Firouzi, Bala Rajaratnam, Alfred Hero III; Proceedings of the Sixteenth International Conference on Artificial Intelligence and Statistics, PMLR 31:274-288

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Mixed LICORS: A Nonparametric Algorithm for Predictive State Reconstruction

Georg Goerg, Cosma Shalizi; Proceedings of the Sixteenth International Conference on Artificial Intelligence and Statistics, PMLR 31:289-297

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Unsupervised Link Selection in Networks

Quanquan Gu, Charu Aggarwal, Jiawei Han; Proceedings of the Sixteenth International Conference on Artificial Intelligence and Statistics, PMLR 31:298-306

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Clustered Support Vector Machines

Quanquan Gu, Jiawei Han; Proceedings of the Sixteenth International Conference on Artificial Intelligence and Statistics, PMLR 31:307-315

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DivMCuts: Faster Training of Structural SVMs with Diverse M-Best Cutting-Planes

Abner Guzman-Rivera, Pushmeet Kohli, Dhruv Batra; Proceedings of the Sixteenth International Conference on Artificial Intelligence and Statistics, PMLR 31:316-324

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Recursive Karcher Expectation Estimators And Geometric Law of Large Numbers

Jeffrey Ho, Guang Cheng, Hesamoddin Salehian, Baba Vemuri; Proceedings of the Sixteenth International Conference on Artificial Intelligence and Statistics, PMLR 31:325-332

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DYNACARE: Dynamic Cardiac Arrest Risk Estimation

Joyce Ho, Yubin Park, Carlos Carvalho, Joydeep Ghosh; Proceedings of the Sixteenth International Conference on Artificial Intelligence and Statistics, PMLR 31:333-341

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Active Learning for Interactive Visualization

Tomoharu Iwata, Neil Houlsby, Zoubin Ghahramani; Proceedings of the Sixteenth International Conference on Artificial Intelligence and Statistics, PMLR 31:342-350

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A Parallel, Block Greedy Method for Sparse Inverse Covariance Estimation for Ultra-high Dimensions

Prabhanjan Kambadur, Aurelie Lozano; Proceedings of the Sixteenth International Conference on Artificial Intelligence and Statistics, PMLR 31:351-359

[abs][Download PDF][Supplementary Material]

Beyond Sentiment: The Manifold of Human Emotions

Seungyeon Kim, Fuxin Li, Guy Lebanon, Irfan Essa; Proceedings of the Sixteenth International Conference on Artificial Intelligence and Statistics, PMLR 31:360-369

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Exact Learning of Bounded Tree-width Bayesian Networks

Janne Korhonen, Pekka Parviainen; Proceedings of the Sixteenth International Conference on Artificial Intelligence and Statistics, PMLR 31:370-378

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Structural Expectation Propagation (SEP): Bayesian structure learning for networks with latent variables

Nevena Lazic, Christopher Bishop, John Winn; Proceedings of the Sixteenth International Conference on Artificial Intelligence and Statistics, PMLR 31:379-387

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Structure Learning of Mixed Graphical Models

Jason Lee, Trevor Hastie; Proceedings of the Sixteenth International Conference on Artificial Intelligence and Statistics, PMLR 31:388-396

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Dynamic Scaled Sampling for Deterministic Constraints

Lei Li, Bharath Ramsundar, Stuart Russell; Proceedings of the Sixteenth International Conference on Artificial Intelligence and Statistics, PMLR 31:397-405

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Learning Markov Networks With Arithmetic Circuits

Daniel Lowd, Amirmohammad Rooshenas; Proceedings of the Sixteenth International Conference on Artificial Intelligence and Statistics, PMLR 31:406-414

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Texture Modeling with Convolutional Spike-and-Slab RBMs and Deep Extensions

Heng Luo, Pierre Luc Carrier, Aaron Courville, Yoshua Bengio; Proceedings of the Sixteenth International Conference on Artificial Intelligence and Statistics, PMLR 31:415-423

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Fast Near-GRID Gaussian Process Regression

Yuancheng Luo, Ramani Duraiswami; Proceedings of the Sixteenth International Conference on Artificial Intelligence and Statistics, PMLR 31:424-432

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Estimating the Partition Function of Graphical Models Using Langevin Importance Sampling

Jianzhu Ma, Jian Peng, Sheng Wang, Jinbo Xu; Proceedings of the Sixteenth International Conference on Artificial Intelligence and Statistics, PMLR 31:433-441

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Thompson Sampling in Switching Environments with Bayesian Online Change Detection

Joseph Mellor, Jonathan Shapiro; Proceedings of the Sixteenth International Conference on Artificial Intelligence and Statistics, PMLR 31:442-450

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A Last-Step Regression Algorithm for Non-Stationary Online Learning

Edward Moroshko, Koby Crammer; Proceedings of the Sixteenth International Conference on Artificial Intelligence and Statistics, PMLR 31:451-462

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Competing with an Infinite Set of Models in Reinforcement Learning

Phuong Nguyen, Odalric-Ambrym Maillard, Daniil Ryabko, Ronald Ortner; Proceedings of the Sixteenth International Conference on Artificial Intelligence and Statistics, PMLR 31:463-471

