Proceedings are published and free online available as
Volume 36 of the JMLR Workshop and Conference Proceedings.

• Parallel Graph Mining with GPUs
  Robert Kessl, Nilothpal Talukder, Pranay Anchuri and Mohammed Zaki.
• Collapsed Gibbs Sampling for Latent Dirichlet Allocation on Spark
  Zhuolin Qiu, Bin Wu, Bai Wang and Le Yu.
• FAQ: A Framework for Fast Approximate Query Processing on Temporal Data
  Udayan Khurana, Srinivasan Parthasarathy and Deepak Turaga.
• Reducing Data Loading Bottleneck with Coarse Feature Vectors for Large Scale Learning
  Shingo Takamatsu and Carlos Guestrin.
• A Clustering Algorithm Merging MCMC and EM Methods Using SQL Queries
  David Matusevich and Carlos Ordonez.
• A Fast Distributed Stochastic Gradient Descent Algorithm for Matrix Factorization
  Fanglin Li, Bin Wu, Liutong Xu and Jing Shi.
• The Gamma Operator for Big Data Summarization on an Array DBMS
  Carlos Ordonez, Yiqun Zhang and Wellington Cabrera.
• Towards Optimal Execution of Density-based Clustering on Heterogeneous Hardware
  Dirk Habich, Stefanie Gahrig and Wolfgang Lehner.
• Scalable Graph Building from Text Data
  Thibault Debatty, Pietro Michiardi, Olivier Thonnard and Wim Mees.
• High density-focused uncertainty sampling for active learning over evolving stream data
  Dino Ienco, Indre Zliobaite and Bernhard Pfahringer.
• iPARAS: Incremental Construction of Parameter Space for Online Association Mining
  Xiao Qin, Ramoza Ahsan, Xika Lin, Elke Rundensteiner and Matthew Ward.
• Frequent Subgraph Discovery in Large Attributed Streaming Graphs
  Abhik Ray, Larry Holder and Sutanay Choudhury.
• From Tweets to Stories: Using Stream-Dashboard to weave the twitter data stream into dynamic cluster models
  Basheer Hawwash and Olfa Nasraoui.
• Ensembles of Adaptive Model Rules from High-Speed Data Streams
  Joao Duarte and Joao Gama.
• Scalable Heterogeneous Transfer Ranking
  Mohammad Taha Bahadori, Yan Liu and Bo Long.