Active & Online learning

Frequency-aware Truncated methods for Sparse Online Learning
Hidekazu Oiwa, Shin Matsushima, Hiroshi Nakagawa

Discriminative Experimental Design
Yu Zhang, Dit-Yan Yeung

Manifold Coarse Graining for Online Semi-Supervised Learning
Mehrdad Farajtabar, Amirreza Shaban, Hamid Rabiee, Mohammad Hossein Rohban

Active learning with evolving streaming data
Indrė Žliobaitė, Albert Bifet, Bernhard Pfahringer, Geoff Holmes

Online Structure Learning for Markov Logic Networks
Tuyen N. Huynh, Raymond J. Mooney

Applications of Data Mining

Image Classification for Age-related Macular Degeneration Screening using Hierarchical Image Decompositions and Graph Mining
Mohd Hanafi Ahmad Hijazi, Chuntao Jiang, Frans Coenen, Yalin Zheng

Label Noise-Tolerant Hidden Markov Models for Segmentation: Application to ECGs
Benoît Frénay, Gaël De Lannoy, Michel Verleysen

Resource-Aware On-Line RFID Localization Using Proximity Data
Christoph Scholz, Stephan Doerfel, Martin Atzmueller, Andreas Hotho, Gerd Stumme

PTMSearch: a Greedy Tree Traversal Algorithm for finding Protein Post-Translational Modifications in Tandem Mass Spectra
Attila Kertész-Farkas, Beáta Reiz, Michael P. Myers, Sándor Pongor

A Novel Framework for Locating Software Faults Using Latent Divergences
Shounak Roychowdhury, Sarfraz Khurshid

Classification & Bayesian Networks

Ancestor Relations in the Presence of Unobserved Variables
Pekka Parviainen, Mikko Koivisto

A Robust Ranking Methodology based on Diverse Calibration of AdaBoost
Róbert Busa-Fekete, Balázs Kégl, Tamás Éltető, György Szarvas

Efficiently approximating Markov tree bagging for high-dimensional density estimation
François Schnitzler, Sourour Ammar, Philippe Leray, Pierre Geurts, Louis Wehenkel

A boosting approach to multiview classification with cooperation
Sokol Koço, Cécile Capponi

ShareBoost: Boosting for Multi-View Learning with Performance Guarantees
Jing Peng, Costin Barbu, Guna Seetharaman, Wei Fan, Xian Wu, Kannappan Palaniappan

Classification & Prediction

Differentiating Code from Data in x86 Binaries
Richard Wartell, Yan Zhou, Kevin W. Hamlen, Murat Kantarcioglu, Bhavani Thuraisingham

Focused Multi-task Learning Using Gaussian Processes
Gayle Leen, Jaakko Peltonen, Samuel Kaski

On the Stratification of Multi-Label Data
Konstantinos Sechidis, Grigorios Tsoumakas, Ioannis Vlahavas

Learning Monotone Nonlinear Models using the Choquet Integral
Ali Fallah Tehrani, Weiwei Cheng, Krzysztof Dembczyński, Eyke Hüllermeier

Compact Coding for Hyperplane Classifiers in Heterogeneous Environment
Hao Shao, Bin Tong, Einoshin Suzuki

Clustering

The Minimum Code Length for Clustering Using the Gray Code
Mahito Sugiyama, Akihiro Yamamoto

Fast approximate text document clustering using Compressive Sampling
Laurence A. F. Park

Clustering Rankings in the Fourier Domain
Stéphan Clémençon, Romaric Gaudel, Jérémie Jakubowicz

Is there a best quality metric for graph clusters?
Hélio Almeida, Dorgival Guedes, Wagner Meira Jr, Mohammed Zaki

a-Clusterable Sets
Gerasimos S. Antzoulatos, Michael N. Vrahatis

Data Mining Theory & Foundations

The VC-Dimension of SQL Queries and Selectivity Estimation Through Sampling
Matteo Riondato, Mert Akdere, Ugur Çetintemel, Stanley B. Zdonik, Eli Upfal

Smooth Receiver Operating Characteristics (smROC) Curves
William Klement, Peter Flach, Nathalie Japkowicz, Stan Matwin

Active Supervised Domain Adaptation
Avishek Saha, Piyush Rai, Hal Daumé III, Suresh Venkatasubramanian, Scott DuVall

