KDD

DenseAlert: Incremental Dense-Subtensor Detection in Tensor Streams

Kijung Shin, Bryan Hooi, Jisu Kim, Christos Faloutsos

Comments to be published in 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD-17)

Algorithmic decision making and the cost of fairness

Sam Corbett-Davies, Emma Pierson, Avi Feller, Sharad Goel, Aziz Huq

Comments To appear in Proceedings of KDD'17

KATE: K-Competitive Autoencoder for Text

Yu Chen, Mohammed J. Zaki

Comments 10 pages, KDD'17

Adaptive Seeding for Gaussian Mixture Models

Johannes Blömer, Kathrin Bujna

Comments This is a preprint of a paper that has been accepted for publication in the Proceedings of the 20th Pacific Asia Conference on Knowledge Discovery and Data Mining (PAKDD) 2016. The final publication is available at link.springer.com (http://link.springer.com/chapter/10.1007/978-3-319-31750-2 24)

Taste or Addiction?: Using Play Logs to Infer Song Selection Motivation

Kosetsu Tsukuda, Masataka Goto

Comments Accepted by The 21st Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD 2017)

REMIX: Automated Exploration for Interactive Outlier Detection

Yanjie Fu, Charu Aggarwal, Srinivasan Parthasarathy, Deepak S. Turaga, Hui Xiong

Comments To appear in KDD 2017

Matrix completion with queries

Natali Ruchansky, Mark Crovella, Evimaria Terzi

Comments Proceedings of the 21th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining

Learning what matters - Sampling interesting patterns

Vladimir Dzyuba, Matthijs van Leeuwen

Comments PAKDD 2017, extended version

Journal ref Advances in Knowledge Discovery and Data Mining. PAKDD 2017. Lecture Notes in Computer Science, vol.10234, 2017, pp.534-546

Approximating the Backbone in the Weighted Maximum Satisfiability Problem

He Jiang, Jifeng Xuan, Yan Hu

Comments 14 pages, 1 figure, Proceedings of Advances in Knowledge Discovery and Data Mining 2008 (PAKDD 2008), 2008

Visual Search at Pinterest

Yushi Jing, David Liu, Dmitry Kislyuk, Andrew Zhai, Jiajing Xu, Jeff Donahue, Sarah Tavel

Comments in Proceedings of the 21th ACM SIGKDD International Conference on Knowledge and Discovery and Data Mining, 2015

Recurrent Poisson Factorization for Temporal Recommendation

Seyed Abbas Hosseini, Keivan Alizadeh, Ali Khodadadi, Ali Arabzadeh, Mehrdad Farajtabar, Hongyuan Zha, Hamid R. Rabiee

Comments Submitted to KDD 2017 | Halifax, Nova Scotia - Canada - sigkdd, Codes are available at https://github.com/AHosseini/RPF

Hidden Community Detection in Social Networks

Kun He, Yingru Li, Sucheta Soundarajan, John E. Hopcroft

Comments 10 pages, 6 figures, 4 tables, submitted to KDD 2017

Non-negative Tensor Factorization for Human Behavioral Pattern Mining in Online Games

Anna Sapienza, Alessandro Bessi, Emilio Ferrara

Comments 9 pages, 6 figures, submitted to KDD'17

Graph Based Relational Features for Collective Classification

Immanuel Bayer, Uwe Nagel, Steffen Rendle

Comments Pacific-Asia Conference on Knowledge Discovery and Data Mining

Finding Influential Institutions in Bibliographic Information Networks

Anubhav Gupta, M. Narasimha Murty

Comments KDD Cup Workshop, 2016

Ranking Research Institutions Based On Related Academic Conferences

Yasin Orouskhani, Leili Tavabi

Comments 3 pages, 3 tables , ranked 12nd in KDD Cup 2016

GeT_Move: An Efficient and Unifying Spatio-Temporal Pattern Mining Algorithm for Moving Objects

Phan Nhat Hai, Pascal Poncelet, Maguelonne Teisseire

Comments 17 pages, 24 figures, submitted to KDD, TKDD

Feature Engineering and Ensemble Modeling for Paper Acceptance Rank Prediction

Yujie Qian, Yinpeng Dong, Ye Ma, Hailong Jin, Juanzi Li

Comments 2nd place winner report of KDD Cup 2016. More details can be found at https://kddcup2016.azurewebsites.net

A Subsequence Interleaving Model for Sequential Pattern Mining

Jaroslav Fowkes, Charles Sutton

Comments 10 pages in KDD 2016: Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining

Longitudinal LASSO: Jointly Learning Features and Temporal Contingency for Outcome Prediction

Tingyang Xu, Jiangwen Sun, Jinbo Bi

Comments Proceedings of the 21th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. ACM, 2015

Scheduling Broadcasts in a Network of Timelines

Emaad Manzoor, Haewoon Kwak, Panos Kalnis

Comments Submitted to KDD 2015

Decision Tree Classification on Outsourced Data

Koray Mancuhan, Chris Clifton

Comments Presented in the Data Ethics Workshop at the 20th ACM SIGKDD Conference on Knowledge Discovery and Data Mining

Identifiability and Transportability in Dynamic Causal Networks

Gilles Blondel, Marta Arias, Ricard Gavaldà

Comments Presented at the 2016 ACM SIGKDD Workshop on Causal Discovery

Ranking academic institutions on potential paper acceptance in upcoming conferences

Jobin Wilson, Ram Mohan, Muhammad Arif, Santanu Chaudhury, Brejesh Lall

Comments KDD 2016, KDD Cup 2016, Appeared in the KDD Cup Workshop 2016,https://kddcup2016.azurewebsites.net/Workshop

A Knowledge Ecosystem for the Food, Energy, and Water System

Praveen Rao, Anas Katib, Daniel E. Lopez Barron

Comments KDD 2016 Workshop on Data Science for Food, Energy and Water, Aug 13-17, 2016, San Francisco, CA

Fashion DNA: Merging Content and Sales Data for Recommendation and Article Mapping

Christian Bracher, Sebastian Heinz, Roland Vollgraf

Comments 10 pages, 13 figures. Paper presented at the workshop "Machine Learning Meets Fashion," KDD 2016 Conference, San Francisco, USA, March 14, 2016

Scalable Betweenness Centrality Maximization via Sampling

Ahmad Mahmoody, Charalampos E. Tsourakakis, Eli Upfal

Comments Accepted in KDD 2016

Interacting with Massive Behavioral Data

Shih-Chieh Su

Comments KDD 2016 Workshop on Interactive Data Exploration and Analytics

Multi-Sensor Prognostics using an Unsupervised Health Index based on LSTM Encoder-Decoder

Pankaj Malhotra, Vishnu TV, Anusha Ramakrishnan, Gaurangi Anand, Lovekesh Vig, Puneet Agarwal, Gautam Shroff

Comments Presented at 1st ACM SIGKDD Workshop on Machine Learning for Prognostics and Health Management, San Francisco, CA, USA, 2016. 10 pages

A Bayesian Network approach to County-Level Corn Yield Prediction using historical data and expert knowledge

Vikas Chawla, Hsiang Sing Naik, Adedotun Akintayo, Dermot Hayes, Patrick Schnable, Baskar Ganapathysubramanian, Soumik Sarkar

Comments 8 pages, In Proceedings of the 22nd ACM SIGKDD Workshop on Data Science for Food, Energy and Water , 2016 (San Francisco, CA, USA)