AISTATS A

123 papers

YearTitle / Authors
2014A Finite-Sample Generalization Bound for Semiparametric Regression: Partially Linear Models.
Ruitong Huang, Csaba Szepesvári
2014A Gaussian Latent Variable Model for Large Margin Classification of Labeled and Unlabeled Data.
Do-kyum Kim, Matthew F. Der, Lawrence K. Saul
2014A Geometric Algorithm for Scalable Multiple Kernel Learning.
John Moeller, Parasaran Raman, Suresh Venkatasubramanian, Avishek Saha
2014A Level-set Hit-and-run Sampler for Quasi-Concave Distributions.
Shane T. Jensen, Dean P. Foster
2014A New Approach to Probabilistic Programming Inference.
Frank D. Wood, Jan-Willem van de Meent, Vikash Mansinghka
2014A New Perspective on Learning Linear Separators with Large \(L_qL_p\) Margins.
Maria-Florina Balcan, Christopher Berlind
2014A Non-parametric Conditional Factor Regression Model for Multi-Dimensional Input and Response.
Ava Bargi, Richard Yi Da Xu, Zoubin Ghahramani, Massimo Piccardi
2014A Statistical Model for Event Sequence Data.
Kevin Heins, Hal S. Stern
2014A Stepwise uncertainty reduction approach to constrained global optimization.
Victor Picheny
2014Accelerated Stochastic Gradient Method for Composite Regularization.
Wenliang Zhong, James Tin-Yau Kwok
2014Accelerating ABC methods using Gaussian processes.
Richard Wilkinson
2014Active Area Search via Bayesian Quadrature.
Yifei Ma, Roman Garnett, Jeff G. Schneider
2014Active Boundary Annotation using Random MAP Perturbations.
Subhransu Maji, Tamir Hazan, Tommi S. Jaakkola
2014Active Learning for Undirected Graphical Model Selection.
Divyanshu Vats, Robert D. Nowak, Richard G. Baraniuk
2014Adaptive Variable Clustering in Gaussian Graphical Models.
Siqi Sun, Yuancheng Zhu, Jinbo Xu
2014Algebraic Reconstruction Bounds and Explicit Inversion for Phase Retrieval at the Identifiability Threshold.
Franz J. Király, Martin Ehler
2014An Analysis of Active Learning with Uniform Feature Noise.
Aaditya Ramdas, Barnabás Póczos, Aarti Singh, Larry A. Wasserman
2014An Efficient Algorithm for Large Scale Compressive Feature Learning.
Hristo S. Paskov, John C. Mitchell, Trevor J. Hastie
2014An LP for Sequential Learning Under Budgets.
Joseph Wang, Kirill Trapeznikov, Venkatesh Saligrama
2014An inclusion optimal algorithm for chain graph structure learning.
José M. Peña, Dag Sonntag, Jens Dalgaard Nielsen
2014Analysis of Empirical MAP and Empirical Partially Bayes: Can They be Alternatives to Variational Bayes?
Shinichi Nakajima, Masashi Sugiyama
2014Analytic Long-Term Forecasting with Periodic Gaussian Processes.
Nooshin HajiGhassemi, Marc Peter Deisenroth
2014Approximate Slice Sampling for Bayesian Posterior Inference.
Christopher DuBois, Anoop Korattikara Balan, Max Welling, Padhraic Smyth
2014Average Case Analysis of High-Dimensional Block-Sparse Recovery and Regression for Arbitrary Designs.
Waheed U. Bajwa, Marco F. Duarte, A. Robert Calderbank
2014Avoiding pathologies in very deep networks.
David Duvenaud, Oren Rippel, Ryan P. Adams, Zoubin Ghahramani
2014Bat Call Identification with Gaussian Process Multinomial Probit Regression and a Dynamic Time Warping Kernel.
Vassilios Stathopoulos, Veronica Zamora-Gutierrez, Kate E. Jones, Mark A. Girolami
2014Bayesian Logistic Gaussian Process Models for Dynamic Networks.
Daniele Durante, David B. Dunson
2014Bayesian Multi-Scale Optimistic Optimization.
Ziyu Wang, Babak Shakibi, Lin Jin, Nando de Freitas
2014Bayesian Nonparametric Poisson Factorization for Recommendation Systems.
Prem Gopalan, Francisco J. R. Ruiz, Rajesh Ranganath, David M. Blei
2014Bayesian Switching Interaction Analysis Under Uncertainty.
