CSI5387 Winter 2014
Theme Papers
· Big Data Analysis
Ø Paper1: KDD’2013: TurboGraph: A Fast
Parallel Graph Engine Handling Billion-scale Graphs in a Single, Wook-Shin
Han; Sangyeon Lee; Kyungyeol Park; Jeong-Hoon Lee; Min-Soo Kim; Jinha Kim; and
Hwanjo Yu
Ø Paper2: ICDM’2013: Efficient Visualization of Large-scale Data Tables through Reordering and
Entropy Minimization, Nemanja Djuric, and Slobodan Vucetic
Ø Paper3:
ICML’2013: Large-Scale
Learning with Less RAM via Randomization,
Daniel Golovin; D. Sculley; Brendan McMahan; Michael Young
· Multi-Label Data Classification
Ø
Paper4: KDD’13: Multi-Label
Classification by Mining Label and Instance Correlations from Heterogeneous
Information Networks, Xiangnan Kong, Bokai Cao and Philip S. Yu
Ø Paper5: ECML’2013: Probabilistic Clustering for Hierarchical Multi-Label Classification of
Protein Functions, Rodrigo
C. Barros, Ricardo
Cerri, Alex A.
Freitas, André C. P. L. F. de Carvalho
Ø
Paper 6: ICML’2013: Efficient Multi-label Classification with Many Labels,
Wei Bi; James Kwok
· Multi-view Data Classification
Ø
Paper8: ECML’2013: Shared Structure Learning for Multiple Tasks with
Multiple Views, Xin Jin, Fuzhen
Zhuang, Shuhui
Wang, Qing He, Zhongzhi
Shi
Ø Paper9: ICML’2013:
Multi-View Clustering and Feature Learning
via Structured Sparsity, Hua Wang; Feiping Nie; Heng Huang
· Outlier Detection and class imbalances
Ø Paper10: ECML’2013: Local Outlier Detection with Interpretation , Xuan
Hong Dang, Barbora
Micenková, Ira
Assent, Raymond
T. Ng
Ø Paper11:
ICDM 2013: Combating Sub-clusters Effect in Imbalanced Classification,
Abhishek Shrivastava, and Yang Zhao
Ø
Paper12: KDD’2013: Subsampling for
Efficient and Effective Unsupervised Outlier Detection Ensembles, Arthur
Zimek, Matthew Gaudet, Ricardo J. G. Campello, Jšrg Sander
· Text Mining
Ø Paper13:
ICDM’2013: Classifying Spam Emails using Text and Readability Features,
Rushdi Shams and Robert Mercer
Ø Paper14:
KDD’2013:’2013: A Phrase Mining Framework for Recursive Construction of
a Topical Hierarchy,
Chi Wang, Marina Danilevsky, Nihit Desai, Yinan Zhang, Phuong Nguyen,
Thrivikrama Taula, Jiawei Han
Ø Paper15: ACL’2013: Separating
Fact from Fear: Tracking Flu Infections on Twitter
Lamb, Paul, Dredze
· Data Mining for Health Informatics
Ø Paper16 :
ICDM’2013: Exploring Patient Risk Groups with Incomplete Knowledge,
Xiang Wang, Fei Wang, Jun Wang, Buyue Qian, and Jianying Hu
Ø Paper17: KDD’2013: Multi-Source Learning with Block-wise Missing Data For Alzheimer’s
Disease Prediction, Shuo Xiang, Lei Yuan, Wei Fan, Yalin Wang, Paul Thompson,
Jieping Ye
Ø
Paper18: ECML’2013: Computational
Drug Repositioning by Ranking and Integrating Multiple Data Sources, Ping Zhang, Pankaj Agarwal, Zoran Obradovic
· Data Mining for Defense and Security
Ø Paper19: SDM’2013:
NetSpot: Spotting Significant Anomalous
Regions on Dynamic Networks, Misael Mongiovi, Petko Bogdanov, Razvan Ranca, Evangelos Papalexakis, Christos Faloutsos, Ambuj Singh
Ø Paper20: ECML’2013: Evasion
Attacks against Machine Learning at Test Time, Battista
Biggio, Igino
Corona, Davide
Maiorca, Blaine
Nelson, Nedim
Šrndić
Ø Paper21: ECML’2013: Learning
to Detect Patterns of Crime, Tong
Wang, Cynthia
Rudin, Daniel
Wagner, Rich
Sevieri
· Social Network Analysis
Ø Paper22: KDD’2013: The Role of
Information Diffusion in the Evolution of Social Networks, Lilian Weng, Jacob Ratkiewicz, Nicola
Perra, Bruno Goncalves, Carlos Castillo, Francesco Bonchi, Rossano Schifanella,
Filippo Menczer, Alessandro Flammini
Ø Paper23: ECML’2013: Discovering Nested Communities, Nikolaj
Tatti, Aristides
Gionis
Ø Paper24: ICML’2013:
Copy or Coincidence? A Model for
Detecting Social Influence and Duplication Events, Lisa Friedland; David
Jensen; Michael Lavine