Comparing Apples and Oranges - Measuring Differences between Data Mining Results
Nikolaj Tatti, Jilles Vreeken

Learning Good Edit Similarities with Generalization Guarantees
Aurélien Bellet, Amaury Habrard, Marc Sebban

Ensemble Learning

Tracking Concept Change with Incremental Boosting by Minimization of the Evolving Exponential Loss
Mihajlo Grbovic, Slobodan Vucetic

Aggregating Independent and Dependent Models to Learn Multi-label Classifiers
Elena Montañés, José Ramón Quevedo, Juan José del Coz

Multi-Label Ensemble Learning
Chuan Shi, Xiangnan Kong, Philip S. Yu, Bai Wang

On oblique random forests
Bjoern H. Menze, B. Michael Kelm, Daniel N. Splitthoff, Ullrich Koethe, Fred A. Hamprecht

Novel Fusion Methods for Pattern Recognition
Muhammad Awais, Fei Yan, Krystian Mikolajczyk, Josef Kittler

Feature Selection, Extraction, and Construction

Feature Selection Stability Assessment based on the Jensen-Shannon Divergence
Roberto Guzmán-Martínez, Rocío Alaiz-Rodriguez

Fast projections onto L1,q-norm balls for grouped feature selection
Suvrit Sra

A Novel Stability based Feature Selection Framework for k-means Clustering
Dimitrios Mavroeidis, Elena Marchiori

Constrained Laplacian Score for semi-supervised feature selection
Khalid Benabdeslem, Mohammed Hindawi

Feature Selection for Transfer Learning
Selen Uguroglu, Jaime Carbonell

Frequent Sets and Patterns

Fast and Memory-Efficient Discovery of the Top-k Relevant Subgroups in a Reduced Candidate Space
Henrik Grosskreutz, Daniel Paurat

Constrained Logistic Regression for Discriminative Pattern Mining
Rajul Anand, Chandan K. Reddy

Mining Actionable Partial Orders in Collections of Sequences
Robert Gwadera, Gianluca Antonini, Abderrahim Labbi

Efficient Mining of Top Correlated Patterns Based on Null-Invariant Measures
Sangkyum Kim, Marina Barsky, Jiawei Han

Non-Redundant Subgroup Discovery in Large and Complex Data
Matthijs van Leeuwen, Arno Knobbe

Graphical & Hidden Markov Models

Fourier-Information Duality in the Identity Management Problem
Xiaoye Jiang, Jonathan Huang, Leonidas Guibas

An Alternating Direction Method for Dual MAP LP Relaxation
Ofer Meshi, Amir Globerson

Restricted Deep Belief Networks for Multi-View Learning
Yoonseop Kang, Seungjin Choi

A Spectral Learning Algorithm for Finite State Transducers
Borja Balle, Ariadna Quattoni, Xavier Carreras

Common Substructure Learning of Multiple Graphical Gaussian Models
Satoshi Hara, Takashi Washio

Learning from Social and Information Networks I

Peer and Authority Pressure in Information-Propagation Models
Aris Anagnostopoulos, George Brova, Evimaria Terzi

Active Learning of Model Parameters for Influence Maximization
Tianyu Cao, Xindong Wu, Tony Xiaohua Hu, Song Wang

A Shapley value Approach for Influence Attribution
Panagiotis Papapetrou, Aristides Gionis, Heikki Mannila

Influence and Passivity in Social Media
Daniel M. Romero, Wojciech Galuba, Sitaram Asur, Bernardo A. Huberman

Learning Recommendations in Social Media Systems By Weighting Multiple Relations
Boris Chidlovskii

Learning from Social and Information Networks II

Toward a Fair Review-Management System
Theodoros Lappas, Evimaria Terzi

Learning to Infer Social Ties in Large Networks
Wenbin Tang, Honglei Zhuang, Jie Tang

A Community-Based Pseudolikelihood Approach for Relationship Labeling in Social Networks
Huaiyu Wan, Youfang Lin, Zhihao Wu, Houkuan Huang

Graph Evolution via Social Diffusion Processes
Dijun Luo, Chris Ding, Heng Huang

Mining Research Topic-related Influence between Academia and Industry
Dan He

Learning from Time Series Data

Motion segmentation by a model-based clustering approach of incomplete trajectories
Vasileios Karavasilis, Konstantinos Blekas, Christophoros Nikou

