MLJ 2016

64 papers

A Column-Wise Update Algorithm for Nonnegative Matrix Factorization in Bregman Divergence with an Orthogonal Constraint Keigo Kimura, Mineichi Kudo, Yuzuru Tanaka

A Dynamic Ensemble Approach to Robust Classification in the Presence of Missing Data Bryan Conroy, Larry J. Eshelman, Cristhian Potes, Minnan Xu-Wilson

A Non-Homogeneous Dynamic Bayesian Network with a Hidden Markov Model Dependency Structure Among the Temporal Data Points Marco Grzegorczyk

A Non-Negative Representation Learning Algorithm for Selecting Neighbors Lili Li, Jiancheng Lv, Zhang Yi

A Novel Probabilistic Clustering Model for Heterogeneous Networks Zhi-Hong Deng, Xiaoran Xu

A Semiparametric Method for Clustering Mixed Data Alex Foss, Marianthi Markatou, Bonnie Ray, Aliza Heching

A Topological Insight into Restricted Boltzmann Machines Decebal Constantin Mocanu, Elena Mocanu, Phuong H. Nguyen, Madeleine Gibescu, Antonio Liotta

Accelerating a Gibbs Sampler for Variable Selection on Genomics Data with Summarization and Variable Pre-Selection Combining an Array DBMS and R David Sergio Matusevich, Wellington Cabrera, Carlos Ordonez

Adaptive Trajectory Analysis of Replicator Dynamics for Data Clustering Morteza Haghir Chehreghani

ALRn: Accelerated Higher-Order Logistic Regression Nayyar Abbas Zaidi, Geoffrey I. Webb, Mark James Carman, François Petitjean, Jesús Cerquides

An Aggregate and Iterative Disaggregate Algorithm with Proven Optimality in Machine Learning Young Woong Park, Diego Klabjan

An Empirical Study on Image Bag Generators for Multi-Instance Learning Xiu-Shen Wei, Zhi-Hua Zhou

Asymptotic Accuracy of Bayes Estimation for Latent Variables with Redundancy Keisuke Yamazaki

Bayesian Multi-Tensor Factorization Suleiman A. Khan, Eemeli Leppäaho, Samuel Kaski

Bayesian Policy Reuse Benjamin Rosman, Majd Hawasly, Subramanian Ramamoorthy

Bibliographic Analysis on Research Publications Using Authors, Categorical Labels and the Citation Network Kar Wai Lim, Wray L. Buntine

Commentary: A Decomposition of the Outlier Detection Problem into a Set of Supervised Learning Problems Ye Zhu, Kai Ming Ting

Context-Based Unsupervised Ensemble Learning and Feature Ranking Erfan Soltanmohammadi, Mort Naraghi-Pour, Mihaela van der Schaar

Cost-Sensitive Boosting Algorithms: Do We Really Need Them? Nikolaos Nikolaou, Narayanan Unny Edakunni, Meelis Kull, Peter A. Flach, Gavin Brown

Expected Similarity Estimation for Large-Scale Batch and Streaming Anomaly Detection Markus Schneider, Wolfgang Ertel, Fabio Ramos

Explaining Mixture Models Through Semantic Pattern Mining and Banded Matrix Visualization Prem Raj Adhikari, Anze Vavpetic, Jan Kralj, Nada Lavrac, Jaakko Hollmén

Factorizing LambdaMART for Cold Start Recommendations Phong Nguyen, Jun Wang, Alexandros Kalousis

Fast and Scalable Lasso via Stochastic Frank-Wolfe Methods with a Convergence Guarantee Emanuele Frandi, Ricardo Ñanculef, Stefano Lodi, Claudio Sartori, Johan A. K. Suykens

Fast Learning of Relational Dependency Networks Oliver Schulte, Zhensong Qian, Arthur E. Kirkpatrick, Xiaoqian Yin, Yan Sun

Generalization Bounds for Metric and Similarity Learning Qiong Cao, Zheng-Chu Guo, Yiming Ying

ILP-Assisted De Novo Drug Design Rama Kaalia, Ashwin Srinivasan, Amit Kumar, Indira Ghosh

Interpretable Domain Adaptation via Optimization over the Stiefel Manifold Christian Pölitz, Wouter Duivesteijn, Katharina Morik

Large Margin Classification with Indefinite Similarities Ibrahim M. Alabdulmohsin, Moustapha Cissé, Xin Gao, Xiangliang Zhang

Learning (predictive) Risk Scores in the Presence of Censoring Due to Interventions Kirill Dyagilev, Suchi Saria

Learning Classification Models of Cognitive Conditions from Subtle Behaviors in the Digital Clock Drawing Test William Souillard-Mandar, Randall Davis, Cynthia Rudin, Rhoda Au, David J. Libon, Rodney Swenson, Catherine C. Price, Melissa Lamar, Dana L. Penney

