Accepted Papers
Machine Learning
A Competitive Strategy for Function Approximation in Q-Learning
Alejandro Agostini and Enric Celaya
A Fast Dual Projected Newton Method for L1-Regularized Least Squares
Pinghua Gong and Changshui Zhang
A Framework for Incorporating General Domain Knowledge into Latent Dirichlet Allocation using First-Order Logic
David Andrzejewski, Xiaojin Zhu, Mark Craven and Benjamin Recht
A general MCMC method for Bayesian inference in logic-based probabilistic modeling
Taisuke Sato
A Hidden Markov Model variant for sequence classification
Sam Blasiak and Huzefa Rangwala
Active online classification via information maximization
Noam Slonim, Koby Crammer and Elad Yom-Tov
Active Surveying: A Probabilistic Approach for Identifying Key Opinion Leaders
Hossam Sharara, Myra Norton and Lise Getoor
Activity Recognition with Finite State Machines
Wesley Kerr, Anh Tran and Paul Cohen
Adaptation of a mixture of multivariate Bernoulli distributions
Ankur Kamthe, Miguel Carreira-Perpinan and Alberto Cerpa
Agent-oriented incremental activity recognition for human teams
Daniele Masato, Timothy Norman, Wamberto Vasconcelos and Katia Sycara
An Efficient Framework for Constructing Generalized Locally-Induced Text Metrics
Saeed Amizadeh, Shuguang Wang and Milos Hauskrecht
Angular Decomposition
Dengdi Sun, Chris Ding, Bin Luo and Jin Tang
Approximation-Guided Evolutionary Multi-Objective Optimization
Karl Bringmann, Tobias Friedrich, Frank Neumann and Markus Wagner
Automatic State Abstraction from Demonstration
Luis C. Cobo, Peng Zang, Charles L. Isbell and Andrea L. Thomaz
Ball Ranking Machine for Content-Based Multimedia Retrieval
Dijun Luo and Heng Huang
Bayesian Policy Search with Policy Priors
David Wingate, Leslie Kaelbling, Dan Roy, Noah Goodman and Joshua Tenenbaum
Bi-Weighting Domain Adaptation for Cross-Language Text Classification
Chang Wan, Rong Pan and Jiefei Li
Biclustering-Driven Ensemble of Bayesian Belief Network Classifiers for Underdetermined Problems
Tatdow Pansombut, William Hendrix, Jacob Gao, Brent Harrison and Nagiza Samatova
Classification of Emerging Extreme Event Tracks in Multi-Variate Spatio-Temporal Physical Systems Using Dynamic Network Structures: Application to Hurricane Track Prediction
Huseyin Sencan, Zhengzhang Chen, William Hendrix, Tatdow Pansombut, Frederick Semazzi, Alok Choudhary, Vipin Kumar, Nagiza Samatova and Anatoli Melechko
Cluster Indicator Decomposition for Efficient Matrix Factorization
Dijun Luo, Chris Ding and Heng Huang
Combining Supervised and Unsupervised Models via Unconstrained Probabilistic Embedding
Xudong Ma, Ping Luo, Fuzhen Zhuang, Qing He, Zhongzhi Shi and Zhiyong Shen
Concept Labeling: Building Text Classifiers with Minimal Supervision
Vijil Chenthamarakshan, Prem Melville, Vikas Sindhwani and Rick Lawrence
Consistency Measures for Feature Selection
Kilho Shin, Danny Fernandes, Seiya Miyazaki
Constituent Grammatical Evolution
Loukas Georgiou and William Teahan
Continuous Correlated Beta Processes
Robby Goetschalckx, Pascal Poupart and Jesse Hoey
Dealing with Concept Drift and Class Imbalance in Multi-label Stream Classification
Eleftherios Spyromitros Xioufis, Myra Spiliopoulou, Grigorios Tsoumakas and Ioannis Vlahavas
Discerning Linkage-Based Algorithms Among Hierarchical Clustering Methods
Margareta Ackerman and Shai Ben-David
Discovering deformable shape templates in continuous time-series data
Suchi Saria, Andrew Duchi and Daphne Koller
Distance Metric Learning Under Covariate Shift
Bin Cao
Distribution-Aware Online Classifiers
Tam T. Nguyen, Kuiyu Chang, Siu Cheung Hui
Diversity Regularized Machine
Yang Yu, Yu-Feng Li and Zhi-Hua Zhou
Domain Adaptation with Ensemble of Feature Groups
Rajhans Samdani and Scott Wen-tau Yih
Extracting temporal patterns from interval-based sequences
Thomas Guyet and René Quiniou
Fast Anomaly Detection for Streaming Data
Swee Chuan Tan, Kai Ming Ting and Tony Fei Liu
Fast Approximate Nearest-Neighbor Search using k-Nearest Neighbor Graph
Kiana Hajebi, Yasin Abbasi-Yadkori, Hossein Shahbazi and Hong Zhang
Fast Nonnegative Matrix Tri-Factorization for Large-Scale Data Co-Clustering
Hua Wang, Feiping Nie, Heng Huang and Chris Ding
Feature Selection via Joint Embedding Learning and Sparse Regression
Chenping Hou, Feiping Nie, Dongyun Yi and Yi Wu
Flexible, High Performance Convolutional Neural Networks for Image Classification
Dan Ciresan, Ueli Meier, Jonathan Masci, Luca Maria-Gambardella and Juergen Schmidhuber