Zoran Dzunic, John W. Fisher III
2014Bias Reduction and Metric Learning for Nearest-Neighbor Estimation of Kullback-Leibler Divergence.
Yung-Kyun Noh, Masashi Sugiyama, Song Liu, Marthinus Christoffel du Plessis, Frank Chongwoo Park, Daniel D. Lee
2014Black Box Variational Inference.
Rajesh Ranganath, Sean Gerrish, David M. Blei
2014Characterizing EVOI-Sufficient k-Response Query Sets in Decision Problems.
Robert Cohn, Satinder Singh, Edmund H. Durfee
2014Class Proportion Estimation with Application to Multiclass Anomaly Rejection.
Tyler Sanderson, Clayton Scott
2014Cluster Canonical Correlation Analysis.
Nikhil Rasiwasia, Dhruv Mahajan, Vijay Mahadevan, Gaurav Aggarwal
2014Collaborative Ranking for Local Preferences.
Berk Kapicioglu, David S. Rosenberg, Robert E. Schapire, Tony Jebara
2014Computational Education using Latent Structured Prediction.
Tanja Käser, Alexander G. Schwing, Tamir Hazan, Markus H. Gross
2014Connected Sub-graph Detection.
Jing Qian, Venkatesh Saligrama, Yuting Chen
2014Context Aware Group Nearest Shrunken Centroids in Large-Scale Genomic Studies.
Juemin Yang, Fang Han, Rafael A. Irizarry, Han Liu
2014Decontamination of Mutually Contaminated Models.
Gilles Blanchard, Clayton Scott
2014Distributed optimization of deeply nested systems.
Miguel Á. Carreira-Perpiñán, Weiran Wang
2014Doubly Aggressive Selective Sampling Algorithms for Classification.
Koby Crammer
2014Dynamic Resource Allocation for Optimizing Population Diffusion.
Shan Xue, Alan Fern, Daniel Sheldon
2014Efficient Algorithms and Error Analysis for the Modified Nystrom Method.
Shusen Wang, Zhihua Zhang
2014Efficient Distributed Topic Modeling with Provable Guarantees.
Weicong Ding, Mohammad H. Rohban, Prakash Ishwar, Venkatesh Saligrama
2014Efficient Inference for Complex Queries on Complex Distributions.
Lili Dworkin, Michael J. Kearns, Lirong Xia
2014Efficient Lifting of MAP LP Relaxations Using k-Locality.
Martin Mladenov, Kristian Kersting, Amir Globerson
2014Efficient Low-Rank Stochastic Gradient Descent Methods for Solving Semidefinite Programs.
Jianhui Chen, Tianbao Yang, Shenghuo Zhu
2014Efficient Transfer Learning Method for Automatic Hyperparameter Tuning.
Dani Yogatama, Gideon Mann
2014Efficiently Enforcing Diversity in Multi-Output Structured Prediction.
Abner Guzmán-Rivera, Pushmeet Kohli, Dhruv Batra, Rob A. Rutenbar
2014Estimating Dependency Structures for non-Gaussian Components with Linear and Energy Correlations.
Hiroaki Sasaki, Michael Gutmann, Hayaru Shouno, Aapo Hyvärinen
2014Expectation Propagation for Likelihoods Depending on an Inner Product of Two Multivariate Random Variables.
Tomi Peltola, Pasi Jylänki, Aki Vehtari
2014Explicit Link Between Periodic Covariance Functions and State Space Models.
Arno Solin, Simo Särkkä
2014Exploiting the Limits of Structure Learning via Inherent Symmetry.
Peng He, Changshui Zhang
2014Fast Distribution To Real Regression.
Junier B. Oliva, Willie Neiswanger, Barnabás Póczos, Jeff G. Schneider, Eric P. Xing
2014FuSSO: Functional Shrinkage and Selection Operator.
Junier B. Oliva, Barnabás Póczos, Timothy D. Verstynen, Aarti Singh, Jeff G. Schneider, Fang-Cheng Yeh, Wen-Yih Isaac Tseng
2014Fugue: Slow-Worker-Agnostic Distributed Learning for Big Models on Big Data.
Abhimanu Kumar, Alex Beutel, Qirong Ho, Eric P. Xing
2014Fully-Automatic Bayesian Piecewise Sparse Linear Models.
Riki Eto, Ryohei Fujimaki, Satoshi Morinaga, Hiroshi Tamano
2014Gaussian Copula Precision Estimation with Missing Values.
Huahua Wang, Farideh Fazayeli, Soumyadeep Chatterjee, Arindam Banerjee
2014Generating Efficient MCMC Kernels from Probabilistic Programs.
