ICML 2006

157 papers

A Brief Survey of Machine Learning Methods for Classification in Networked Data and an Application to Suspicion Scoring Sofus Attila Macskassy, Foster J. Provost
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A Choice Model with Infinitely Many Latent Features Dilan Görür, Frank Jäkel, Carl Edward Rasmussen
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A Continuation Method for Semi-Supervised SVMs Olivier Chapelle, Mingmin Chi, Alexander Zien
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A DC-Programming Algorithm for Kernel Selection Andreas Argyriou, Raphael Hauser, Charles A. Micchelli, Massimiliano Pontil
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A Duality View of Spectral Methods for Dimensionality Reduction Lin Xiao, Jun Sun, Stephen P. Boyd
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A Graphical Model for Predicting Protein Molecular Function Barbara E. Engelhardt, Michael I. Jordan, Steven E. Brenner
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A Latent Space Model for Rank Data Isobel Claire Gormley, Thomas Brendan Murphy
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A New Approach to Data Driven Clustering Arik Azran, Zoubin Ghahramani
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A Note on Mixtures of Experts for Multiclass Responses: Approximation Rate and Consistent Bayesian Inference Yang Ge, Wenxin Jiang
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A Probabilistic Model for Text Kernels Alain D. Lehmann, John Shawe-Taylor
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A Regularization Framework for Multiple-Instance Learning Pak-Ming Cheung, James T. Kwok
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A Simple Model for Complex Networks with Arbitrary Degree Distribution and Clustering Mark S. Handcock, Martina Morris
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A Statistical Approach to Rule Learning Ulrich Rückert, Stefan Kramer
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Accelerated Training of Conditional Random Fields with Stochastic Gradient Methods S. V. N. Vishwanathan, Nicol N. Schraudolph, Mark W. Schmidt, Kevin P. Murphy
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Active Learning via Transductive Experimental Design Kai Yu, Jinbo Bi, Volker Tresp
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Active Sampling for Detecting Irrelevant Features Sriharsha Veeramachaneni, Emanuele Olivetti, Paolo Avesani
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Age and Geographic Inferences of the LiveJournal Social Network Ian MacKinnon, Robert H. Warren
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Agnostic Active Learning Maria-Florina Balcan, Alina Beygelzimer, John Langford
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Algorithms for Portfolio Management Based on the Newton Method Amit Agarwal, Elad Hazan, Satyen Kale, Robert E. Schapire
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An Analysis of Graph Cut Size for Transductive Learning Steve Hanneke
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An Analytic Solution to Discrete Bayesian Reinforcement Learning Pascal Poupart, Nikos Vlassis, Jesse Hoey, Kevin Regan
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An Empirical Comparison of Supervised Learning Algorithms Rich Caruana, Alexandru Niculescu-Mizil
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An Intrinsic Reward Mechanism for Efficient Exploration Özgür Simsek, Andrew G. Barto
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An Investigation of Computational and Informational Limits in Gaussian Mixture Clustering Nathan Srebro, Gregory Shakhnarovich, Sam T. Roweis
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Approximate Kalman Filters for Embedding Author-Word Co-Occurrence Data over Time Purnamrita Sarkar, Sajid M. Siddiqi, Geoffrey J. Gordon
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Automatic Basis Function Construction for Approximate Dynamic Programming and Reinforcement Learning Philipp W. Keller, Shie Mannor, Doina Precup
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Autonomous Shaping: Knowledge Transfer in Reinforcement Learning George Dimitri Konidaris, Andrew G. Barto
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Batch Mode Active Learning and Its Application to Medical Image Classification Steven C. H. Hoi, Rong Jin, Jianke Zhu, Michael R. Lyu
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Bayesian Learning of Measurement and Structural Models Ricardo Bezerra de Andrade e Silva, Richard Scheines
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Bayesian Multi-Population Haplotype Inference via a Hierarchical Dirichlet Process Mixture Eric P. Xing, Kyung-Ah Sohn, Michael I. Jordan, Yee Whye Teh