Unsupervised Modeling of Partially Observable Environments
Vincent Graziano, Jan Koutnik, Jürgen Schmidhuber

Artemis: Assessing the Similarity of Event-interval Sequences
Orestis Kostakis, Panagiotis Papapetrou, Jaakko Hollmén

Discovering Temporal Bisociations for Linking Concepts over Time
Corrado Loglisci, Michelangelo Ceci

ShiftTree: an Interpretable Model-Based Approach for Time Series Classification
Balázs Hidasi, Csaba Gáspár-Papanek

Matrix and Tensor Analysis

Tensor Factorization Using Auxiliary Information
Atsuhiro Narita, Kohei Hayashi, Ryota Tomioka, Hisashi Kashima

Bayesian Matrix Co-Factorization: Variational Algorithm and Cramer-Rao Bound
Jiho Yoo, Seungjin Choi

Generalized Dictionary Learning for Symmetric Positive Definite Matrices with Application to Nearest Neighbor Retrieval
Suvrit Sra, Anoop Cherian

Link prediction via matrix factorization
Aditya Krishna Menon, Charles Elkan

Multi-Subspace Representation and Discovery
Dijun Luo, Feiping Nie, Chris Ding, Heng Huang

Model Selection & Statistical Learning

A selecting-the-best method for budgeted model selection
Gianluca Bontempi, Olivier Caelen

Aspects of Semi-Supervised and Active Learning in Conditional Random Fields
Nataliya Sokolovska

Sampling Table Configurations for the Hierarchical Poisson-Dirichlet Process
Changyou Chen, Lan Du, Wray Buntine

Comparing Probabilistic Models for Melodic Sequences
Athina Spiliopoulou, Amos Storkey

Multimodal nonlinear filtering using Gauss-Hermite Quadrature
Hannes P. Saal, Nicolas Heess, Sethu Vijayakumar

Preference Learning and Ranking

Direct Policy Ranking with Robot Data Streams
Riad Akrour, Marc Schoenauer, Michèle Sebag

Multiview Semi-Supervised Learning for Ranking Multilingual Documents
Nicolas Usunier, Massih-Reza Amini, Cyril Goutte

Preference-based policy iteration: Leveraging preference learning for reinforcement learning
Weiwei Cheng, Johannes Fürnkranz, Eyke Hüllermeier, Sang-Hyeun Park

Rule-Based Active Sampling for Learning to Rank
Rodrigo Silva, Marcos Gonçalves, Adriano Veloso

A Geometric Approach to Find Nondominated Policies to Imprecise Reward MDPs
Valdinei Freire da Silva, Anna Helena Reali Costa

Reinforcement learning

Preference elicitation and inverse reinforcement learning
Constantin Rothkopf, Christos Dimitrakakis

Sparse Kernel-SARSA(\lambda) with an Eligibility Trace
Matthew Robards, Peter Sunehag, Scott Sanner, Bhaskara Marthi

Analyzing and Escaping Local Optima in Planning as Inference for Partially Observable Domains
Pascal Poupart, Tobias Lang, Marc Toussaint

Lagrange Dual Decomposition for Finite Horizon Markov Decision Processes
Thomas Furmston, David Barber

Reinforcement Learning Through Global Stochastic Search in N-MDPs
Matteo Leonetti, Luca Iocchi, Subramanian Ramamoorthy

Relational learning and Inductive Logic Programming

Correcting Bias in Statistical Tests for Network Classifier Evaluation
Tao Wang, Jennifer Neville, Brian Gallagher, Tina Eliassi-Rad

Abductive Plan Recognition by Extending Bayesian Logic Programs
Sindhu Raghavan, Raymond J. Mooney

Learning the Parameters of Probabilistic Logic Programs from Interpretations
Bernd Gutmann, Ingo Thon, Luc De Raedt

Gaussian Logic for Predictive Classification
Ondřej Kuželka, Andrea Szabóová, Matěj Holec, Filip Železný

Learning First-Order Definite Theories via Object-Based Queries
Joseph Selman, Alan Fern

Semi-Supervised and Transductive Learning

Learning from Label Proportions by Optimizing Cluster Model Selection
Marco Stolpe, Katharina Morik

Adaptive Boosting for Transfer Learning using Dynamic Updates
Samir Al-Stouhi, Chandan K. Reddy

