AISTATS 1999

85 papers

An Improved 1-norm SVM for Simultaneous Classification and Variable Selection

Hui Zou

Generalized Do-Calculus with Testable Causal Assumptions

Jiji Zhang

Nonnegative Garrote Component Selection in Functional ANOVA models

Ming Yuan

Importance Sampling for General Hybrid Bayesian Networks

Changhe Yuan, Marek J. Druzdzel

SVM versus Least Squares SVM

Jieping Ye, Tao Xiong

How Powerful Can Any Regression Learning Procedure Be?

Yuhong Yang

Transductive Classification via Local Learning Regularization

Mingrui Wu, Bernhard Schölkopf

Performance Guarantees for Information Theoretic Active Inference

Jason L. Williams, John W. Fisher III, Alan S. Willsky

Metric Learning for Kernel Regression

Kilian Q. Weinberger, Gerald Tesauro

Fast Mean Shift with Accurate and Stable Convergence

Ping Wang, Dongryeol Lee, Alexander Gray, James M. Rehg

Semi-Supervised Mean Fields

Fei Wang, Shijun Wang, Changshui Zhang, Ole Winther

Efficient large margin semisupervised learning

Junhui Wang

The Kernel Path in Kernelized LASSO

Gang Wang, Dit-Yan Yeung, Frederick H. Lochovsky

Nonlinear Dimensionality Reduction as Information Retrieval

Jarkko Venna, Samuel Kaski

Hierarchical Beta Processes and the Indian Buffet Process

Romain Thibaux, Michael I. Jordan

Stick-breaking Construction for the Indian Buffet Process

Yee Whye Teh, Dilan Grür, Zoubin Ghahramani

Learning Multilevel Distributed Representations for High-Dimensional Sequences

Ilya Sutskever, Geoffrey Hinton

Emerge and spread models and word burstiness

Peter Sunehag

Predictive Discretization during Model Selection

Harald Steck, Tommi S. Jaakkola

Local and global sparse Gaussian process approximations

Edward Snelson, Zoubin Ghahramani

Generalized Darting Monte Carlo

Cristian Sminchisescu, Max Welling

Dynamic Factorization Tests: Applications to Multi-modal Data Association

Michael R. Siracusa, John W. Fisher III

Analogical Reasoning with Relational Bayesian Sets

Ricardo Silva, Katherine A. Heller, Zoubin Ghahramani

Fast State Discovery for HMM Model Selection and Learning

Sajid M. Siddiqi, Geogrey J. Gordon, Andrew W. Moore

Ellipsoidal Machines

Pannagadatta K. Shivaswamy, Tony Jebara

Fast Kernel ICA using an Approximate Newton Method

Hao Shen, Stefanie Jegelka, Arthur Gretton

A Framework for Probability Density Estimation

John Shawe-Taylor, Alex Dolia

Minimum Volume Embedding

Blake Shaw, Tony Jebara

A Unified Algorithmic Approach for Efficient Online Label Ranking

Shai Shalev-shwartz, Yoram Singer

Bayesian Inference and Optimal Design in the Sparse Linear Model

Matthias Seeger, Florian Steinke, Koji Tsuda

A Stochastic Quasi-Newton Method for Online Convex Optimization

Nicol N. Schraudolph, Jin Yu, Simon Günter

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

A Latent Space Approach to Dynamic Embedding of Co-occurrence Data

Purnamrita Sarkar, Sajid M. Siddiqi, Geogrey J. Gordon

Learning a Nonlinear Embedding by Preserving Class Neighbourhood Structure

Ruslan Salakhutdinov, Geoff Hinton

Continuous Neural Networks

Nicolas Le Roux, Yoshua Bengio

The Rademacher Complexity of Co-Regularized Kernel Classes

David S. Rosenberg, Peter L. Bartlett

A fast algorithm for learning large scale preference relations

Vikas C. Raykar, Ramani Duraiswami, Balaji Krishnapuram

(Approximate) Subgradient Methods for Structured Prediction

Nathan D. Ratliff, J. Andrew Bagnell, Martin A. Zinkevich

A Unified Energy-Based Framework for Unsupervised Learning

Marc’Aurelio Ranzato, Y-lan Boureau, Sumit Chopra, Yann LeCun

Margin based Transductive Graph Cuts using Linear Programming

K. Pelckmans, J. Shawe-Taylor, J.A.K. Suykens, B. De Moor

Approximate Counting of Graphical Models Via MCMC

Jose M. Peña

Maximum Entropy Correlated Equilibria

Luis E. Ortiz, Robert E. Schapire, Sham M. Kakade

Inductive Transfer for Bayesian Network Structure Learning

Alexandru Niculescu-mizil, Rich Caruana

Loop Corrected Belief Propagation

Joris Mooij, Bastian Wemmenhove, Bert Kappen, Tommaso Rizzo

A Fast Bundle-based Anytime Algorithm for Poker and other Convex Games

H. Brendan McMahan, Geoffrey J. Gordon

AClass: A simple, online, parallelizable algorithm for probabilistic classification