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Bayesian Pattern Ranking for Move Prediction in the Game of Go David H. Stern, Ralf Herbrich, Thore Graepel
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Bayesian Regression with Input Noise for High Dimensional Data Jo-Anne Ting, Aaron D'Souza, Stefan Schaal
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Block-Quantized Kernel Matrix for Fast Spectral Embedding Kai Zhang, James T. Kwok
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Categorization in Multiple Category Systems Jean-Michel Renders, Éric Gaussier, Cyril Goutte, François Pacull, Gabriela Csurka
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Classifying EEG for Brain-Computer Interfaces: Learning Optimal Filters for Dynamical System Features Le Song, Julien Epps
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Clustering Documents with an Exponential-Family Approximation of the Dirichlet Compound Multinomial Distribution Charles Elkan
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Clustering Graphs by Weighted Substructure Mining Koji Tsuda, Taku Kudo
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CN = CPCN Liva Ralaivola, François Denis, Christophe Nicolas Magnan
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Collaborative Ordinal Regression Shipeng Yu, Kai Yu, Volker Tresp, Hans-Peter Kriegel
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Collaborative Prediction Using Ensembles of Maximum Margin Matrix Factorizations Dennis DeCoste
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Combined Central and Subspace Clustering for Computer Vision Applications Le Lu, René Vidal
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Combining Discriminative Features to Infer Complex Trajectories David A. Ross, Simon Osindero, Richard S. Zemel
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Combining Stochastic Block Models and Mixed Membership for Statistical Network Analysis Edoardo M. Airoldi, David M. Blei, Stephen E. Fienberg, Eric P. Xing
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Concept Boundary Detection for Speeding up SVMs Navneet Panda, Edward Y. Chang, Gang Wu
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Connectionist Temporal Classification: Labelling Unsegmented Sequence Data with Recurrent Neural Networks Alex Graves, Santiago Fernández, Faustino J. Gomez, Jürgen Schmidhuber
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Constructing Informative Priors Using Transfer Learning Rajat Raina, Andrew Y. Ng, Daphne Koller
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Convex Optimization Techniques for Fitting Sparse Gaussian Graphical Models Onureena Banerjee, Laurent El Ghaoui, Alexandre d'Aspremont, Georges Natsoulis
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Cost-Sensitive Learning with Conditional Markov Networks Prithviraj Sen, Lise Getoor
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Cover Trees for Nearest Neighbor Alina Beygelzimer, Sham M. Kakade, John Langford
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Data Association for Topic Intensity Tracking Andreas Krause, Jure Leskovec, Carlos Guestrin
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Dealing with Non-Stationary Environments Using Context Detection Bruno Castro da Silva, Eduardo W. Basso, Ana L. C. Bazzan, Paulo Martins Engel
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Deterministic Annealing for Semi-Supervised Kernel Machines Vikas Sindhwani, S. Sathiya Keerthi, Olivier Chapelle
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Discovering Functional Communities in Dynamical Networks Cosma Rohilla Shalizi, Marcelo F. Camperi, Kristina Lisa Klinkner
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Discrete Temporal Models of Social Networks Steve Hanneke, Eric P. Xing
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Discriminative Cluster Analysis Fernando De la Torre, Takeo Kanade
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Discriminative Unsupervised Learning of Structured Predictors Linli Xu, Dana F. Wilkinson, Finnegan Southey, Dale Schuurmans
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Dynamic Topic Models David M. Blei, John D. Lafferty
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Efficient Co-Regularised Least Squares Regression Ulf Brefeld, Thomas Gärtner, Tobias Scheffer, Stefan Wrobel
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Efficient Inference on Sequence Segmentation Models Sunita Sarawagi
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Efficient Lazy Elimination for Averaged One-Dependence Estimators Fei Zheng, Geoffrey I. Webb
