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ORCID20th PKDD / 27th ECML 2016: Riva del Garda, Italy
- Paolo Frasconi, Niels Landwehr, Giuseppe Manco, Jilles Vreeken:
Machine Learning and Knowledge Discovery in Databases - European Conference, ECML PKDD 2016, Riva del Garda, Italy, September 19-23, 2016, Proceedings, Part I. Lecture Notes in Computer Science 9851, Springer 2016, ISBN 978-3-319-46127-4 - Nitish Shirish Keskar, Albert S. Berahas
:
adaQN: An Adaptive Quasi-Newton Algorithm for Training RNNs. 1-16 - Bokai Cao, Chun-Ta Lu, Xiaokai Wei, Philip S. Yu, Alex D. Leow:
Semi-supervised Tensor Factorization for Brain Network Analysis. 17-32 - Nicolas Schilling, Martin Wistuba, Lars Schmidt-Thieme:
Scalable Hyperparameter Optimization with Products of Gaussian Process Experts. 33-48 - Nguyen Lu Dang Khoa, Sanjay Chawla:
Incremental Commute Time Using Random Walks and Online Anomaly Detection. 49-64 - Michael Geilke, Andreas Karwath, Stefan Kramer:
Online Density Estimation of Heterogeneous Data Streams in Higher Dimensions. 65-80 - Branislav Kveton, Hung Bui, Mohammad Ghavamzadeh, Georgios Theocharous, S. Muthukrishnan, Siqi Sun:
Graphical Model Sketch. 81-97 - Yizhe Zhang, Changyou Chen, Ricardo Henao, Lawrence Carin:
Laplacian Hamiltonian Monte Carlo. 98-114 - Yuchen Wang, Kan Ren, Weinan Zhang, Jun Wang, Yong Yu:
Functional Bid Landscape Forecasting for Display Advertising. 115-131 - Naoto Ohsaka, Yutaro Yamaguchi, Naonori Kakimura, Ken-ichi Kawarabayashi:
Maximizing Time-Decaying Influence in Social Networks. 132-147 - Changying Du, Fuzhen Zhuang, Jia He, Qing He, Guoping Long:
Learning Beyond Predefined Label Space via Bayesian Nonparametric Topic Modelling. 148-164 - Changying Du, Changde Du, Guoping Long, Xin Jin, Yucheng Li:
Efficient Bayesian Maximum Margin Multiple Kernel Learning. 165-181 - Mostafa Haghir Chehreghani, Morteza Haghir Chehreghani:
Transactional Tree Mining. 182-198 - Martin Wistuba, Nicolas Schilling, Lars Schmidt-Thieme:
Two-Stage Transfer Surrogate Model for Automatic Hyperparameter Optimization. 199-214 - P. K. Srijith, Balamurugan Palaniappan, Shirish K. Shevade:
Gaussian Process Pseudo-Likelihood Models for Sequence Labeling. 215-231 - Evangelos Michelioudakis, Anastasios Skarlatidis, Georgios Paliouras, Alexander Artikis:
\mathtt OSLα : Online Structure Learning Using Background Knowledge Axiomatization. 232-247 - Colin Bellinger, Christopher Drummond, Nathalie Japkowicz:
Beyond the Boundaries of SMOTE - A Framework for Manifold-Based Synthetically Oversampling. 248-263 - Kijung Shin, Bryan Hooi, Christos Faloutsos:
M-Zoom: Fast Dense-Block Detection in Tensors with Quality Guarantees. 264-280 - Sen Wang, Feiping Nie, Xiaojun Chang, Xue Li, Quan Z. Sheng, Lina Yao:
Uncovering Locally Discriminative Structure for Feature Analysis. 281-295 - Behrooz Omidvar-Tehrani, Sihem Amer-Yahia, Pierre-François Dutot, Denis Trystram:
Multi-Objective Group Discovery on the Social Web. 296-312 - Yang Li, Junyuan Hong, Huanhuan Chen:
Sequential Data Classification in the Space of Liquid State Machines. 313-328 - Andreas Henelius, Isak Karlsson, Panagiotis Papapetrou, Antti Ukkonen, Kai Puolamäki:
Semigeometric Tiling of Event Sequences. 329-344 - Kongming Liang, Hong Chang, Shiguang Shan, Xilin Chen:
Attribute Conjunction Learning with Recurrent Neural Network. 345-360 - Boris Cule, Len Feremans, Bart Goethals:
