- Preface
- Marina Meila and Xiaotong Shen;
2:1-2, 2007.
[pdf]
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- Policy-Gradients for PSRs and POMDPs
- Douglas Aberdeen, Olivier Buffet, Owen Thomas;
2:3-10, 2007.
[abs]
[pdf]
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- Generalized Non-metric Multidimensional Scaling
- Sameer Agarwal, Josh Wills, Lawrence Cayton, Gert Lanckriet, David Kriegman, Serge Belongie;
2:11-18, 2007.
[abs]
[pdf]
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- Seeking The Truly Correlated Topic Posterior - on tight approximate inference of logistic-normal admixture model
- Amr Ahmed, Eric P. Xing;
2:19-26, 2007.
[abs]
[pdf]
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- A Boosting Algorithm for Label Covering in Multilabel Problems
- Yonatan Amit, Ofer Dekel, Yoram Singer;
2:27-34, 2007.
[abs]
[pdf]
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- Mixture of Watson Distributions: A Generative Model for Hyperspherical Embeddings
- Avleen S. Bijral, Markus Breitenbach, Greg Grudic;
2:35-42, 2007.
[abs]
[pdf]
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- Kernel Multi-task Learning using Task-specific Features
- Edwin V. Bonilla, Felix V. Agakov, Christopher K. I. Williams;
2:43-50, 2007.
[abs]
[pdf]
|
- A Hybrid Pareto Model for Conditional Density Estimation of Asymmetric Fat-Tail Data
- Julie Carreau, Yoshua Bengio;
2:51-58, 2007.
[abs]
[pdf]
|
- The Laplacian Eigenmaps Latent Variable Model
- Miguel A. Carreira-Perpiñan, Zhengdong Lu;
2:59-66, 2007.
[abs]
[pdf]
|
- Visualizing Similarity Data with a Mixture of Maps
- James Cook, Ilya Sutskever, Andriy Mnih, Geoffrey Hinton;
2:67-74, 2007.
[abs]
[pdf]
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- Solving Markov Random Fields with Spectral Relaxation
- Timothee Cour, Jianbo Shi;
2:75-82, 2007.
[abs]
[pdf]
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- Fast search for Dirichlet process mixture models
- Hal Daume III;
2:83-90, 2007.
[abs]
[pdf]
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- Large-Margin Classification in Banach Spaces
- Ricky Der, Daniel Lee;
2:91-98, 2007.
[abs]
[pdf]
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- Learning A* underestimates : Using inference to guide inference
- Gregory Druck, Mukund Narasimhan, Paul Viola;
2:99-106, 2007.
[abs]
[pdf]
|
- Exact Bayesian structure learning from uncertain interventions
- Daniel Eaton, Kevin Murphy;
2:107-114, 2007.
[abs]
[pdf]
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- Online Learning of Search Heuristics
- Michael Fink;
2:114-122, 2007.
[abs]
[pdf]
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- Deterministic Annealing for Multiple-Instance Learning
- Peter V. Gehler, Olivier Chapelle;
2:123-130, 2007.
[abs]
[pdf]
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- Approximate inference using conditional entropy decompositions
- Amir Globerson, Tommi Jaakkola;
2:130-138, 2007.
[abs]
[pdf]
|
- Visualizing pairwise similarity via semidefinite programming
- Amir Globerson, Sam Roweis;
2:139-146, 2007.
[abs]
[pdf]
|
- SampleSearch: A Scheme that Searches for Consistent Samples
- Vibhav Gogate, Rina Dechter;
2:147-154, 2007.
[abs]
[pdf]
|
- Dissimilarity in Graph-Based Semi-Supervised Classification
- Andrew B. Goldberg, Xiaojin Zhu, Stephen Wright;
2:155-162, 2007.
[abs]
[pdf]
|
- Hidden Topic Markov Models
- Amit Gruber, Yair Weiss, Michal Rosen-Zvi;
2:163-170, 2007.