Vikash K. Mansinghka, Daniel M. Roy, Ryan Rifkin, Josh Tenenbaum

Recall Systems: Effcient Learning and Use of Category Indices

Omid Madani, Wiley Greiner, David Kempe, Mohammad R. Salavatipour

Semi-supervised Clustering with Pairwise Constraints: A Discriminative Approach

Zhengdong Lu

Fisher Consistency of Multicategory Support Vector Machines

Yufeng Liu

Sparse Nonparametric Density Estimation in High Dimensions Using the Rodeo

Han Liu, John Lafferty, Larry Wasserman

A Bayesian Divergence Prior for Classiffier Adaptation

Xiao Li, Jeff Bilmes

Efficient active learning with generalized linear models

Jeremy Lewi, Robert Butera, Liam Paninski

Treelets | A Tool for Dimensionality Reduction and Multi-Scale Analysis of Unstructured Data

Ann B. Lee, Boaz Nadler

Learning Nearest-Neighbor Quantizers from Labeled Data by Information Loss Minimization

Svetlana Lazebnik, Maxim Raginsky

Learning for Larger Datasets with the Gaussian Process Latent Variable Model

Neil D. Lawrence

Fast Low-Rank Semidefinite Programming for Embedding and Clustering

Brian Kulis, Arun C. Surendran, John C. Platt

Incorporating Prior Knowledge on Features into Learning

Eyal Krupka, Naftali Tishby

MDL Histogram Density Estimation

Petri Kontkanen, Petri Myllymäki

Multi-object tracking with representations of the symmetric group

Risi Kondor, Andrew Howard, Tony Jebara

Learning Markov Structure by Maximum Entropy Relaxation

Jason K. Johnson, Venkat Chandrasekaran, Alan S. Willsky

Loopy Belief Propagation for Bipartite Maximum Weight b-Matching

Bert Huang, Tony Jebara

A Nonparametric Bayesian Approach to Modeling Overlapping Clusters

Katherine A. Heller, Zoubin Ghahramani

Information Retrieval by Inferring Implicit Queries from Eye Movements

David R. Hardoon, John Shawe-Taylor, Antti Ajanki, Kai Puolamäki, Samuel Kaski

Space-Efficient Sampling

Sudipto Guha, Andrew McGregor

Hidden Topic Markov Models

Amit Gruber, Yair Weiss, Michal Rosen-Zvi

Andrew B. Goldberg, Xiaojin Zhu, Stephen Wright

SampleSearch: A Scheme that Searches for Consistent Samples

Vibhav Gogate, Rina Dechter

Visualizing pairwise similarity via semidefinite programming

Amir Globerson, Sam Roweis

Approximate inference using conditional entropy decompositions

Amir Globerson, Tommi Jaakkola

Deterministic Annealing for Multiple-Instance Learning

Peter V. Gehler, Olivier Chapelle

Online Learning of Search Heuristics

Michael Fink

Exact Bayesian structure learning from uncertain interventions

Daniel Eaton, Kevin Murphy

Learning A* underestimates : Using inference to guide inference

Gregory Druck, Mukund Narasimhan, Paul Viola

Large-Margin Classification in Banach Spaces

Ricky Der, Daniel Lee

Fast search for Dirichlet process mixture models

Hal Daume III

Solving Markov Random Fields with Spectral Relaxation

Timothee Cour, Jianbo Shi

James Cook, Ilya Sutskever, Andriy Mnih, Geoffrey Hinton

The Laplacian Eigenmaps Latent Variable Model

Miguel Á. Carreira-Perpiñán, Zhengdong Lu

A Hybrid Pareto Model for Conditional Density Estimation of Asymmetric Fat-Tail Data

Julie Carreau, Yoshua Bengio

Kernel Multi-task Learning using Task-specific Features

Edwin V. Bonilla, Felix V. Agakov, Christopher K. I. Williams

Mixture of Watson Distributions: A Generative Model for Hyperspherical Embeddings

Avleen S. Bijral, Markus Breitenbach, Greg Grudic

A Boosting Algorithm for Label Covering in Multilabel Problems

Yonatan Amit, Ofer Dekel, Yoram Singer

Seeking The Truly Correlated Topic Posterior - on tight approximate inference of logistic-normal admixture model

Amr Ahmed, Eric P. Xing

Generalized Non-metric Multidimensional Scaling

Sameer Agarwal, Josh Wills, Lawrence Cayton, Gert Lanckriet, David Kriegman

Policy-Gradients for PSRs and POMDPs

Douglas Aberdeen, Olivier Buffet, Owen Thomas