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Efficient Variational Inference for Gaussian Process Regression Networks

Trung Nguyen, Edwin Bonilla; Proceedings of the Sixteenth International Conference on Artificial Intelligence and Statistics, PMLR 31:472-480

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High-dimensional Inference via Lipschitz Sparsity-Yielding Regularizers

Zheng Pan, Changshui Zhang; Proceedings of the Sixteenth International Conference on Artificial Intelligence and Statistics, PMLR 31:481-488

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Bayesian Structure Learning for Functional Neuroimaging

Mijung Park, Oluwasanmi Koyejo, Joydeep Ghosh, Russell Poldrack, Jonathan Pillow; Proceedings of the Sixteenth International Conference on Artificial Intelligence and Statistics, PMLR 31:489-497

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Random Projections for Support Vector Machines

Saurabh Paul, Christos Boutsidis, Malik Magdon-Ismail, Petros Drineas; Proceedings of the Sixteenth International Conference on Artificial Intelligence and Statistics, PMLR 31:498-506

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Distribution-Free Distribution Regression

Barnabas Poczos, Aarti Singh, Alessandro Rinaldo, Larry Wasserman; Proceedings of the Sixteenth International Conference on Artificial Intelligence and Statistics, PMLR 31:507-515

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Localization and Adaptation in Online Learning

Alexander Rakhlin, Ohad Shamir, Karthik Sridharan; Proceedings of the Sixteenth International Conference on Artificial Intelligence and Statistics, PMLR 31:516-526

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A recursive estimate for the predictive likelihood in a topic model

James Scott, Jason Baldridge; Proceedings of the Sixteenth International Conference on Artificial Intelligence and Statistics, PMLR 31:527-535

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Detecting Activations over Graphs using Spanning Tree Wavelet Bases

James Sharpnack, Aarti Singh, Akshay Krishnamurthy; Proceedings of the Sixteenth International Conference on Artificial Intelligence and Statistics, PMLR 31:536-544

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Changepoint Detection over Graphs with the Spectral Scan Statistic

James Sharpnack, Aarti Singh, Alessandro Rinaldo; Proceedings of the Sixteenth International Conference on Artificial Intelligence and Statistics, PMLR 31:545-553

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Central Limit Theorems for Conditional Markov Chains

Mathieu Sinn, Bei Chen; Proceedings of the Sixteenth International Conference on Artificial Intelligence and Statistics, PMLR 31:554-562

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Statistical Tests for Contagion in Observational Social Network Studies

Greg Ver Steeg, Aram Galstyan; Proceedings of the Sixteenth International Conference on Artificial Intelligence and Statistics, PMLR 31:563-571

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Completeness Results for Lifted Variable Elimination

Nima Taghipour, Daan Fierens, Guy Van den Broeck, Jesse Davis, Hendrik Blockeel; Proceedings of the Sixteenth International Conference on Artificial Intelligence and Statistics, PMLR 31:572-580

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Supervised Sequential Classification Under Budget Constraints

Kirill Trapeznikov, Venkatesh Saligrama; Proceedings of the Sixteenth International Conference on Artificial Intelligence and Statistics, PMLR 31:581-589

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On the Asymptotic Optimality of Maximum Margin Bayesian Networks

Sebastian Tschiatschek, Franz Pernkopf; Proceedings of the Sixteenth International Conference on Artificial Intelligence and Statistics, PMLR 31:590-598

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Collapsed Variational Bayesian Inference for Hidden Markov Models

Pengyu Wang, Phil Blunsom; Proceedings of the Sixteenth International Conference on Artificial Intelligence and Statistics, PMLR 31:599-607

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Block Regularized Lasso for Multivariate Multi-Response Linear Regression

Weiguang Wang, Yingbin Liang, Eric Xing; Proceedings of the Sixteenth International Conference on Artificial Intelligence and Statistics, PMLR 31:608-617

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Bethe Bounds and Approximating the Global Optimum

Adrian Weller, Tony Jebara; Proceedings of the Sixteenth International Conference on Artificial Intelligence and Statistics, PMLR 31:618-631

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Dual Decomposition for Joint Discrete-Continuous Optimization

Christopher Zach; Proceedings of the Sixteenth International Conference on Artificial Intelligence and Statistics, PMLR 31:632-640

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Learning Social Infectivity in Sparse Low-rank Networks Using Multi-dimensional Hawkes Processes

Ke Zhou, Hongyuan Zha, Le Song; Proceedings of the Sixteenth International Conference on Artificial Intelligence and Statistics, PMLR 31:641-649

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Greedy Bilateral Sketch, Completion & Smoothing

Tianyi Zhou, Dacheng Tao; Proceedings of the Sixteenth International Conference on Artificial Intelligence and Statistics, PMLR 31:650-658

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Scoring anomalies: a M-estimation formulation

Stéphan Clémençon, Jérémie Jakubowicz; Proceedings of the Sixteenth International Conference on Artificial Intelligence and Statistics, PMLR 31:659-667

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