- S2201: JONG HOON AHNN, Scalable Big Data Computing for the Personalization of Machine Learned Models and its Application to Automatic Speech Recognition Service
- S2202: Hong Gu and Tao Song, Balanced Sampling Method for Imbalanced Big Data Using AdaBoost
- S2204: Moufida ADJOUT and Faouzi BOUFARES, A massively parallel processing for the Multiple Linear Regression
- S2205: Hasan Asfoor, Rajagopalan Srinivasan, Gayathri Vasudevan, Nele Verbiest, Chris Cornelis, Matthew Tolentino, Ankur Teredesai, and Martine De Cock,Computing Fuzzy Rough Approximations in Large Scale Information Systems
- S2206: Vinay Deolalikar, Feature Selection for Text Clustering in Limited Memory Using Monte Carlo Wrapper
- S2207: Yiqi Chen, Zhiyuan Lin, Robert Pienta, Minsuk Kahng, and Duen Horng Chau, Towards Scalable Graph Computation on Mobile Devices
- S2208: Cailing Dong and Arvind Agarwal, WS^2F: A Weakly Supervised Framework for Data Stream Filtering
- S2210: Yifang Jiang, Kai Chen, Yi Zhou, Diao Zhang, Qu Zhou, and Jianhua He, An Improved Memory Management Scheme for Large Scale Graph Computing Engine GraphChi
- S2212: Mohammad Sharif and Vijay Raghavan, A Clustering Based Scalable Hybrid Approach for Web Page Recommendation
- S2213: Xiaoguang Wang, Xuan Liu, Stan Matwin, Nathalie Nathalie Japkowicz, and hongyu guo, A Multi-View Two-level Classification Method for Generalized Multi-instance Problems
- S2215: Xiaoguang Wang, Xuan Liu, and Stan Matwin, Applying Instance-weighted Support Vector Machines to Class Imbalanced Datasets
- BigD208: Andrew Cassidy and Frank Deviney, Calculating Feature Importance in Data Streams with Concept Drift using Online Random Forest
- BigD278: Roberto D'Ambrosio, Wafa Belhajali, and Michel Barlaud, Boosting Stochastic Newton Descent for Bigdata Mining and Classification
- BigD309: Chandra B and Rajesh Kumar sharma, Parameterized Multilayer Perceptron for Fast Learning in Big Data
- BigD317: Eric Sibony, Stéphan Clémençon, and Jérémie Jakubowicz, Multiresolution analysis of incomplete rankings with applications to prediction
- BigD446: Ujjal Mukherjee and Ansu Chatterjee, Fast Algorithm for Computing Weighted Projection Quantiles and Data Depth for High-Dimensional Large
- BigD467: Xiaoli Song, Yue Shang, Yuan Ling, Mengwen Liu, and Xiaohua Hu, Pairwise Topic Model via Relation Extraction
- BigD470: Tanay Kumar Saha and Mohammad Hasan, FS^3: A sampling based method for top-k frequent subgraph mining