MLJ 2014

60 papers

A Comparison of Collapsed Bayesian Methods for Probabilistic Finite Automata Chihiro Shibata, Ryo Yoshinaka

A Constrained Matrix-Variate Gaussian Process for Transposable Data Oluwasanmi Koyejo, Cheng H. Lee, Joydeep Ghosh

A Semantic Matching Energy Function for Learning with Multi-Relational Data - Application to Word-Sense Disambiguation Antoine Bordes, Xavier Glorot, Jason Weston, Yoshua Bengio

A Theoretical and Empirical Analysis of Support Vector Machine Methods for Multiple-Instance Classification Gary Doran, Soumya Ray

Adaptively Learning Probabilistic Deterministic Automata from Data Streams Borja Balle, Jorge Castro, Ricard Gavaldà

Almost Optimal Estimates for Approximation and Learning by Radial Basis Function Networks Shaobo Lin, Xia Liu, Yuanhua Rong, Zongben Xu

An Improved Multiclass LogitBoost Using Adaptive-One-vs-One Peng Sun, Mark D. Reid, Jie Zhou

An Instance Level Analysis of Data Complexity Michael R. Smith, Tony R. Martinez, Christophe G. Giraud-Carrier

Bounds on the Sample Complexity for Private Learning and Private Data Release Amos Beimel, Hai Brenner, Shiva Prasad Kasiviswanathan, Kobbi Nissim

Collaborative Filtering with Information-Rich and Information-Sparse Entities Kai Zhu, Rui Wu, Lei Ying, R. Srikant

Collaborative Information Acquisition for Data-Driven Decisions Danxia Kong, Maytal Saar-Tsechansky

Computational Social Science and Social Computing Winter A. Mason, Jennifer Wortman Vaughan, Hanna M. Wallach

Detecting Concept Change in Dynamic Data Streams - A Sequential Approach Based on Reservoir Sampling Russel Pears, Sripirakas Sakthithasan, Yun Sing Koh

Detecting Inappropriate Access to Electronic Health Records Using Collaborative Filtering Aditya Krishna Menon, Xiaoqian Jiang, Jihoon Kim, Jaideep Vaidya, Lucila Ohno-Machado

Discriminative Extended Canonical Correlation Analysis for Pattern Set Matching Ognjen Arandjelovic

Distributional Learning of Parallel Multiple Context-Free Grammars Alexander Clark, Ryo Yoshinaka

Efficient Implementation of Class-Based Decomposition Schemes for Naïve Bayes Sang-Hyeun Park, Johannes Fürnkranz

Enhancing Understanding and Improving Prediction of Severe Weather Through Spatiotemporal Relational Learning Amy McGovern, David John Gagne Ii, John K. Williams, Rodger A. Brown, Jeffrey B. Basara

Fast Relational Learning Using Bottom Clause Propositionalization with Artificial Neural Networks Manoel V. M. França, Gerson Zaverucha, Artur S. d'Avila Garcez

Finding Relational Redescriptions Esther Galbrun, Angelika Kimmig

Forecast Aggregation via Recalibration Brandon M. Turner, Mark Steyvers, Edgar C. Merkle, David V. Budescu, Thomas S. Wallsten

From Machine Learning to Machine Reasoning - An Essay Léon Bottou

Hierarchical Constraints - Providing Structural Bias for Hierarchical Clustering Korinna Bade, Andreas Nürnberger

Improving Active Mealy Machine Learning for Protocol Conformance Testing Fides Aarts, Harco Kuppens, Jan Tretmans, Frits W. Vaandrager, Sicco Verwer

Imputation of Missing Links and Attributes in Longitudinal Social Surveys Vladimir Ouzienko, Zoran Obradovic

Interactive Relational Reinforcement Learning of Concept Semantics Matthias Nickles, Achim Rettinger

Interactive Topic Modeling Yuening Hu, Jordan L. Boyd-Graber, Brianna Satinoff, Alison Smith

Introduction to the Special Issue on Grammatical Inference Jeffrey Heinz, Colin de la Higuera, Tim Oates

Learning a Priori Constrained Weighted Majority Votes Aurélien Bellet, Amaury Habrard, Emilie Morvant, Marc Sebban

Learning from Interpretation Transition Katsumi Inoue, Tony Ribeiro, Chiaki Sakama

Learning from Multiple Annotators with Varying Expertise Yan Yan, Rómer Rosales, Glenn Fung, Subramanian Ramanathan, Jennifer G. Dy