[abs]
[pdf]
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- Space-Efficient Sampling
- Sudipto Guha, Andrew McGregor;
2:171-178, 2007.
[abs]
[pdf]
|
- Information Retrieval by Inferring Implicit Queries from Eye Movements
- David R. Hardoon, John Shawe-Taylor, Antti Ajanki, Kai Puolamäki, Samuel Kaski;
2:179-186, 2007.
[abs]
[pdf]
|
- A Nonparametric Bayesian Approach to Modeling Overlapping Clusters
- Katherine A. Heller, Zoubin Ghahramani;
2:187-194, 2007.
[abs]
[pdf]
|
- Loopy Belief Propagation for Bipartite Maximum Weight b-Matching
- Bert Huang, Tony Jebara;
2:195-202, 2007.
[abs]
[pdf]
|
- Learning Markov Structure by Maximum Entropy Relaxation
- Jason K. Johnson, Venkat Chandrasekaran, Alan S. Willsky;
2:203-210, 2007.
[abs]
[pdf]
|
- Multi-object tracking with representations of the symmetric group
- Risi Kondor, Andrew Howard, Tony Jebara;
2:211-218, 2007.
[abs]
[pdf]
|
- MDL Histogram Density Estimation
- Petri Kontkanen, Petri Myllymäki;
2:219-226, 2007.
[abs]
[pdf]
|
- Incorporating Prior Knowledge on Features into Learning
- Eyal Krupka, Naftali Tishby;
2:227-234, 2007.
[abs]
[pdf]
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- Fast Low-Rank Semidefinite Programming for Embedding and Clustering
- Brian Kulis, Arun C. Surendran, John C. Platt;
2:235-242, 2007.
[abs]
[pdf]
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- Learning for Larger Datasets with the Gaussian Process Latent Variable Model
- Neil D. Lawrence;
2:243-250, 2007.
[abs]
[pdf]
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- Learning Nearest-Neighbor Quantizers from Labeled Data by Information Loss Minimization
- Svetlana Lazebnik, Maxim Raginsky;
2:251-258, 2007.
[abs]
[pdf]
|
- Treelets | A Tool for Dimensionality Reduction and Multi-Scale Analysis of Unstructured Data
- Ann B. Lee, Boaz Nadler;
2:259-266, 2007.
[abs]
[pdf]
|
- Efficient active learning with generalized linear models
- Jeremy Lewi, Robert Butera, Liam Paninski;
2:267-274, 2007.
[abs]
[pdf]
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- A Bayesian Divergence Prior for Classiffier Adaptation
- Xiao Li, Jeff Bilmes;
2:275-282, 2007.
[abs]
[pdf]
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- Sparse Nonparametric Density Estimation in High Dimensions Using the Rodeo
- Han Liu, John Lafferty, Larry Wasserman;
2:283-290, 2007.
[abs]
[pdf]
|
- Fisher Consistency of Multicategory Support Vector Machines
- Yufeng Liu;
2:291-298, 2007.
[abs]
[pdf]
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- Semi-supervised Clustering with Pairwise Constraints: A Discriminative Approach
- Zhengdong Lu;
2:299-306, 2007.
[abs]
[pdf]
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- Recall Systems: Effcient Learning and Use of Category Indices
- Omid Madani, Wiley Greiner, David Kempe, Mohammad R. Salavatipour;
2:307-314, 2007.
[abs]
[pdf]
|
- AClass: A simple, online, parallelizable algorithm for probabilistic classification
- Vikash K. Mansinghka, Daniel M. Roy, Ryan Rifkin, Josh Tenenbaum;
2:315-322, 2007.
[abs]
[pdf]
|
- A Fast Bundle-based Anytime Algorithm for Poker and other Convex Games
- H. Brendan McMahan, Geoffrey J. Gordony;
2:323-330, 2007.