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Efficient Learning of Naive Bayes Classifiers Under Class-Conditional Classification Noise François Denis, Christophe Nicolas Magnan, Liva Ralaivola
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Efficient MAP Approximation for Dense Energy Functions Marius Leordeanu, Martial Hebert
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Empirical Analysis of a Dynamic Social Network Built from PGP Keyrings Robert H. Warren, Dana F. Wilkinson, Mike Warnecke
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Estimating Relatedness via Data Compression Brendan Juba
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Experience-Efficient Learning in Associative Bandit Problems Alexander L. Strehl, Chris Mesterharm, Michael L. Littman, Haym Hirsh
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Exploratory Study of a New Model for Evolving Networks Anna Goldenberg, Alice X. Zheng
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Fast and Space Efficient String Kernels Using Suffix Arrays Choon Hui Teo, S. V. N. Vishwanathan
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Fast Direct Policy Evaluation Using Multiscale Analysis of Markov Diffusion Processes Mauro Maggioni, Sridhar Mahadevan
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Fast Nonparametric Clustering with Gaussian Blurring Mean-Shift Miguel Á. Carreira-Perpiñán
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Fast Particle Smoothing: If I Had a Million Particles Mike Klaas, Mark Briers, Nando de Freitas, Arnaud Doucet, Simon Maskell, Dustin Lang
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Fast Time Series Classification Using Numerosity Reduction Xiaopeng Xi, Eamonn J. Keogh, Christian R. Shelton, Li Wei, Chotirat Ann Ratanamahatana
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Fast Transpose Methods for Kernel Learning on Sparse Data Patrick Haffner
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Feature Subset Selection Bias for Classification Learning Surendra K. Singhi, Huan Liu
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Feature Value Acquisition in Testing: A Sequential Batch Test Algorithm Victor S. Sheng, Charles X. Ling
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Full Bayesian Network Classifiers Jiang Su, Harry Zhang
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Generalized Spectral Bounds for Sparse LDA Baback Moghaddam, Yair Weiss, Shai Avidan
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Graph Model Selection Using Maximum Likelihood Ivona Bezáková, Adam Kalai, Rahul Santhanam
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Heider vs Simmel: Emergent Features in Dynamic Structures David Krackhardt, Mark S. Handcock
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Hidden Process Models Rebecca A. Hutchinson, Tom M. Mitchell, Indrayana Rustandi
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Hierarchical Classification: Combining Bayes with SVM Nicolò Cesa-Bianchi, Claudio Gentile, Luca Zaniboni
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Higher Order Learning with Graphs Sameer Agarwal, Kristin Branson, Serge J. Belongie
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How Boosting the Margin Can Also Boost Classifier Complexity Lev Reyzin, Robert E. Schapire
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Inference with the Universum Jason Weston, Ronan Collobert, Fabian H. Sinz, Léon Bottou, Vladimir Vapnik
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Inferring Organizational Titles in Online Communication Galileo Mark S. Namata Jr., Lise Getoor, Christopher P. Diehl
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Iterative RELIEF for Feature Weighting Yijun Sun, Jian Li
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Joint Group and Topic Discovery from Relations and Text Andrew McCallum, Xuerui Wang, Natasha Mohanty
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Kernel Information Embeddings Roland Memisevic
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Kernel Predictive Linear Gaussian Models for Nonlinear Stochastic Dynamical Systems David Wingate, Satinder Singh
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Kernelizing the Output of Tree-Based Methods Pierre Geurts, Louis Wehenkel, Florence d'Alché-Buc
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Label Propagation Through Linear Neighborhoods Fei Wang, Changshui Zhang
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Learning a Kernel Function for Classification with Small Training Samples Tomer Hertz, Aharon Bar-Hillel, Daphna Weinshall
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Learning Algorithms for Online Principal-Agent Problems (and Selling Goods Online) Vincent Conitzer, Nikesh Garera