Learning from Natural Instructions Dan Goldwasser, Dan Roth

Learning Perceptually Grounded Word Meanings from Unaligned Parallel Data Stefanie Tellex, Pratiksha Thaker, Joshua Mason Joseph, Nicholas Roy

Learning Register Automata: From Languages to Program Structures Malte Isberner, Falk Howar, Bernhard Steffen

Learning Semantic Representations of Objects and Their Parts Grégoire Mesnil, Antoine Bordes, Jason Weston, Gal Chechik, Yoshua Bengio

Learning What Is Where from Unlabeled Images: Joint Localization and Clustering of Foreground Objects Ashok Chandrashekar, Lorenzo Torresani, Richard Granger

Learning with Tensors: A Framework Based on Convex Optimization and Spectral Regularization Marco Signoretto, Dinh Quoc Tran, Lieven De Lathauwer, Johan A. K. Suykens

Least-Squares Independence Regression for Non-Linear Causal Inference Under Non-Gaussian Noise Makoto Yamada, Masashi Sugiyama, Jun Sese

Leave-One-Out Cross-Validation Is Risk Consistent for Lasso Darren Homrighausen, Daniel J. McDonald

Machine Learning for Science and Society Cynthia Rudin, Kiri L. Wagstaff

Machine Learning for Targeted Display Advertising: Transfer Learning in Action Claudia Perlich, Brian Dalessandro, Troy Raeder, Ori Stitelman, Foster J. Provost

Manifestations of User Personality in Website Choice and Behaviour on Online Social Networks Michal Kosinski, Yoram Bachrach, Pushmeet Kohli, David Stillwell, Thore Graepel

Meta-Interpretive Learning: Application to Grammatical Inference Stephen H. Muggleton, Dianhuan Lin, Niels Pahlavi, Alireza Tamaddoni-Nezhad

Modeling Topic Control to Detect Influence in Conversations Using Nonparametric Topic Models Viet-An Nguyen, Jordan L. Boyd-Graber, Philip Resnik, Deborah A. Cai, Jennifer E. Midberry, Yuanxin Wang

Modelling Relational Statistics with Bayes Nets Oliver Schulte, Hassan Khosravi, Arthur E. Kirkpatrick, Tianxiang Gao, Yuke Zhu

On Combining Machine Learning with Decision Making Theja Tulabandhula, Cynthia Rudin

PAutomaC: A Probabilistic Automata and Hidden Markov Models Learning Competition Sicco Verwer, Rémi Eyraud, Colin de la Higuera

Plane-Based Object Categorisation Using Relational Learning Reza Farid, Claude Sammut

Preference-Based Reinforcement Learning: Evolutionary Direct Policy Search Using a Preference-Based Racing Algorithm Róbert Busa-Fekete, Balázs Szörényi, Paul Weng, Weiwei Cheng, Eyke Hüllermeier

Regression Conformal Prediction with Random Forests Ulf Johansson, Henrik Boström, Tuve Löfström, Henrik Linusson

Regret Bounded by Gradual Variation for Online Convex Optimization Tianbao Yang, Mehrdad Mahdavi, Rong Jin, Shenghuo Zhu

SAGA: Sparse and Geometry-Aware Non-Negative Matrix Factorization Through Non-Linear Local Embedding Nicolas Courty, Xing Gong, Jimmy Vandel, Thomas Burger

Sequence Labeling with Multiple Annotators Filipe Rodrigues, Francisco C. Pereira, Bernardete Ribeiro

Spectral Learning of Weighted Automata - A Forward-Backward Perspective Borja Balle, Xavier Carreras, Franco M. Luque, Ariadna Quattoni

The Bane of Skew - Uncertain Ranks and Unrepresentative Precision Thomas Andrew Lampert, Pierre Gançarski

The Matrix Ridge Approximation: Algorithms and Applications Zhihua Zhang

The Variational Garrote Hilbert J. Kappen, Vicenç Gómez

Tracking People over Time in 19th Century Canada for Longitudinal Analysis Luiza Antonie, Kris Inwood, Daniel J. Lizotte, J. Andrew Ross

Using Random Forests to Diagnose Aviation Turbulence John K. Williams

Water Pipe Condition Assessment: A Hierarchical Beta Process Approach for Sparse Incident Data Zhidong Li, Bang Zhang, Yang Wang, Fang Chen, Ronnie Taib, Vicky Whiffin, Yi Wang