[abs]
[pdf]
|
- Loop Corrected Belief Propagation
- Joris Mooij, Bastian Wemmenhove, Bert Kappen, Tommaso Rizzo;
2:331-338, 2007.
[abs]
[pdf]
|
- Inductive Transfer for Bayesian Network Structure Learning
- Alexandru Niculescu-Mizil, Rich Caruana;
2:339-346, 2007.
[abs]
[pdf]
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- Maximum Entropy Correlated Equilibria
- Luis E. Ortiz, Robert E. Schapire, Sham M. Kakade;
2:347-354, 2007.
[abs]
[pdf]
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- Approximate Counting of Graphical Models Via MCMC
- Jose M. Peña;
2:355-362, 2007.
[abs]
[pdf]
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- Margin based Transductive Graph Cuts using Linear Programming
- K. Pelckmans, J. Shawe-Taylor, J.A.K. Suykens, B. De Moor;
2:363-370, 2007.
[abs]
[pdf]
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- A Unified Energy-Based Framework for Unsupervised Learning
- Marc'Aurelio Ranzato, Y-Lan Boureau, Sumit Chopra, Yann LeCun;
2:371-379, 2007.
[abs]
[pdf]
|
- (Approximate) Subgradient Methods for Structured Prediction
- Nathan D. Ratliff, J. Andrew Bagnell, Martin A. Zinkevich;
2:380-387, 2007.
[abs]
[pdf]
|
- A fast algorithm for learning large scale preference relations
- Vikas C. Raykar, Ramani Duraiswami, Balaji Krishnapuram;
2:388-395, 2007.
[abs]
[pdf]
|
- The Rademacher Complexity of Co-Regularized Kernel Classes
- David S. Rosenberg, Peter L. Bartlett;
2:396-403, 2007.
[abs]
[pdf]
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- Continuous Neural Networks
- Nicolas Le Roux, Yoshua Bengio;
2:404-411, 2007.
[abs]
[pdf]
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- Learning a Nonlinear Embedding by Preserving Class Neighbourhood Structure
- Ruslan Salakhutdinov, Geoff Hinton;
2:412-419, 2007.
[abs]
[pdf]
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- A Latent Space Approach to Dynamic Embedding of Co-occurrence Data
- Purnamrita Sarkar, Sajid M. Siddiqi, Geogrey J. Gordon;
2:420-427, 2007.
[abs]
[pdf]
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- 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;
2:428-435, 2007.
[abs]
[pdf]
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- A Stochastic Quasi-Newton Method for Online Convex Optimization
- Nicol N. Schraudolph, Jin Yu, Simon Günter;
2:436-443, 2007.
[abs]
[pdf]
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- Bayesian Inference and Optimal Design in the Sparse Linear Model
- Matthias Seeger, Florian Steinke, Koji Tsuda;
2:444-451, 2007.
[abs]
[pdf]
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- A Unified Algorithmic Approach for Efficient Online Label Ranking
- Shai Shalev-Shwartz, Yoram Singer;
2:452-459, 2007.
[abs]
[pdf]
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- Minimum Volume Embedding
- Blake Shaw, Tony Jebara;
2:460-467, 2007.
[abs]
[pdf]
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- A Framework for Probability Density Estimation
- John Shawe-Taylor, Alex Dolia;
2:468-475, 2007.
[abs]
[pdf]
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- Fast Kernel ICA using an Approximate Newton Method
- Hao Shen, Stefanie Jegelka, Arthur Gretton;
2:476-483, 2007.
[abs]
[pdf]
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- Ellipsoidal Machines
- Pannagadatta K. Shivaswamy, Tony Jebara;
2:484-491, 2007.
[abs]
[pdf]
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- Fast State Discovery for HMM Model Selection and Learning
- Sajid M. Siddiqi, Geogrey J. Gordon, Andrew W. Moore;
2:492-499, 2007.