Learning Deterministic Probabilistic Automata from a Model Checking Perspective Hua Mao, Yingke Chen, Manfred Jaeger, Thomas D. Nielsen, Kim G. Larsen, Brian Nielsen

Learning from Patches by Efficient Spectral Decomposition of a Structured Kernel Moshe Salhov, Amit Bermanis, Guy Wolf, Amir Averbuch

Learning Rotations with Little Regret Elad Hazan, Satyen Kale, Manfred K. Warmuth

Learning Rules for Multi-Label Classification: A Stacking and a Separate-and-Conquer Approach Eneldo Loza Mencía, Frederik Janssen

Learning to Control a Structured-Prediction Decoder for Detection of HTTP-Layer DDoS Attackers Uwe Dick, Tobias Scheffer

Learning to Identify Relevant Studies for Systematic Reviews Using Random Forest and External Information Madian Khabsa, Ahmed K. Elmagarmid, Ihab F. Ilyas, Hossam Hammady, Mourad Ouzzani

Learning Undirected Graphical Models Using Persistent Sequential Monte Carlo Hanchen Xiong, Sándor Szedmák, Justus H. Piater

Lifted Generative Learning of Markov Logic Networks Jan Van Haaren, Guy Van den Broeck, Wannes Meert, Jesse Davis

Loda: Lightweight On-Line Detector of Anomalies Tomás Pevný

Lower Bounds on Individual Sequence Regret Eyal Gofer, Yishay Mansour

Multi-Target Regression via Input Space Expansion: Treating Targets as Inputs Eleftherios Spyromitros Xioufis, Grigorios Tsoumakas, William Groves, Ioannis P. Vlahavas

Multi-Task Seizure Detection: Addressing Intra-Patient Variation in Seizure Morphologies Alexander Van Esbroeck, Landon Smith, Zeeshan Syed, Satinder Singh, Zahi N. Karam

On Data Preconditioning for Regularized Loss Minimization Tianbao Yang, Rong Jin, Shenghuo Zhu, Qihang Lin

On Some Transformations of High Dimension, Low Sample Size Data for Nearest Neighbor Classification Subhajit Dutta, Anil Kumar Ghosh

On the Need for Structure Modelling in Sequence Prediction Niall Twomey, Tom Diethe, Peter A. Flach

Online Passive-Aggressive Active Learning Jing Lu, Peilin Zhao, Steven C. H. Hoi

Population Recovery and Partial Identification Avi Wigderson, Amir Yehudayoff

Probabilistic Archetypal Analysis Sohan Seth, Manuel J. A. Eugster

Probabilistic Inference for Determining Options in Reinforcement Learning Christian Daniel, Herke van Hoof, Jan Peters, Gerhard Neumann

Probabilistic Logic Programming for Hybrid Relational Domains Davide Nitti, Tinne De Laet, Luc De Raedt

Propagation Kernels: Efficient Graph Kernels from Propagated Information Marion Neumann, Roman Garnett, Christian Bauckhage, Kristian Kersting

Rényi Divergence Minimization Based Co-Regularized Multiview Clustering Shalmali Joshi, Joydeep Ghosh, Mark Reid, Oluwasanmi Koyejo

Sequential Anomalies: A Study in the Railway Industry Rita P. Ribeiro, Pedro Mota Pereira, João Gama

Sparse and Low-Rank Matrix Regularization for Learning Time-Varying Markov Networks Junichiro Hirayama, Aapo Hyvärinen, Shin Ishii

Sparse Topical Analysis of Dyadic Data Using Matrix Tri-Factorization Ranganath Biligere Narayana Swamy

Spatio-Temporal Convolution Kernels Konstantin Knauf, Daniel Memmert, Ulf Brefeld

Special Issue on Discovery Science Saso Dzeroski, Dragi Kocev, Pance Panov

Subjective Interestingness of Subgraph Patterns Matthijs van Leeuwen, Tijl De Bie, Eirini Spyropoulou, Cédric Mesnage

Supersparse Linear Integer Models for Optimized Medical Scoring Systems Berk Ustun, Cynthia Rudin

Swamping and Masking in Markov Boundary Discovery Xuqing Liu, Xinsheng Liu

Tikhonov, Ivanov and Morozov Regularization for Support Vector Machine Learning Luca Oneto, Sandro Ridella, Davide Anguita

Transductive Hyperspectral Image Classification: Toward Integrating Spectral and Relational Features via an Iterative Ensemble System Annalisa Appice, Pietro Guccione, Donato Malerba

V-Shaped Interval Insensitive Loss for Ordinal Classification Kostiantyn Antoniuk, Vojtech Franc, Václav Hlavác

Variance-Constrained Actor-Critic Algorithms for Discounted and Average Reward MDPs L. A. Prashanth, Mohammad Ghavamzadeh