AISTATS 2012
157 papers
A General Framework for Structured Sparsity via Proximal Optimization
Luca Baldassarre, Jean Morales, Andreas Argyriou, Massimiliano Pontil A Two-Graph Guided Multi-Task Lasso Approach for eQTL Mapping
Xiaohui Chen, Xinghua Shi, Xing Xu, Zhiyong Wang, Ryan Mills, Charles Lee, Jinbo Xu Active Learning from Multiple Knowledge Sources
Yan Yan, Romer Rosales, Glenn Fung, Faisal Farooq, Bharat Rao, Jennifer Dy Adaptive MCMC with Bayesian Optimization
Nimalan Mahendran, Ziyu Wang, Firas Hamze, Nando De Freitas Adaptive Metropolis with Online Relabeling
Remi Bardenet, Olivier Cappe, Gersende Fort, Balazs Kegl Bayesian Classifier Combination
Hyun-Chul Kim, Zoubin Ghahramani Bayesian Group Factor Analysis
Seppo Virtanen, Arto Klami, Suleiman Khan, Samuel Kaski Bayesian Quadrature for Ratios
Michael Osborne, Roman Garnett, Stephen Roberts, Christopher Hart, Suzanne Aigrain, Neale Gibson Beta-Negative Binomial Process and Poisson Factor Analysis
Mingyuan Zhou, Lauren Hannah, David Dunson, Lawrence Carin Beyond Logarithmic Bounds in Online Learning
Francesco Orabona, Nicolo Cesa-Bianchi, Claudio Gentile Classifier Cascade for Minimizing Feature Evaluation Cost
Minmin Chen, Zhixiang Xu, Kilian Weinberger, Olivier Chapelle, Dor Kedem Constrained 1-Spectral Clustering
Syama Sundar Rangapuram, Matthias Hein Contextual Bandit Learning with Predictable Rewards
Alekh Agarwal, Miroslav Dudik, Satyen Kale, John Langford, Robert Schapire Deep Boltzmann Machines as Feed-Forward Hierarchies
Gregoire Montavon, Mikio Braun, Klaus-Robert Muller Deterministic Annealing for Semi-Supervised Structured Output Learning
Paramveer Dhillon, Sathiya Keerthi, Kedar Bellare, Olivier Chapelle, Sundararajan Sellamanickam Efficient Hypergraph Clustering
Marius Leordeanu, Cristian Sminchisescu Exploiting Unrelated Tasks in Multi-Task Learning
Bernardino Romera Paredes, Andreas Argyriou, Nadia Berthouze, Massimiliano Pontil Factorized Diffusion mAP Approximation
Saeed Amizadeh, Hamed Valizadegan, Milos Hauskrecht Gaussian Processes for Time-Marked Time-Series Data
John Cunningham, Zoubin Ghahramani, Carl Rasmussen Hierarchical Relative Entropy Policy Search
Christian Daniel, Gerhard Neumann, Jan Peters High-Dimensional Structured Feature Screening Using Binary Markov Random Fields
Jie Liu, Chunming Zhang, Catherine Mccarty, Peggy Peissig, Elizabeth Burnside, David Page High-Rank Matrix Completion
Brian Eriksson, Laura Balzano, Robert Nowak History-Alignment Models for Bias-Aware Prediction of Virological Response to HIV Combination Therapy
Jasmina Bogojeska, Daniel Stockel, Maurizio Zazzi, Rolf Kaiser, Francesca Incardona, Michal Rosen-Zvi, Thomas Lengauer Information Theoretic Model Validation for Spectral Clustering
Morteza Haghir Chehreghani, Alberto Giovanni Busetto, Joachim M. Buhmann Kernel Topic Models
Philipp Hennig, David Stern, Ralf Herbrich, Thore Graepel Learning from Weak Teachers
Ruth Urner, Shai Ben David, Ohad Shamir Lifted Linear Programming
Martin Mladenov, Babak Ahmadi, Kristian Kersting Lifted Variable Elimination with Arbitrary Constraints
Nima Taghipour, Daan Fierens, Jesse Davis, Hendrik Blockeel Local Anomaly Detection
Venkatesh Saligrama, Manqi Zhao Locality Preserving Feature Learning
Quanquan Gu, Marina Danilevsky, Zhenhui Li, Jiawei Han Max-Margin Min-Entropy Models
Kevin Miller, M. Pawan Kumar, Ben Packer, Danny Goodman, Daphne Koller Minimax Rates for Homology Inference
Sivaraman Balakrishnan, Alesandro Rinaldo, Don Sheehy, Aarti Singh, Larry Wasserman Multi-Armed Bandit Problems with History
Pannagadatta Shivaswamy, Thorsten Joachims Multiple Texture Boltzmann Machines
Jyri Kivinen, Christopher Williams On Bisubmodular Maximization
Ajit Singh, Andrew Guillory, Jeff Bilmes Online Clustering of Processes
Azadeh Khaleghi, Daniil Ryabko, Jeremie Mary, Philippe Preux Online Clustering with Experts
Anna Choromanska, Claire Monteleoni Protocols for Learning Classifiers on Distributed Data
Hal Daume Iii, Jeff Phillips, Avishek Saha, Suresh Venkatasubramanian Regression for Sets of Polynomial Equations
Franz Kiraly, Paul Von Buenau, Jan Muller, Duncan Blythe, Frank Meinecke, Klaus-Robert Muller Sparsistency of the Edge Lasso over Graphs
James Sharpnack, Aarti Singh, Alessandro Rinaldo Statistical Optimization in High Dimensions
Huan Xu, Constantine Caramanis, Shie Mannor Subset Infinite Relational Models
Katsuhiko Ishiguro, Naonori Ueda, Hiroshi Sawada Using More Data to Speed-up Training Time
Shai Shalev-Shwartz, Ohad Shamir, Eran Tromer Variable Selection for Gaussian Graphical Models
Jean Honorio, Dimitris Samaras, Irina Rish, Guillermo Cecchi