Learning from Partially Annotated Sequences
Eraldo R. Fernandes, Ulf Brefeld

Constraint selection for semi-supervised topological clustering
Kais Allab, Khalid Benabdeslem

COSNet: a Cost Sensitive Neural Network for Semi-supervised Learning in Graphs
Alberto Bertoni, Marco Frasca, Giorgio Valentini

Spectral Clustering & Graph Mining

Unifying Guilt-by-Association Approaches: Theorems and Fast Algorithms
Danai Koutra, Tai-You Ke, U Kang, Duen Horng Polo Chau, Hsing-Kuo Kenneth Pao, Christos Faloutsos

Privacy Preserving Semi-Supervised Learning for Labeled Graphs
Hiromi Arai, Jun Sakuma

Eigenvector Sensitive Feature Selection For Spectral Clustering
Yi Jiang, Jiangtao Ren

DB-CSC: A density-based approach for subspace clustering in graphs with feature vectors
Stephan Günnemann, Brigitte Boden, Thomas Seidl

Parallel Structural Graph Clustering
Madeleine Seeland, Simon A. Berger, Alexandros Stamatakis, Stefan Kramer

Supervised Learning I

Generalized Agreement Statistics over Fixed Group of Experts
Mohak Shah

Larger Residuals, Less Work: Active Document Scheduling for Latent Dirichlet Allocation
Mirwaes Wahabzada, Kristian Kersting

Datum-Wise Classification: A Sequential Approach to Sparsity
Gabriel Dulac-Arnold, Ludovic Denoyer, Philippe Preux, Patrick Gallinari

Transfer Learning With Adaptive Regularizers
Ulrich Rückert, Marius Kloft

Network Regression with Predictive Clustering Trees
Daniela Stojanova, Michelangelo Ceci, Annalisa Appice, Sašo Džeroski

Learning from Inconsistent and Unreliable Annotators by a Gaussian Mixture Model and Bayesian Information Criterion
Ping Zhang, Zoran Obradovic

Supervised Learning II

Regularized Sparse Kernel Slow Feature Analysis
Wendelin Böhmer, Steffen Grünewälder, Hannes Nickisch, Klaus Obermayer

Kernels for Link Prediction with Latent Feature Models
Canh Hao Nguyen, Hiroshi Mamitsuka

PerTurbo: a new classification algorithm based on the spectrum perturbations of the Laplace-Beltrami operator
Nicolas Courty, Thomas Burger, Johann Laurent

Fast Support Vector Machines for Structural Kernels
Aliaksei Severyn. Alessandro Moschitti

Building Sparse Support Vector Machines for Multi-Instance Classification
Zhouyu Fu, Guojun Lu, Kai Ming Ting, Dengsheng Zhang

Text Mining & Recommender Systems

Expertise finding using topic models -- the expert--tag--topic model
Gregor Heinrich

Analyzing Word Frequencies in Large Text Corpora using Inter-arrival Times and Bootstrapping
Jefrey Lijffijt, Panagiotis Papapetrou, Kai Puolamäki, Heikki Mannila

An Analysis of Probabilistic Methods for Top-N Recommendation in Collaborative Filtering
Nicola Barbieri, Giuseppe Manco

A Game Theoretic Framework for Data Privacy Preservation in Recommender Systems
Maria Halkidi, Iordanis Koutsopoulos

iDVS: An Interactive Multi-Document Visual Summarization System
Yi Zhang, Dingding Wang, Tao Li

Unsupervised Learning & dimensionality reduction

Minimum Neighbor Distance Estimators of Intrinsic Dimension
Gabriele Lombardi, Alessandro Rozza, Claudio Ceruti, Elena Casiraghi, Paola Campadelli

Online Clustering of High-Dimensional Trajectories under Concept Drift
Georg Krempl, Zaigham Faraz Siddiqui, Myra Spiliopoulou

Linear Discriminant Dimensionality Reduction
Quanquan Gu, Zhenhui Li, Jiawei Han

The Minimum Transfer Cost Principle for Model-Order Selection
Mario Frank, Morteza Haghir Chehreghani, Joachim Buhmann

Higher Order Contractive auto-encoder
Salah Rifai, Grégoire Mesnil, Pascal Vincent, Xavier Muller, Yoshua Bengio, Yann Dauphin, Xavier Glorot