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2020 – today
- 2022
[j25]Caleb Belth
, Alican Büyükçakir, Danai Koutra:
A hidden challenge of link prediction: which pairs to check? Knowl. Inf. Syst. 64(3): 743-771 (2022)- [j24]Junchen Jin, Mark Heimann, Di Jin, Danai Koutra:
Toward Understanding and Evaluating Structural Node Embeddings. ACM Trans. Knowl. Discov. Data 16(3): 58:1-58:32 (2022) - [c65]Di Jin, Sungchul Kim, Ryan A. Rossi, Danai Koutra:
On Generalizing Static Node Embedding to Dynamic Settings. WSDM 2022: 410-420 - [c64]Puja Trivedi, Ekdeep Singh Lubana, Yujun Yan, Yaoqing Yang, Danai Koutra:
Augmentations in Graph Contrastive Learning: Current Methodological Flaws & Towards Better Practices. WWW 2022: 1538-1549 - 2021
- [j23]Danai Koutra:
The Power of Summarization in Graph Mining and Learning: Smaller Data, Faster Methods, More Interpretability. Proc. VLDB Endow. 14(13): 3416 (2021) - [j22]Di Jin, Bunyamin Sisman, Hao Wei, Xin Luna Dong, Danai Koutra:
Deep Transfer Learning for Multi-source Entity Linkage via Domain Adaptation. Proc. VLDB Endow. 15(3): 465-477 (2021) - [c63]Jiong Zhu, Ryan A. Rossi, Anup Rao, Tung Mai, Nedim Lipka, Nesreen K. Ahmed, Danai Koutra:
Graph Neural Networks with Heterophily. AAAI 2021: 11168-11176 - [c62]Tara Safavi, Danai Koutra:
Relational World Knowledge Representation in Contextual Language Models: A Review. EMNLP (1) 2021: 1053-1067 - [c61]Tara Safavi, Jing Zhu, Danai Koutra:
NegatER: Unsupervised Discovery of Negatives in Commonsense Knowledge Bases. EMNLP (1) 2021: 5633-5646 - [c60]Nishil Talati, Di Jin, Haojie Ye, Ajay Brahmakshatriya, Ganesh S. Dasika, Saman P. Amarasinghe, Trevor N. Mudge, Danai Koutra, Ronald G. Dreslinski:
A Deep Dive Into Understanding The Random Walk-Based Temporal Graph Learning. IISWC 2021: 87-100 - [c59]Jing Zhu, Xingyu Lu, Mark Heimann, Danai Koutra:
Node Proximity Is All You Need: Unified Structural and Positional Node and Graph Embedding. SDM 2021: 163-171 - [c58]Mark Heimann, Xiyuan Chen, Fatemeh Vahedian, Danai Koutra:
Refining Network Alignment to Improve Matched Neighborhood Consistency. SDM 2021: 172-180 - [i40]Junchen Jin, Mark Heimann, Di Jin, Danai Koutra:
Towards Understanding and Evaluating Structural Node Embeddings. CoRR abs/2101.05730 (2021) - [i39]Mark Heimann, Xiyuan Chen, Fatemeh Vahedian, Danai Koutra:
Refining Network Alignment to Improve Matched Neighborhood Consistency. CoRR abs/2101.08808 (2021) - [i38]Yujun Yan, Milad Hashemi, Kevin Swersky, Yaoqing Yang, Danai Koutra:
Two Sides of the Same Coin: Heterophily and Oversmoothing in Graph Convolutional Neural Networks. CoRR abs/2102.06462 (2021) - [i37]Caleb Belth, Alican Büyükçakir, Danai Koutra:
A Hidden Challenge of Link Prediction: Which Pairs to Check? CoRR abs/2102.07878 (2021) - [i36]Jing Zhu, Xingyu Lu, Mark Heimann, Danai Koutra:
Node Proximity Is All You Need: Unified Structural and Positional Node and Graph Embedding. CoRR abs/2102.13582 (2021) - [i35]Tara Safavi, Danai Koutra:
Relational world knowledge representation in contextual language models: A review. CoRR abs/2104.05837 (2021) - [i34]Jiong Zhu, Junchen Jin, Michael T. Schaub, Danai Koutra:
Improving Robustness of Graph Neural Networks with Heterophily-Inspired Designs. CoRR abs/2106.07767 (2021) - [i33]Di Jin, Bunyamin Sisman, Hao Wei, Xin Luna Dong, Danai Koutra:
Deep Transfer Learning for Multi-source Entity Linkage via Domain Adaptation. CoRR abs/2110.14509 (2021) - [i32]Puja Trivedi, Ekdeep Singh Lubana, Yujun Yan, Yaoqing Yang, Danai Koutra:
Augmentations in Graph Contrastive Learning: Current Methodological Flaws & Towards Better Practices. CoRR abs/2111.03220 (2021) - [i31]Fatemeh Vahedian, Ruiyu Li, Puja Trivedi, Di Jin, Danai Koutra:
Convolutional Neural Network Dynamics: A Graph Perspective. CoRR abs/2111.05410 (2021) - 2020
- [j21]Shengpu Tang, Parmida Davarmanesh, Yanmeng Song, Danai Koutra, Michael W. Sjoding, Jenna Wiens:
Democratizing EHR analyses with FIDDLE: a flexible data-driven preprocessing pipeline for structured clinical data. J. Am. Medical Informatics Assoc. 27(12): 1921-1934 (2020) - [j20]Saba A. Al-Sayouri, Ekta Gujral, Danai Koutra, Evangelos E. Papalexakis, Sarah S. Lam:
t-PINE: tensor-based predictable and interpretable node embeddings. Soc. Netw. Anal. Min. 10(1): 46 (2020) - [j19]Ryan A. Rossi, Di Jin, Sungchul Kim, Nesreen K. Ahmed, Danai Koutra, John Boaz Lee:
On Proximity and Structural Role-based Embeddings in Networks: Misconceptions, Techniques, and Applications. ACM Trans. Knowl. Discov. Data 14(5): 63:1-63:37 (2020) - [c57]Kyle Kai Qin, Flora D. Salim, Yongli Ren, Wei Shao, Mark Heimann, Danai Koutra:
G-CREWE: Graph CompREssion With Embedding for Network Alignment. CIKM 2020: 1255-1264 - [c56]Xiyuan Chen, Mark Heimann, Fatemeh Vahedian, Danai Koutra:
CONE-Align: Consistent Network Alignment with Proximity-Preserving Node Embedding. CIKM 2020: 1985-1988 - [c55]Josh Gardner, Jawad Mroueh, Natalia Jenuwine, Noah Weaverdyck, Samuel Krassenstein, Arya Farahi, Danai Koutra:
Driving with Data in the Motor City: Understanding and Predicting Fleet Maintenance Patterns. DSAA 2020: 380-389 - [c54]Tara Safavi, Danai Koutra, Edgar Meij:
Evaluating the Calibration of Knowledge Graph Embeddings for Trustworthy Link Prediction. EMNLP (1) 2020: 8308-8321 - [c53]Tara Safavi, Danai Koutra:
CoDEx: A Comprehensive Knowledge Graph Completion Benchmark. EMNLP (1) 2020: 8328-8350 - [c52]Caleb Belth, Alican Büyükçakir, Danai Koutra:
A Hidden Challenge of Link Prediction: Which Pairs to Check? ICDM 2020: 831-840 - [c51]Scott McMillan, Manoj Kumar, Danai Koutra, Mahantesh Halappanavar, Tim Mattson, Antonino Tumeo:
Message from the workshop chairs. IPDPS Workshops 2020: 199-200 - [c50]Caleb Belth, Xinyi Zheng, Danai Koutra:
Mining Persistent Activity in Continually Evolving Networks. KDD 2020: 934-944 - [c49]Yujun Yan, Kevin Swersky, Danai Koutra, Parthasarathy Ranganathan, Milad Hashemi:
Neural Execution Engines: Learning to Execute Subroutines. NeurIPS 2020 - [c48]Jiong Zhu, Yujun Yan, Lingxiao Zhao, Mark Heimann, Leman Akoglu, Danai Koutra:
Beyond Homophily in Graph Neural Networks: Current Limitations and Effective Designs. NeurIPS 2020 - [c47]Wenjie Feng, Shenghua Liu, Danai Koutra, Huawei Shen, Xueqi Cheng:
SpecGreedy: Unified Dense Subgraph Detection. ECML/PKDD (1) 2020: 181-197 - [c46]Tara Safavi, Adam Fourney, Robert Sim, Marcin Juraszek, Shane Williams, Ned Friend, Danai Koutra, Paul N. Bennett:
Toward Activity Discovery in the Personal Web. WSDM 2020: 492-500 - [c45]Caleb Belth, Xinyi Zheng, Jilles Vreeken, Danai Koutra:
What is Normal, What is Strange, and What is Missing in a Knowledge Graph: Unified Characterization via Inductive Summarization. WWW 2020: 1115-1126 - [i30]Josh Gardner, Jawad Mroueh, Natalia Jenuwine, Noah Weaverdyck, Samuel Krassenstein, Arya Farahi, Danai Koutra:
Driving with Data in the Motor City: Mining and Modeling Vehicle Fleet Maintenance Data. CoRR abs/2002.10010 (2020) - [i29]Caleb Belth, Xinyi Zheng, Jilles Vreeken, Danai Koutra:
What is Normal, What is Strange, and What is Missing in a Knowledge Graph: Unified Characterization via Inductive Summarization. CoRR abs/2003.10412 (2020) - [i28]Tara Safavi, Danai Koutra, Edgar Meij:
Improving the Utility of Knowledge Graph Embeddings with Calibration. CoRR abs/2004.01168 (2020) - [i27]Xiyuan Chen, Mark Heimann, Fatemeh Vahedian, Danai Koutra:
Consistent Network Alignment with Node Embedding. CoRR abs/2005.04725 (2020) - [i26]Yujun Yan, Kevin Swersky, Danai Koutra, Parthasarathy Ranganathan, Milad Hashemi:
Neural Execution Engines: Learning to Execute Subroutines. CoRR abs/2006.08084 (2020) - [i25]Jiong Zhu, Yujun Yan, Lingxiao Zhao, Mark Heimann, Leman Akoglu, Danai Koutra:
Generalizing Graph Neural Networks Beyond Homophily. CoRR abs/2006.11468 (2020) - [i24]Caleb Belth, Xinyi Zheng, Danai Koutra:
Mining Persistent Activity in Continually Evolving Networks. CoRR abs/2006.15410 (2020) - [i23]Kyle Kai Qin, Flora D. Salim, Yongli Ren, Wei Shao, Mark Heimann, Danai Koutra:
G-CREWE: Graph CompREssion With Embedding for Network Alignment. CoRR abs/2007.16208 (2020) - [i22]Tara Safavi, Danai Koutra:
CoDEx: A Comprehensive Knowledge Graph Completion Benchmark. CoRR abs/2009.07810 (2020) - [i21]Di Jin, Sungchul Kim, Ryan A. Rossi, Danai Koutra:
From Static to Dynamic Node Embeddings. CoRR abs/2009.10017 (2020) - [i20]Jiong Zhu, Ryan A. Rossi, Anup B. Rao, Tung Mai, Nedim Lipka, Nesreen K. Ahmed, Danai Koutra:
Graph Neural Networks with Heterophily. CoRR abs/2009.13566 (2020) - [i19]Tara Safavi, Danai Koutra:
Generating Negative Commonsense Knowledge. CoRR abs/2011.07497 (2020)
2010 – 2019
- 2019
- [j18]Saba A. Al-Sayouri, Danai Koutra, Evangelos E. Papalexakis, Sarah S. Lam:
SURREAL: Subgraph Robust Representation Learning. Appl. Netw. Sci. 4(1): 88:1-88:20 (2019) - [j17]Oshini Goonetilleke, Danai Koutra, Kewen Liao, Timos Sellis:
On effective and efficient graph edge labeling. Distributed Parallel Databases 37(1): 5-38 (2019) - [j16]Tara Safavi, Chandra Sekhar Sripada, Danai Koutra:
Fast network discovery on sequence data via time-aware hashing. Knowl. Inf. Syst. 61(2): 987-1017 (2019) - [j15]Asso Hamzehei, Raymond K. Wong, Danai Koutra, Fang Chen:
Collaborative topic regression for predicting topic-based social influence. Mach. Learn. 108(10): 1831-1850 (2019) - [j14]Pin-Yu Chen, Chun-Chen Tu, Pai-Shun Ting, Ya-Yun Lo, Danai Koutra, Alfred O. Hero III:
Identifying Influential Links for Event Propagation on Twitter: A Network of Networks Approach. IEEE Trans. Signal Inf. Process. over Networks 5(1): 139-151 (2019) - [c44]Caleb Belth, Fahad Kamran, Donna Tjandra, Danai Koutra:
When to remember where you came from: node representation learning in higher-order networks. ASONAM 2019: 222-225 - [c43]Sang Won Lee, Aaron Willette, Danai Koutra, Walter S. Lasecki:
The Effect of Social Interaction on Facilitating Audience Participation in a Live Music Performance. Creativity & Cognition 2019: 108-120 - [c42]Mark Heimann, Tara Safavi, Danai Koutra:
Distribution of Node Embeddings as Multiresolution Features for Graphs. ICDM 2019: 289-298 - [c41]Tara Safavi, Caleb Belth, Lukas Faber, Davide Mottin, Emmanuel Müller, Danai Koutra:
Personalized Knowledge Graph Summarization: From the Cloud to Your Pocket. ICDM 2019: 528-537 - [c40]Yujun Yan, Jiong Zhu, Marlena Duda, Eric Solarz, Chandra Sekhar Sripada, Danai Koutra:
GroupINN: Grouping-based Interpretable Neural Network for Classification of Limited, Noisy Brain Data. KDD 2019: 772-782 - [c39]Di Jin, Ryan A. Rossi, Eunyee Koh, Sungchul Kim, Anup Rao, Danai Koutra:
Latent Network Summarization: Bridging Network Embedding and Summarization. KDD 2019: 987-997 - [c38]Di Jin, Mark Heimann, Tara Safavi, Mengdi Wang, Wei Lee, Lindsay Snider, Danai Koutra:
Smart Roles: Inferring Professional Roles in Email Networks. KDD 2019: 2923-2933 - [c37]Di Jin, Mark Heimann, Ryan A. Rossi, Danai Koutra:
node2bits: Compact Time- and Attribute-Aware Node Representations for User Stitching. ECML/PKDD (1) 2019: 483-506 - [c36]Yike Liu, Linhong Zhu, Pedro A. Szekely, Aram Galstyan, Danai Koutra:
Coupled Clustering of Time-Series and Networks. SDM 2019: 531-539 - [i18]Di Jin, Mark Heimann, Ryan A. Rossi, Danai Koutra:
node2bits: Compact Time- and Attribute-aware Node Representations for User Stitching. CoRR abs/1904.08572 (2019) - [i17]Ryan A. Rossi, Di Jin, Sungchul Kim, Nesreen K. Ahmed, Danai Koutra, John Boaz Lee:
From Community to Role-based Graph Embeddings. CoRR abs/1908.08572 (2019) - 2018
- [j13]Yike Liu, Tara Safavi, Abhilash Dighe, Danai Koutra:
Graph Summarization Methods and Applications: A Survey. ACM Comput. Surv. 51(3): 62:1-62:34 (2018) - [j12]Geoffrey D. Hannigan, Melissa Beth Duhaime, Danai Koutra, Patrick D. Schloss:
Biogeography and environmental conditions shape bacteriophage-bacteria networks across the human microbiome. PLoS Comput. Biol. 14(4) (2018) - [j11]Yike Liu, Tara Safavi, Neil Shah, Danai Koutra:
Reducing large graphs to small supergraphs: a unified approach. Soc. Netw. Anal. Min. 8(1): 17 (2018) - [c35]Saba A. Al-Sayouri, Ekta Gujral, Danai Koutra, Evangelos E. Papalexakis, Sarah S. Lam:
t-PNE: Tensor-Based Predictable Node Embeddings. ASONAM 2018: 491-494 - [c34]Mark Heimann, Haoming Shen, Tara Safavi, Danai Koutra:
REGAL: Representation Learning-based Graph Alignment. CIKM 2018: 117-126 - [c33]Jie Song, Danai Koutra, Murali Mani, H. V. Jagadish:
GeoAlign: Interpolating Aggregates over Unaligned Partitions. EDBT 2018: 361-372 - [c32]Danai Koutra, Jilles Vreeken, Francesco Bonchi:
Summarizing Graphs at Multiple Scales: New Trends. ICDM 2018: 1097 - [c31]Tara Safavi, Maryam Davoodi, Danai Koutra:
Career Transitions and Trajectories: A Case Study in Computing. KDD 2018: 675-684 - [c30]Mark Heimann, Wei Lee, Shengjie Pan, Kuan-Yu Chen, Danai Koutra:
HashAlign: Hash-Based Alignment of Multiple Graphs. PAKDD (3) 2018: 726-739 - [c29]Yujun Yan, Mark Heimann, Di Jin, Danai Koutra:
Fast Flow-based Random Walk with Restart in a Multi-query Setting. SDM 2018: 342-350 - [c28]Jie Song, Danai Koutra, Murali Mani, H. V. Jagadish:
GeoFlux: Hands-Off Data Integration Leveraging Join Key Knowledge. SIGMOD Conference 2018: 1797-1800 - [i16]Mark Heimann, Haoming Shen, Danai Koutra:
Node Representation Learning for Multiple Networks: The Case of Graph Alignment. CoRR abs/1802.06257 (2018) - [i15]Saba A. Al-Sayouri, Danai Koutra, Evangelos E. Papalexakis, Sarah S. Lam:
SURREAL: SUbgraph Robust REpresentAtion Learning. CoRR abs/1805.01509 (2018) - [i14]Saba A. Al-Sayouri, Ekta Gujral, Danai Koutra, Evangelos E. Papalexakis, Sarah S. Lam:
t-PINE: Tensor-based Predictable and Interpretable Node Embeddings. CoRR abs/1805.01889 (2018) - [i13]Tara Safavi, Maryam Davoodi, Danai Koutra:
Career Transitions and Trajectories: A Case Study in Computing. CoRR abs/1805.06534 (2018) - [i12]Di Jin, Ryan A. Rossi, Danai Koutra, Eunyee Koh, Sungchul Kim, Anup Rao:
Bridging Network Embedding and Graph Summarization. CoRR abs/1811.04461 (2018) - 2017
- [b1]Danai Koutra, Christos Faloutsos:
Individual and Collective Graph Mining: Principles, Algorithms, and Applications. Synthesis Lectures on Data Mining and Knowledge Discovery, Morgan & Claypool Publishers 2017 - [j10]Asso Hamzehei, Shanqing Jiang, Danai Koutra, Raymond K. Wong, Fang Chen:
Topic-based Social Influence Measurement for Social Networks. Australas. J. Inf. Syst. 21 (2017) - [j9]Neil Shah, Danai Koutra, Lisa Jin, Tianmin Zou, Brian Gallagher, Christos Faloutsos:
On Summarizing Large-Scale Dynamic Graphs. IEEE Data Eng. Bull. 40(3): 75-88 (2017) - [j8]Di Jin, Aristotelis Leventidis, Haoming Shen, Ruowang Zhang, Junyue Wu, Danai Koutra:
PERSEUS-HUB: Interactive and Collective Exploration of Large-Scale Graphs. Informatics 4(3): 22 (2017) - [j7]Pravallika Devineni, Danai Koutra, Michalis Faloutsos, Christos Faloutsos:
Facebook wall posts: a model of user behaviors. Soc. Netw. Anal. Min. 7(1): 6:1-6:15 (2017) - [c27]Pravallika Devineni, Evangelos E. Papalexakis, Danai Koutra, A. Seza Dogruöz, Michalis Faloutsos:
One Size Does Not Fit All: Profiling Personalized Time-Evolving User Behaviors. ASONAM 2017: 331-340 - [c26]Amanda J. Minnich, Nikan Chavoshi, Danai Koutra, Abdullah Mueen:
BotWalk: Efficient Adaptive Exploration of Twitter Bot Networks. ASONAM 2017: 467-474 - [c25]Di Jin, Danai Koutra:
Exploratory Analysis of Graph Data by Leveraging Domain Knowledge. ICDM 2017: 187-196 - [c24]Tara Safavi, Chandra Sekhar Sripada, Danai Koutra:
Scalable Hashing-Based Network Discovery. ICDM 2017: 405-414 - [c23]Danai Koutra:
Inferring, Summarizing and Mining Multi-source Graph Data. ICDM Workshops 2017: 978 - [c22]Danai Koutra, Abhilash Dighe, Smriti Bhagat, Udi Weinsberg, Stratis Ioannidis, Christos Faloutsos, Jean Bolot:
PNP: Fast Path Ensemble Method for Movie Design. KDD 2017: 1527-1536 - [c21]Oshini Goonetilleke, Danai Koutra, Timos Sellis, Kewen Liao:
Edge Labeling Schemes for Graph Data. SSDBM 2017: 12:1-12:12 - [i11]Josh Gardner, Danai Koutra, Jawad Mroueh, Victor Pang, Arya Farahi, Sam Krassenstein, Jared Webb:
Driving with Data: Modeling and Forecasting Vehicle Fleet Maintenance in Detroit. CoRR abs/1710.06839 (2017) - 2016
- [j6]Miguel Araujo, Stephan Günnemann, Spiros Papadimitriou, Christos Faloutsos, Prithwish Basu, Ananthram Swami, Evangelos E. Papalexakis, Danai Koutra:
Discovery of "comet" communities in temporal and labeled graphs Com^2. Knowl. Inf. Syst. 46(3): 657-677 (2016) - [j5]Danai Koutra, Neil Shah, Joshua T. Vogelstein, Brian Gallagher, Christos Faloutsos:
DeltaCon: Principled Massive-Graph Similarity Function with Attribution. ACM Trans. Knowl. Discov. Data 10(3): 28:1-28:43 (2016) - [c20]Jinyeong Yim, Jeel Jasani, Aubrey Henderson, Danai Koutra, Steven Dow, Winnie Leung, Ellen Lim, Mitchell L. Gordon, Jeffrey P. Bigham, Walter S. Lasecki:
Coding Varied Behavior Types Using the Crowd. CSCW Companion 2016: 114-117 - [c19]Venkata Krishna Pillutla, Zhanpeng Fang, Pravallika Devineni, Christos Faloutsos, Danai Koutra, Jie Tang:
On Skewed Multi-dimensional Distributions: the FusionRP Model, Algorithms, and Discoveries. SDM 2016: 783-791 - [i10]Pin-Yu Chen, Chun-Chen Tu, Pai-Shun Ting, Ya-Yun Lo, Danai Koutra, Alfred O. Hero III:
Identifying Influential Links for Event Propagation on Twitter: A Network of Networks Approach. CoRR abs/1609.05378 (2016) - [i9]Danai Koutra, Abhilash Dighe, Smriti Bhagat, Udi Weinsberg, Stratis Ioannidis, Christos Faloutsos, Jean Bolot:
PNP: Fast Path Ensemble Method for Movie Design. CoRR abs/1611.02388 (2016) - [i8]Yike Liu, Abhilash Dighe, Tara Safavi, Danai Koutra:
A Graph Summarization: A Survey. CoRR abs/1612.04883 (2016) - 2015
- [j4]Leman Akoglu, Hanghang Tong, Danai Koutra:
Graph based anomaly detection and description: a survey. Data Min. Knowl. Discov. 29(3): 626-688 (2015) - [j3]Wolfgang Gatterbauer, Stephan Günnemann, Danai Koutra, Christos Faloutsos:
Linearized and Single-Pass Belief Propagation. Proc. VLDB Endow. 8(5): 581-592 (2015) - [j2]Danai Koutra, Di Jin, Yuanshi Ning, Christos Faloutsos:
Perseus: An Interactive Large-Scale Graph Mining and Visualization Tool. Proc. VLDB Endow. 8(12): 1924-1927 (2015) - [j1]Danai Koutra, U Kang, Jilles Vreeken, Christos Faloutsos:
Summarizing and understanding large graphs. Stat. Anal. Data Min. 8(3): 183-202 (2015) - [c18]Pravallika Devineni, Danai Koutra, Michalis Faloutsos, Christos Faloutsos:
If walls could talk: Patterns and anomalies in Facebook wallposts. ASONAM 2015: 367-374 - [c17]Neil Shah, Danai Koutra, Tianmin Zou, Brian Gallagher, Christos Faloutsos:
TimeCrunch: Interpretable Dynamic Graph Summarization. KDD 2015: 1055-1064 - [c16]Danai Koutra, Paul N. Bennett, Eric Horvitz:
Events and Controversies: Influences of a Shocking News Event on Information Seeking. WWW 2015: 614-624 - [i7]Yike Liu, Neil Shah, Danai Koutra:
An Empirical Comparison of the Summarization Power of Graph Clustering Methods. CoRR abs/1511.06820 (2015) - 2014
- [c15]Miguel Araujo, Spiros Papadimitriou, Stephan Günnemann, Christos Faloutsos, Prithwish Basu, Ananthram Swami, Evangelos E. Papalexakis, Danai Koutra:
Com2: Fast Automatic Discovery of Temporal ('Comet') Communities. PAKDD (2) 2014: 271-283 - [c14]U Kang, Jay Yoon Lee, Danai Koutra, Christos Faloutsos:
Net-Ray: Visualizing and Mining Billion-Scale Graphs. PAKDD (1) 2014: 348-361 - [c13]Yibin Lin, Agha Ali Raza, Jay Yoon Lee, Danai Koutra, Roni Rosenfeld, Christos Faloutsos:
Influence Propagation: Patterns, Model and a Case Study. PAKDD (1) 2014: 386-397 - [c12]Danai Koutra, U Kang, Jilles Vreeken, Christos Faloutsos:
VOG: Summarizing and Understanding Large Graphs. SDM 2014: 91-99 - [c11]Walter S. Lasecki, Mitchell L. Gordon, Danai Koutra, Malte F. Jung, Steven P. Dow, Jeffrey P. Bigham:
Glance: rapidly coding behavioral video with the crowd. UIST 2014: 551-562 - [i6]Leman Akoglu, Hanghang Tong, Danai Koutra:
Graph-based Anomaly Detection and Description: A Survey. CoRR abs/1404.4679 (2014) - [i5]Danai Koutra, Paul N. Bennett, Eric Horvitz:
Events and Controversies: Influences of a Shocking News Event on Information Seeking. CoRR abs/1405.1486 (2014) - [i4]Danai Koutra, U Kang, Jilles Vreeken, Christos Faloutsos:
VoG: Summarizing and Understanding Large Graphs. CoRR abs/1406.3411 (2014) - [i3]Wolfgang Gatterbauer, Stephan Günnemann, Danai Koutra, Christos Faloutsos:
Linearized and Turbo Belief Propagation. CoRR abs/1406.7288 (2014) - 2013
- [c10]