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Learning Approximate MRFs from Large Transactional Data Chao Wang, Srinivasan Parthasarathy
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Learning Hierarchical Task Networks by Observation Negin Nejati, Pat Langley, Tolga Könik
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Learning High-Order MRF Priors of Color Images Julian J. McAuley, Tibério S. Caetano, Alexander J. Smola, Matthias O. Franz
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Learning Low-Rank Kernel Matrices Brian Kulis, Mátyás A. Sustik, Inderjit S. Dhillon
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Learning Predictive State Representations Using Non-Blind Policies Michael H. Bowling, Peter McCracken, Michael James, James Neufeld, Dana F. Wilkinson
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Learning the Structure of Factored Markov Decision Processes in Reinforcement Learning Problems Thomas Degris, Olivier Sigaud, Pierre-Henri Wuillemin
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Learning to Impersonate Moni Naor, Guy N. Rothblum
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Learning User Preferences for Sets of Objects Marie desJardins, Eric Eaton, Kiri Wagstaff
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Local Distance Preservation in the GP-LVM Through Back Constraints Neil D. Lawrence, Joaquin Quiñonero Candela
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Local Fisher Discriminant Analysis for Supervised Dimensionality Reduction Masashi Sugiyama
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Locally Adaptive Classification Piloted by Uncertainty Juan Dai, Shuicheng Yan, Xiaoou Tang, James T. Kwok
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Looping Suffix Tree-Based Inference of Partially Observable Hidden State Michael P. Holmes, Charles Lee Isbell Jr.
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Maximum Margin Planning Nathan D. Ratliff, J. Andrew Bagnell, Martin Zinkevich
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MISSL: Multiple-Instance Semi-Supervised Learning Rouhollah Rahmani, Sally A. Goldman
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Multiclass Boosting with Repartitioning Ling Li
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Multiclass Reduced-Set Support Vector Machines Benyang Tang, Dominic Mazzoni
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Nightmare at Test Time: Robust Learning by Feature Deletion Amir Globerson, Sam T. Roweis
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Nonstationary Kernel Combination Darrin P. Lewis, Tony Jebara, William Stafford Noble
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Null Space Versus Orthogonal Linear Discriminant Analysis Jieping Ye, Tao Xiong
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On a Theory of Learning with Similarity Functions Maria-Florina Balcan, Avrim Blum
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On Bayesian Bounds Arindam Banerjee
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Online Decoding of Markov Models Under Latency Constraints Mukund Narasimhan, Paul A. Viola, Michael Shilman
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Online Multiclass Learning by Interclass Hypothesis Sharing Michael Fink, Shai Shalev-Shwartz, Yoram Singer, Shimon Ullman
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Optimal Kernel Selection in Kernel Fisher Discriminant Analysis Seung-Jean Kim, Alessandro Magnani, Stephen P. Boyd
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PAC Model-Free Reinforcement Learning Alexander L. Strehl, Lihong Li, Eric Wiewiora, John Langford, Michael L. Littman
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Pachinko Allocation: DAG-Structured Mixture Models of Topic Correlations Wei Li, Andrew McCallum
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Panel Discussion David M. Blei
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Pareto Optimal Linear Classification Seung-Jean Kim, Alessandro Magnani, Sikandar Samar, Stephen P. Boyd, Johan Lim
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Permutation Invariant SVMs Pannagadatta K. Shivaswamy, Tony Jebara
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Personalized Handwriting Recognition via Biased Regularization Wolf Kienzle, Kumar Chellapilla
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Practical Solutions to the Problem of Diagonal Dominance in Kernel Document Clustering Derek Greene, Padraig Cunningham
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Predictive Linear-Gaussian Models of Controlled Stochastic Dynamical Systems Matthew R. Rudary, Satinder Singh
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Predictive Search Distributions Edwin V. Bonilla, Christopher K. I. Williams, Felix V. Agakov, John Cavazos, John Thomson, Michael F. P. O'Boyle