Efficient Discovery of Sets of Co-occurring Items in Event Sequences. 361-377 - Congfu Xu, Xin Wang, Yunhui Guo:
Collaborative Expert Recommendation for Community-Based Question Answering. 378-393 - Mahmudur Rahman, Mohammad Al Hasan:
Link Prediction in Dynamic Networks Using Graphlet. 394-409 - Fábio Pinto, Carlos Soares, João Mendes-Moreira:
CHADE: Metalearning with Classifier Chains for Dynamic Combination of Classifiers. 410-425 - Xiawei Guo, James T. Kwok:
Aggregating Crowdsourced Ordinal Labels via Bayesian Clustering. 426-442 - Suncong Zheng, Jiaming Xu, Hongyun Bao, Zhenyu Qi, Jie Zhang, Hongwei Hao, Bo Xu:
Joint Learning of Entity Semantics and Relation Pattern for Relation Extraction. 443-458 - Xuezhi Cao, Yong Yu:
BASS: A Bootstrapping Approach for Aligning Heterogenous Social Networks. 459-475 - Guixiang Ma, Lifang He, Bokai Cao, Jiawei Zhang, Philip S. Yu, Ann B. Ragin:
Multi-graph Clustering Based on Interior-Node Topology with Applications to Brain Networks. 476-492 - Shankar Vembu, Sandra Zilles:
Interactive Learning from Multiple Noisy Labels. 493-508 - Yongdai Kim, Minwoo Chae, Kuhwan Jeong, Byungyup Kang, Hyoju Chung:
An Online Gibbs Sampler Algorithm for Hierarchical Dirichlet Processes Prior. 509-523 - Bolei Zhang, Zhuzhong Qian, Sanglu Lu:
Structure Pattern Analysis and Cascade Prediction in Social Networks. 524-539 - Peng Yan, Yun Li:
Graph-Margin Based Multi-label Feature Selection. 540-555 - Yahel David, Nahum Shimkin:
Pure Exploration for Max-Quantile Bandits. 556-571 - Dhouha Grissa, Blandine Comte, Estelle Pujos-Guillot, Amedeo Napoli:
A Hybrid Knowledge Discovery Approach for Mining Predictive Biomarkers in Metabolomic Data. 572-587 - Iordanis Koutsopoulos, Panagiotis Spentzouris:
Native Advertisement Selection and Allocation in Social Media Post Feeds. 588-603 - Shin Matsushima:
Asynchronous Feature Extraction for Large-Scale Linear Predictors. 604-618 - Maxime Gasse, Alex Aussem:
F-Measure Maximization in Multi-Label Classification with Conditionally Independent Label Subsets. 619-631 - Romain Tavenard, Simon Malinowski:
Cost-Aware Early Classification of Time Series. 632-647 - Farideh Fazayeli, Arindam Banerjee:
The Matrix Generalized Inverse Gaussian Distribution: Properties and Applications. 648-664 - Bo Han, Ivor W. Tsang, Ling Chen:
On the Convergence of a Family of Robust Losses for Stochastic Gradient Descent. 665-680 - Krzysztof J. Geras, Charles Sutton:
Composite Denoising Autoencoders. 681-696 - Jiawei Zhang, Qianyi Zhan, Lifang He, Charu C. Aggarwal, Philip S. Yu:
Trust Hole Identification in Signed Networks. 697-713 - Oleksandr Zadorozhnyi, Gunthard Benecke, Stephan Mandt, Tobias Scheffer, Marius Kloft:
Huber-Norm Regularization for Linear Prediction Models. 714-730 - Suyash P. Awate, Nishanth N. Koushik:
Robust Dictionary Learning on the Hilbert Sphere in Kernel Feature Space. 731-748 - Ibrahim M. Alabdulmohsin, Moustapha Cissé, Xiangliang Zhang:
Is Attribute-Based Zero-Shot Learning an Ill-Posed Strategy? 749-760 - Dipan K. Pal, Ole J. Mengshoel:
Stochastic CoSaMP: Randomizing Greedy Pursuit for Sparse Signal Recovery. 761-776 - Wenlin Wang, Changyou Chen, Wenlin Chen, Piyush Rai, Lawrence Carin:
Deep Metric Learning with Data Summarization. 777-794 - Hamed Karimi, Julie Nutini, Mark Schmidt:
Linear Convergence of Gradient and Proximal-Gradient Methods Under the Polyak-Łojasiewicz Condition. 795-811
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