AISTATS 2007

85 papers

(Approximate) Subgradient Methods for Structured Prediction Nathan D. Ratliff, J. Andrew Bagnell, Martin A. Zinkevich

A Bayesian Divergence Prior for Classiffier Adaptation Xiao Li, Jeff Bilmes

A Boosting Algorithm for Label Covering in Multilabel Problems Yonatan Amit, Ofer Dekel, Yoram Singer

A Fast Algorithm for Learning Large Scale Preference Relations Vikas C. Raykar, Ramani Duraiswami, Balaji Krishnapuram

A Fast Bundle-Based Anytime Algorithm for Poker and Other Convex Games H. Brendan McMahan, Geoffrey J. Gordon

A Framework for Probability Density Estimation John Shawe-Taylor, Alex Dolia

A Hybrid Pareto Model for Conditional Density Estimation of Asymmetric Fat-Tail Data Julie Carreau, Yoshua Bengio

A Latent Space Approach to Dynamic Embedding of Co-Occurrence Data Purnamrita Sarkar, Sajid M. Siddiqi, Geogrey J. Gordon

A Nonparametric Bayesian Approach to Modeling Overlapping Clusters Katherine A. Heller, Zoubin Ghahramani

A Stochastic Quasi-Newton Method for Online Convex Optimization Nicol N. Schraudolph, Jin Yu, Simon Günter

A Unified Algorithmic Approach for Efficient Online Label Ranking Shai Shalev-Shwartz, Yoram Singer

A Unified Energy-Based Framework for Unsupervised Learning Marc’Aurelio Ranzato, Y-Lan Boureau, Sumit Chopra, Yann LeCun

AClass: A Simple, Online, Parallelizable Algorithm for Probabilistic Classification Vikash K. Mansinghka, Daniel M. Roy, Ryan Rifkin, Josh Tenenbaum

An Improved 1-Norm SVM for Simultaneous Classification and Variable Selection Hui Zou

Analogical Reasoning with Relational Bayesian Sets Ricardo Silva, Katherine A. Heller, Zoubin Ghahramani

Approximate Counting of Graphical Models via MCMC Jose M. Peña

Approximate Inference Using Conditional Entropy Decompositions Amir Globerson, Tommi Jaakkola

Bayesian Inference and Optimal Design in the Sparse Linear Model Matthias Seeger, Florian Steinke, Koji Tsuda

Continuous Neural Networks Nicolas Le Roux, Yoshua Bengio

Deterministic Annealing for Multiple-Instance Learning Peter V. Gehler, Olivier Chapelle

Dissimilarity in Graph-Based Semi-Supervised Classification Andrew B. Goldberg, Xiaojin Zhu, Stephen Wright

Dynamic Factorization Tests: Applications to Multi-Modal Data Association Michael R. Siracusa, John W. Fisher Iii

Efficient Active Learning with Generalized Linear Models Jeremy Lewi, Robert Butera, Liam Paninski

Efficient Large Margin Semisupervised Learning Junhui Wang

Ellipsoidal Machines Pannagadatta K. Shivaswamy, Tony Jebara

Emerge and Spread Models and Word Burstiness Peter Sunehag

Exact Bayesian Structure Learning from Uncertain Interventions Daniel Eaton, Kevin Murphy

Fast Kernel ICA Using an Approximate Newton Method Hao Shen, Stefanie Jegelka, Arthur Gretton

Fast Low-Rank Semidefinite Programming for Embedding and Clustering Brian Kulis, Arun C. Surendran, John C. Platt

Fast Mean Shift with Accurate and Stable Convergence Ping Wang, Dongryeol Lee, Alexander Gray, James M. Rehg

Fast Search for Dirichlet Process Mixture Models Hal Daume Iii

Fast State Discovery for HMM Model Selection and Learning Sajid M. Siddiqi, Geogrey J. Gordon, Andrew W. Moore

Fisher Consistency of Multicategory Support Vector Machines Yufeng Liu

Generalized Darting Monte Carlo Cristian Sminchisescu, Max Welling

Generalized Do-Calculus with Testable Causal Assumptions Jiji Zhang

Generalized Non-Metric Multidimensional Scaling Sameer Agarwal, Josh Wills, Lawrence Cayton, Gert Lanckriet, David Kriegman, Serge Belongie

Hidden Topic Markov Models Amit Gruber, Yair Weiss, Michal Rosen-Zvi

Hierarchical Beta Processes and the Indian Buffet Process Romain Thibaux, Michael I. Jordan

How Powerful Can Any Regression Learning Procedure Be? Yuhong Yang

Importance Sampling for General Hybrid Bayesian Networks Changhe Yuan, Marek J. Druzdzel

Incorporating Prior Knowledge on Features into Learning Eyal Krupka, Naftali Tishby

Inductive Transfer for Bayesian Network Structure Learning Alexandru Niculescu-Mizil, Rich Caruana

Information Retrieval by Inferring Implicit Queries from Eye Movements David R. Hardoon, John Shawe-Taylor, Antti Ajanki, Kai Puolamäki, Samuel Kaski