Gaussianity Measures for Detecting the Direction of Causal Time Series
José Miguel Hernández-Lobato, Pablo Morales-Mombiela and Alberto Suárez
Generative Structure Learning for Markov Logic Network Based on Graph of Predicates
Quang-Thang DINH, Christel Vrain and Matthieu Exbrayat
Heterogeneous Domain Adaptation using Manifold Alignment
Chang Wang and Sridhar Mahadevan
Heuristic Rule-Based Regression via Dynamic Reduction to Classification
Frederik Janssen and Johannes Fuernkranz
Imitation Learning in Relational Words: A Functional Gradient Boosting Approach
Sriraam Natarajan, Saket Joshi, Prasad Tadepelli, Kristian Kersting and Jude Shavlik
Improving performance of topic models by variable grouping
Evgeniy Bart
Increasing the Scalability of the Fitting of Generalised Block Models for Social Networks
Jeffrey Chan, Samantha Lam and Conor Hayes
Incremental Slow Feature Analysis
Varun Raj Kompella, Matthew Luciw and Juergen Schmidhuber
Integrating Task Planning and Interactive Learning for Robots to Work in Human Environments
Alejandro Agostini, Carme Torras and Florentin Woergoetter
Joint Feature Selection and Subspace Learning
Quanquan Gu, Zhenhui Li and Jiawei Han
Jointly Learning Data-Dependent Label and Locality-Preserving Projections
Chang Wang and Sridhar Mahadevan
Kernel-based Selective Ensemble Learning for Streams of Trees
Valerio Grossi and Alessandro Sperduti
Kinship Verification through Transfer Learning
Siyu Xia, Ming Shao and Yun Fu
L21-Norm Regularized Discriminative Feature Selection for Unsupervised Learning
Yi Yang, Heng Tao Shen, Zhigang Ma, Zi Huang and Xiaofang Zhou
Learning a Distance Metric by Empirical Loss Minimization
Wei Bian, Dacheng Tao
Learning Decision Rules from Data Streams
Joao Gama and Petr Kosina
Learning Driving Behavior By Timed Syntactic Pattern Recognition
Sicco Verwer, Mathijs de Weerdt and Cees Witteveen
Learning Hash Functions for Cross-View Similarity Search
Shaishav Kumar and Raghavendra Udupa
Learning to Rank under Multiple Annotators
Ou Wu
LIFT: Multi-Label Learning with Label-Specific Features
Min-Ling Zhang
Local and Structural Consistency for Multi-manifold Clustering
Yong Wang, Yuan Jiang, Yi Wu, Zhi-Hua Zhou
Locality-constrained Concept Factorization
Haifeng Liu, Zheng Yang and Zhaohui Wu
Matrix Co-Factorization on Compressed Sensing
Jiho Yoo and Seungjin Choi
Modular Community Detection in Networks
Wenye Li and Dale Schuurmans
Multi-Evidence Lifted Message Passing
Babak Ahmadi, Kristian Kersting and Scott Sanner
Multi-Kernel Gaussian Processes
Arman Melkumyan and Fabio Ramos
Multi-kernel Multi-Label Learning with Max-Margin Concept Network
Wei Zhang, Xiangyang Xue, Jianping Fan, Xiaojing Huang, Bin Wu, Mingjie Liu
Multi-label Classification using Conditional Dependency Networks
Yuhong Guo
On Trivial Solution and Scale Transfer Problems in Graph Regularized NMF
Quanquan Gu, Chris Ding and Jiawei Han
Pattern Field Classification with Style Normalized Transformation
Xu-Yao Zhang, Kaizhu Huang and Cheng-Lin Liu
Positive Unlabeled Leaning for Time Series Classification
Minh Nhut Nguyen, Xiaoli Li and See-Kiong NG
Principal Component Analysis with Non-Greedy L1-Norm Maximization
Feiping Nie, Heng Huang, Ding and Dijun Luo
Probit Classifiers with a Generalized Gaussian Scale Mixture Prior
Guoqing Liu, Jianxin Wu and Suiping Zhou
Q-error as a Selection Mechanism in Modular Reinforcement-Learning Systems
Mark Ring and Tom Schaul
Revisiting Numerical Pattern Mining with Formal Concept Analysis
Mehdi Kaytoue, Sergei O. Kuznetsov and Amedeo Napoli
Semi-supervised learning from a translation model between data distributions
Henry Anaya-Sánchez, José Martínez-Sotoca and Adolfo Martínez-Usó
Similarity-Based Approach for Positive and Unlabeled learning
Yanshan Xiao, Bo Liu, Jie Yin, Longbing Cao and Chengqi Zhang
Simulation-based Data Mining Solution to the Structure of Water Surrounding Proteins
Hieu Chi Dam, Tu Bao Ho and Ayumu Sugiyama
Strategy Learning for Autonomous Agents in Smart Grid Markets
Prashant Reddy and Manuela Veloso
Unsupervised Grammar Learning with a Curriculum
Kewei Tu and Vasant Honavar
Unsupervised Learning of Patterns in Data Streams using Compression and Edit Distance
Sook-Ling Chua, Stephen Marsland and Hans Guesgen
Using Cases as Heuristics in Reinforcement Learning: a Transfer Learning application
Luiz Celiberto, Ramon Lopez de Mantaras and Reinaldo Bianchi
Utility-based Fraud Detection
Luis Torgo and Elsa Lopes