Lingfeng Yang, Pat Hanrahan, Noah D. Goodman
2014Global Optimization Methods for Extended Fisher Discriminant Analysis.
Satoru Iwata, Yuji Nakatsukasa, Akiko Takeda
2014Heterogeneous Domain Adaptation for Multiple Classes.
Joey Tianyi Zhou, Ivor W. Tsang, Sinno Jialin Pan, Mingkui Tan
2014High-Dimensional Density Ratio Estimation with Extensions to Approximate Likelihood Computation.
Rafael Izbicki, Ann B. Lee, Chad Schafer
2014Hybrid Discriminative-Generative Approach with Gaussian Processes.
Ricardo Andrade Pacheco, James Hensman, Max Zwiessele, Neil D. Lawrence
2014Improved Bounds for Online Learning Over the Permutahedron and Other Ranking Polytopes.
Nir Ailon
2014In Defense of Minhash over Simhash.
Anshumali Shrivastava, Ping Li
2014Incremental Tree-Based Inference with Dependent Normalized Random Measures.
Juho Lee, Seungjin Choi
2014Information-Theoretic Characterization of Sparse Recovery.
Cem Aksoylar, Venkatesh Saligrama
2014Interpretable Sparse High-Order Boltzmann Machines.
Martin Renqiang Min, Xia Ning, Chao Cheng, Mark Gerstein
2014Joint Structure Learning of Multiple Non-Exchangeable Networks.
Chris J. Oates, Sach Mukherjee
2014Jointly Informative Feature Selection.
Leonidas Lefakis, François Fleuret
2014LAMORE: A Stable, Scalable Approach to Latent Vector Autoregressive Modeling of Categorical Time Series.
Yubin Park, Carlos Carvalho, Joydeep Ghosh
2014Latent Gaussian Models for Topic Modeling.
Changwei Hu, Eunsu Ryu, David E. Carlson, Yingjian Wang, Lawrence Carin
2014Learning Bounded Tree-width Bayesian Networks using Integer Linear Programming.
Pekka Parviainen, Hossein Shahrabi Farahani, Jens Lagergren
2014Learning Heterogeneous Hidden Markov Random Fields.
Jie Liu, Chunming Zhang, Elizabeth S. Burnside, David Page
2014Learning Optimal Bounded Treewidth Bayesian Networks via Maximum Satisfiability.
Jeremias Berg, Matti Järvisalo, Brandon M. Malone
2014Learning Structured Models with the AUC Loss and Its Generalizations.
Nir Rosenfeld, Ofer Meshi, Daniel Tarlow, Amir Globerson
2014Learning and Evaluation in Presence of Non-i.i.d. Label Noise.
Nico Görnitz, Anne Porbadnigk, Alexander Binder, Claudia Sannelli, Mikio L. Braun, Klaus-Robert Müller, Marius Kloft
2014Learning with Maximum A-Posteriori Perturbation Models.
Andreea Gane, Tamir Hazan, Tommi S. Jaakkola
2014Lifted MAP Inference for Markov Logic Networks.
Somdeb Sarkhel, Deepak Venugopal, Parag Singla, Vibhav Gogate
2014Linear-time training of nonlinear low-dimensional embeddings.
Max Vladymyrov, Miguel Á. Carreira-Perpiñán
2014Loopy Belief Propagation in the Presence of Determinism.
David B. Smith, Vibhav Gogate
2014Low-Rank Spectral Learning.
Alex Kulesza, N. Raj Rao, Satinder Singh
2014Mixed Graphical Models via Exponential Families.
Eunho Yang, Yulia Baker, Pradeep Ravikumar, Genevera I. Allen, Zhandong Liu
2014Near Optimal Bayesian Active Learning for Decision Making.
Shervin Javdani, Yuxin Chen, Amin Karbasi, Andreas Krause, Drew Bagnell, Siddhartha S. Srinivasa
2014New Bounds on Compressive Linear Least Squares Regression.
Ata Kabán
2014Non-Asymptotic Analysis of Relational Learning with One Network.
Peng He, Changshui Zhang
2014Nonparametric estimation and testing of exchangeable graph models.
Justin Yang, Christina Han, Edoardo M. Airoldi
2014On Estimating Causal Effects based on Supplemental Variables.
Takahiro Hayashi, Manabu Kuroki
2014On correlation and budget constraints in model-based bandit optimization with application to automatic machine learning.
Matthew W. Hoffman, Bobak Shahriari, Nando de Freitas
2014On the Testability of Models with Missing Data.