[abs]
[pdf]
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- Analogical Reasoning with Relational Bayesian Sets
- Ricardo Silva, Katherine A. Heller, Zoubin Ghahramani;
2:500-507, 2007.
[abs]
[pdf]
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- Dynamic Factorization Tests: Applications to Multi-modal Data Association
- Michael R. Siracusa, John W. Fisher III;
2:508-515, 2007.
[abs]
[pdf]
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- Generalized Darting Monte Carlo
- Cristian Sminchisescu, Max Welling;
2:516-523, 2007.
[abs]
[pdf]
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- Local and global sparse Gaussian process approximations
- Edward Snelson, Zoubin Ghahramani;
2:524-531, 2007.
[abs]
[pdf]
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- Predictive Discretization during Model Selection
- Harald Steck, Tommi S. Jaakkola;
2:532-539, 2007.
[abs]
[pdf]
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- Emerge and spread models and word burstiness
- Peter Sunehag;
2:540-547, 2007.
[abs]
[pdf]
|
- Learning Multilevel Distributed Representations for High-Dimensional Sequences
- Ilya Sutskever, Geoffrey Hinton;
2:548-555, 2007.
[abs]
[pdf]
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- Stick-breaking Construction for the Indian Buffet Process
- Yee Whye Teh, Dilan Grür, Zoubin Ghahramani;
2:556-563, 2007.
[abs]
[pdf]
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- Hierarchical Beta Processes and the Indian Buffet Process
- Romain Thibaux, Michael I. Jordan;
2:564-571, 2007.
[abs]
[pdf]
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- Nonlinear Dimensionality Reduction as Information Retrieval
- Jarkko Venna, Samuel Kaski;
2:572-579, 2007.
[abs]
[pdf]
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- The Kernel Path in Kernelized LASSO
- Gang Wang, Dit-Yan Yeung, Frederick H. Lochovsky;
2:580-587, 2007.
[abs]
[pdf]
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- Efficient large margin semisupervised learning
- Junhui Wang;
2:588-595, 2007.
[abs]
[pdf]
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- Semi-Supervised Mean Fields
- Fei Wang, Shijun Wang, Changshui Zhang, Ole Winther;
2:596-603, 2007.
[abs]
[pdf]
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- Fast Mean Shift with Accurate and Stable Convergence
- Ping Wang, Dongryeol Lee, Alexander Gray, James M. Rehg;
2:604-611, 2007.
[abs]
[pdf]
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- Metric Learning for Kernel Regression
- Kilian Q. Weinberger, Gerald Tesauro;
2:612-619, 2007.
[abs]
[pdf]
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- Performance Guarantees for Information Theoretic Active Inference
- Jason L. Williams, John W. Fisher III, Alan S. Willsky;
2:620-627, 2007.
[abs]
[pdf]
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- Transductive Classification via Local Learning Regularization
- Mingrui Wu, Bernhard Scholkopf;
2:628-635, 2007.
[abs]
[pdf]
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- How Powerful Can Any Regression Learning Procedure Be?
- Yuhong Yang;
2:636-643, 2007.
[abs]
[pdf]
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- SVM versus Least Squares SVM
- Jieping Ye, Tao Xiong;
2:644-651, 2007.
[abs]
[pdf]
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- Importance Sampling for General Hybrid Bayesian Networks
- Changhe Yuan, Marek J. Druzdzel;
2:652-659, 2007.
[abs]
[pdf]
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- Nonnegative Garrote Component Selection in Functional ANOVA models
- Ming Yuan;
2:660-666, 2007.
[abs]
[pdf]
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- Generalized Do-Calculus with Testable Causal Assumptions
- Jiji Zhang;
2:667-674, 2007.
[abs]
[pdf]
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- An Improved 1-norm SVM for Simultaneous Classification and Variable Selection
- Hui Zou;
2:675-681, 2007.
[abs]
[pdf]
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