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Predictive State Representations with Options Britton Wolfe, Satinder Singh
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Probabilistic Inference for Solving Discrete and Continuous State Markov Decision Processes Marc Toussaint, Amos J. Storkey
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Pruning in Ordered Bagging Ensembles Gonzalo Martínez-Muñoz, Alberto Suárez
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Quadratic Programming Relaxations for Metric Labeling and Markov Random Field MAP Estimation Pradeep Ravikumar, John D. Lafferty
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Qualitative Reinforcement Learning Arkady Epshteyn, Gerald DeJong
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R1-PCA: Rotational Invariant L1-Norm Principal Component Analysis for Robust Subspace Factorization Chris H. Q. Ding, Ding Zhou, Xiaofeng He, Hongyuan Zha
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Ranking Individuals by Group Comparisons Tzu-Kuo Huang, Chih-Jen Lin, Ruby C. Weng
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Ranking on Graph Data Shivani Agarwal
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Region-Based Value Iteration for Partially Observable Markov Decision Processes Hui Li, Xuejun Liao, Lawrence Carin
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Regression with the Optimised Combination Technique Jochen Garcke
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Reinforcement Learning for Optimized Trade Execution Yuriy Nevmyvaka, Yi Feng, Michael J. Kearns
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Relational Temporal Difference Learning Nima Asgharbeygi, David J. Stracuzzi, Pat Langley
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Robust Euclidean Embedding Lawrence Cayton, Sanjoy Dasgupta
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Robust Probabilistic Projections Cédric Archambeau, Nicolas Delannay, Michel Verleysen
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Semi-Supervised Learning for Structured Output Variables Ulf Brefeld, Tobias Scheffer
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Semi-Supervised Nonlinear Dimensionality Reduction Xin Yang, Haoying Fu, Hongyuan Zha, Jesse L. Barlow
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Sequential Update of ADtrees Josep Roure, Andrew W. Moore
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Simpler Knowledge-Based Support Vector Machines Quoc V. Le, Alexander J. Smola, Thomas Gärtner
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Spectral Clustering for Multi-Type Relational Data Bo Long, Zhongfei (Mark) Zhang, Xiaoyun Wu, Philip S. Yu
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Statistical Debugging: Simultaneous Identification of Multiple Bugs Alice X. Zheng, Michael I. Jordan, Ben Liblit, Mayur Naik, Alex Aiken
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Statistical Models for Networks: A Brief Review of Some Recent Research Stanley Wasserman, Garry Robins, Douglas L. Steinley
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Structural Inference of Hierarchies in Networks Aaron Clauset, Cristopher Moore, Mark E. J. Newman
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The Rate Adapting Poisson Model for Information Retrieval and Object Recognition Peter V. Gehler, Alex Holub, Max Welling
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The Relationship Between Precision-Recall and ROC Curves Jesse Davis, Mark H. Goadrich
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The Support Vector Decomposition Machine Francisco Pereira, Geoffrey J. Gordon
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The Uniqueness of a Good Optimum for K-Means Marina Meila
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Topic Modeling: Beyond Bag-of-Words Hanna M. Wallach
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Totally Corrective Boosting Algorithms That Maximize the Margin Manfred K. Warmuth, Jun Liao, Gunnar Rätsch
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Trading Convexity for Scalability Ronan Collobert, Fabian H. Sinz, Jason Weston, Léon Bottou
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Two-Dimensional Solution Path for Support Vector Regression Gang Wang, Dit-Yan Yeung, Frederick H. Lochovsky
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Using Inaccurate Models in Reinforcement Learning Pieter Abbeel, Morgan Quigley, Andrew Y. Ng
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Using Query-Specific Variance Estimates to Combine Bayesian Classifiers Chi-Hoon Lee, Russell Greiner, Shaojun Wang
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