Kernel Multi-Task Learning Using Task-Specific Features Edwin V. Bonilla, Felix V. Agakov, Christopher K. I. Williams

Large-Margin Classification in Banach Spaces Ricky Der, Daniel Lee

Learning a Nonlinear Embedding by Preserving Class Neighbourhood Structure Ruslan Salakhutdinov, Geoff Hinton

Learning A* Underestimates : Using Inference to Guide Inference Gregory Druck, Mukund Narasimhan, Paul Viola

Learning for Larger Datasets with the Gaussian Process Latent Variable Model Neil D. Lawrence

Learning Markov Structure by Maximum Entropy Relaxation Jason K. Johnson, Venkat Chandrasekaran, Alan S. Willsky

Learning Multilevel Distributed Representations for High-Dimensional Sequences Ilya Sutskever, Geoffrey Hinton

Learning Nearest-Neighbor Quantizers from Labeled Data by Information Loss Minimization Svetlana Lazebnik, Maxim Raginsky

Local and Global Sparse Gaussian Process Approximations Edward Snelson, Zoubin Ghahramani

Loop Corrected Belief Propagation Joris Mooij, Bastian Wemmenhove, Bert Kappen, Tommaso Rizzo

Loopy Belief Propagation for Bipartite Maximum Weight B-Matching Bert Huang, Tony Jebara

Margin Based Transductive Graph Cuts Using Linear Programming K. Pelckmans, J. Shawe-Taylor, J.A.K. Suykens, B. De Moor

Maximum Entropy Correlated Equilibria Luis E. Ortiz, Robert E. Schapire, Sham M. Kakade

MDL Histogram Density Estimation Petri Kontkanen, Petri Myllymäki

Memory-Effcient Orthogonal Least Squares Kernel Density Estimation Using Enhanced Empirical Cumulative Distribution Functions Martin Schaffoner, Edin Andelic, Marcel Katz, Sven E. Krüger, Andreas Wendemuth

Metric Learning for Kernel Regression Kilian Q. Weinberger, Gerald Tesauro

Minimum Volume Embedding Blake Shaw, Tony Jebara

Mixture of Watson Distributions: A Generative Model for Hyperspherical Embeddings Avleen S. Bijral, Markus Breitenbach, Greg Grudic

Multi-Object Tracking with Representations of the Symmetric Group Risi Kondor, Andrew Howard, Tony Jebara

Nonlinear Dimensionality Reduction as Information Retrieval Jarkko Venna, Samuel Kaski

Nonnegative Garrote Component Selection in Functional ANOVA Models Ming Yuan

Online Learning of Search Heuristics Michael Fink

Performance Guarantees for Information Theoretic Active Inference Jason L. Williams, John W. Fisher Iii, Alan S. Willsky

Policy-Gradients for PSRs and POMDPs Douglas Aberdeen, Olivier Buffet, Owen Thomas

Predictive Discretization During Model Selection Harald Steck, Tommi S. Jaakkola

Recall Systems: Effcient Learning and Use of Category Indices Omid Madani, Wiley Greiner, David Kempe, Mohammad R. Salavatipour

SampleSearch: A Scheme That Searches for Consistent Samples Vibhav Gogate, Rina Dechter

Seeking the Truly Correlated Topic Posterior - On Tight Approximate Inference of Logistic-Normal Admixture Model Amr Ahmed, Eric P. Xing

Semi-Supervised Clustering with Pairwise Constraints: A Discriminative Approach Zhengdong Lu

Semi-Supervised Mean Fields Fei Wang, Shijun Wang, Changshui Zhang, Ole Winther

Solving Markov Random Fields with Spectral Relaxation Timothee Cour, Jianbo Shi

Space-Efficient Sampling Sudipto Guha, Andrew McGregor

Sparse Nonparametric Density Estimation in High Dimensions Using the Rodeo Han Liu, John Lafferty, Larry Wasserman

Stick-Breaking Construction for the Indian Buffet Process Yee Whye Teh, Dilan Grür, Zoubin Ghahramani

SVM Versus Least Squares SVM Jieping Ye, Tao Xiong

The Kernel Path in Kernelized LASSO Gang Wang, Dit-Yan Yeung, Frederick H. Lochovsky

The Laplacian Eigenmaps Latent Variable Model Miguel A. Carreira-Perpiñán, Zhengdong Lu

The Rademacher Complexity of Co-Regularized Kernel Classes David S. Rosenberg, Peter L. Bartlett

Transductive Classification via Local Learning Regularization Mingrui Wu, Bernhard Schölkopf

Treelets | a Tool for Dimensionality Reduction and Multi-Scale Analysis of Unstructured Data Ann B. Lee, Boaz Nadler

Visualizing Pairwise Similarity via Semidefinite Programming Amir Globerson, Sam Roweis

Visualizing Similarity Data with a Mixture of Maps James Cook, Ilya Sutskever, Andriy Mnih, Geoffrey Hinton