Karthika Mohan, Judea Pearl
2014Online Passive-Aggressive Algorithms for Non-Negative Matrix Factorization and Completion.
Mathieu Blondel, Yotaro Kubo, Naonori Ueda
2014Optimality of Thompson Sampling for Gaussian Bandits Depends on Priors.
Junya Honda, Akimichi Takemura
2014PAC-Bayesian Collective Stability.
Ben London, Bert Huang, Ben Taskar, Lise Getoor
2014PAC-Bayesian Theory for Transductive Learning.
Luc Bégin, Pascal Germain, François Laviolette, Jean-Francis Roy
2014Pan-sharpening with a Bayesian nonparametric dictionary learning model.
Xinghao Ding, Yiyong Jiang, Yue Huang, John W. Paisley
2014Path Thresholding: Asymptotically Tuning-Free High-Dimensional Sparse Regression.
Divyanshu Vats, Richard G. Baraniuk
2014Preface.
Samuel Kaski, Jukka Corander
2014Probabilistic Solutions to Differential Equations and their Application to Riemannian Statistics.
Philipp Hennig, Søren Hauberg
2014Proceedings of the Seventeenth International Conference on Artificial Intelligence and Statistics, AISTATS 2014, Reykjavik, Iceland, April 22-25, 2014
2014Random Bayesian networks with bounded indegree.
Eunice Yuh-Jie Chen, Judea Pearl
2014Recovering Distributions from Gaussian RKHS Embeddings.
Motonobu Kanagawa, Kenji Fukumizu
2014Robust Forward Algorithms via PAC-Bayes and Laplace Distributions.
Asaf Noy, Koby Crammer
2014Robust Stochastic Principal Component Analysis.
John Goes, Teng Zhang, Raman Arora, Gilad Lerman
2014Robust learning of inhomogeneous PMMs.
Ralf Eggeling, Teemu Roos, Petri Myllymäki, Ivo Grosse
2014SMERED: A Bayesian Approach to Graphical Record Linkage and De-duplication.
Rebecca C. Steorts, Rob Hall, Stephen E. Fienberg
2014Scalable Collaborative Bayesian Preference Learning.
Mohammad Emtiyaz Khan, Young-Jun Ko, Matthias W. Seeger
2014Scalable Variational Bayesian Matrix Factorization with Side Information.
Yong-Deok Kim, Seungjin Choi
2014Scaling Graph-based Semi Supervised Learning to Large Number of Labels Using Count-Min Sketch.
Partha Pratim Talukdar, William W. Cohen
2014Scaling Nonparametric Bayesian Inference via Subsample-Annealing.
Fritz Obermeyer, Jonathan Glidden, Eric Jonas
2014Selective Sampling with Drift.
Edward Moroshko, Koby Crammer
2014Sequential crowdsourced labeling as an epsilon-greedy exploration in a Markov Decision Process.
Vikas C. Raykar, Priyanka Agrawal
2014Sketching the Support of a Probability Measure.
Joachim Giesen, Sören Laue, Lars Kuehne
2014Sparse Bayesian Variable Selection for the Identification of Antigenic Variability in the Foot-and-Mouth Disease Virus.
Vinny Davies, Richard E. Reeve, William T. Harvey, Francois F. Maree, Dirk Husmeier
2014Sparsity and the truncated \(l^2\)-norm.
Lee H. Dicker
2014Spoofing Large Probability Mass Functions to Improve Sampling Times and Reduce Memory Costs.
Jon Parker, Hans Engler
2014Student-t Processes as Alternatives to Gaussian Processes.
Amar Shah, Andrew Gordon Wilson, Zoubin Ghahramani
2014The Dependent Dirichlet Process Mixture of Objects for Detection-free Tracking and Object Modeling.
Willie Neiswanger, Frank D. Wood, Eric P. Xing
2014Tight Bounds for the Expected Risk of Linear Classifiers and PAC-Bayes Finite-Sample Guarantees.
Jean Honorio, Tommi S. Jaakkola
2014Tilted Variational Bayes.
James Hensman, Max Zwiessele, Neil D. Lawrence
2014To go deep or wide in learning?
Gaurav Pandey, Ambedkar Dukkipati
2014Towards building a Crowd-Sourced Sky Map.
Dustin Lang, David W. Hogg, Bernhard Schölkopf
2014Visual Boundary Prediction: A Deep Neural Prediction Network and Quality Dissection.
Jyri J. Kivinen, Christopher K. I. Williams, Nicolas Heess