Xuan-Hong Dang

Publication Activity (10 Years)

Years Active: 2006-2024
Publications (10 Years): 22

Top Topics

Multivariate Time Series

Temporal Dependencies

Alternative Clusterings

Top Venues

Publications

Matt Stallone, Vaibhav Saxena, Leonid Karlinsky, Bridget McGinn, Tim Bula, Mayank Mishra, Adriana Meza Soria, Gaoyuan Zhang, Aditya Prasad, Yikang Shen, Saptha Surendran, Shanmukha C. Guttula, Hima Patel, Parameswaran Selvam, Xuan-Hong Dang, Yan Koyfman, Atin Sood, Rogério Feris, Nirmit Desai, David D. Cox, Ruchir Puri, Rameswar Panda
Scaling Granite Code Models to 128K Context. CoRR (2024)
Mayank Mishra, Matt Stallone, Gaoyuan Zhang, Yikang Shen, Aditya Prasad, Adriana Meza Soria, Michele Merler, Parameswaran Selvam, Saptha Surendran, Shivdeep Singh, Manish Sethi, Xuan-Hong Dang, Pengyuan Li, Kun-Lung Wu, Syed Zawad, Andrew Coleman, Matthew White, Mark Lewis, Raju Pavuluri, Yan Koyfman, Boris Lublinsky, Maximilien de Bayser, Ibrahim Abdelaziz, Kinjal Basu, Mayank Agarwal, Yi Zhou, Chris Johnson, Aanchal Goyal, Hima Patel, S. Yousaf Shah, Petros Zerfos, Heiko Ludwig, Asim Munawar, Maxwell Crouse, Pavan Kapanipathi, Shweta Salaria, Bob Calio, Sophia Wen, Seetharami Seelam, Brian Belgodere, Carlos A. Fonseca, Amith Singhee, Nirmit Desai, David D. Cox, Ruchir Puri, Rameswar Panda
Granite Code Models: A Family of Open Foundation Models for Code Intelligence. CoRR (2024)
Adrian Shuai Li, Elisa Bertino, Xuan-Hong Dang, Ankush Singla, Yuhai Tu, Mark N. Wegman
Maximal Domain Independent Representations Improve Transfer Learning. CoRR (2023)
Hajar Emami, Xuan-Hong Dang, S. Yousaf Shah, Petros Zerfos
Modality-aware Transformer for Time series Forecasting. CoRR (2023)
Syed Yousaf Shah, Dhaval Patel, Long Vu, Xuan-Hong Dang, Bei Chen, Peter Kirchner, Horst Samulowitz, David Wood, Gregory Bramble, Wesley M. Gifford, Giridhar Ganapavarapu, Roman Vaculín, Petros Zerfos
AutoAI-TS: AutoAI for Time Series Forecasting. CoRR (2021)
Syed Yousaf Shah, Dhaval Patel, Long Vu, Xuan-Hong Dang, Bei Chen, Peter Kirchner, Horst Samulowitz, David Wood, Gregory Bramble, Wesley M. Gifford, Giridhar Ganapavarapu, Roman Vaculín, Petros Zerfos
AutoAI-TS: AutoAI for Time Series Forecasting. SIGMOD Conference (2021)
Xuan-Hong Dang, Syed Yousaf Shah, Petros Zerfos
"The Squawk Bot": Joint Learning of Time Series and Text Data Modalities for Automated Financial Information Filtering. IJCAI (2020)
Xuan-Hong Dang, Syed Yousaf Shah, Petros Zerfos
"The Squawk Bot": Joint Learning of Time Series and Text Data Modalities for Automated Financial Information Filtering. CoRR (2019)
Xuan-Hong Dang, Syed Yousaf Shah, Petros Zerfos
seq2graph: Discovering Dynamic Non-linear Dependencies from Multivariate Time Series. IEEE BigData (2019)
Xuan-Hong Dang, Omid Askarisichani, Ambuj K. Singh
Learning Multiclassifiers with Predictive Features that Vary with Data Distribution. IEEE BigData (2018)
Xuan-Hong Dang, Raji Akella, Somaieh Bahrami, Vadim Sheinin, Petros Zerfos
Unsupervised Threshold Autoencoder to Analyze and Understand Sentence Elements. IEEE BigData (2018)
Syed Yousaf Shah, Xuan-Hong Dang, Petros Zerfos
Root Cause Detection using Dynamic Dependency Graphs from Time Series Data. IEEE BigData (2018)
Xuan-Hong Dang, Syed Yousaf Shah, Petros Zerfos
seq2graph: Discovering Dynamic Dependencies from Multivariate Time Series with Multi-level Attention. CoRR (2018)
Xuan-Hong Dang, Hongyuan You, Ambuj K. Singh, Scott T. Grafton
Subnetwork Mining with Spatial and Temporal Smoothness. SDM (2017)
Minh X. Hoang, Xuan-Hong Dang, Xiang Wu, Zhenyu Yan, Ambuj K. Singh
GPOP: Scalable Group-level Popularity Prediction for Online Content in Social Networks. WWW (2017)
Arlei Silva, Xuan-Hong Dang, Prithwish Basu, Ambuj K. Singh, Ananthram Swami
Graph Wavelets via Sparse Cuts. KDD (2016)
Xuan-Hong Dang, Arlei Silva, Ambuj K. Singh, Ananthram Swami, Prithwish Basu
Outlier Detection from Network Data with Subnetwork Interpretation. CoRR (2016)
Arlei Silva, Xuan-Hong Dang, Prithwish Basu, Ambuj K. Singh, Ananthram Swami
Graph Wavelets via Sparse Cuts. CoRR (2016)
Xuan-Hong Dang, Arlei Silva, Ambuj K. Singh, Ananthram Swami, Prithwish Basu
Outlier Detection from Network Data with Subnetwork Interpretation. ICDM (2016)
Xuan-Hong Dang, James Bailey
A framework to uncover multiple alternative clusterings. Mach. Learn. 98 (1-2) (2015)
Xuan-Hong Dang, Hongyuan You, Petko Bogdanov, Ambuj K. Singh
Learning Predictive Substructures with Regularization for Network Data. ICDM (2015)
Xuan-Hong Dang, Ambuj K. Singh, Petko Bogdanov, Hongyuan You, Bayyuan Hsu
Discriminative Subnetworks with Regularized Spectral Learning for Global-state Network Data. CoRR (2015)
Xuan-Hong Dang, James Bailey
Generating multiple alternative clusterings via globally optimal subspaces. Data Min. Knowl. Discov. 28 (3) (2014)
Dong-Anh Nguyen, Tarek F. Abdelzaher, Steven A. Borbash, Xuan-Hong Dang, Raghu K. Ganti, Ambuj K. Singh, Mudhakar Srivatsa
On Critical Event Observability Using Social Networks: A Disaster Monitoring Perspective. MILCOM (2014)
Xuan-Hong Dang, Ira Assent, Raymond T. Ng, Arthur Zimek, Erich Schubert
Discriminative features for identifying and interpreting outliers. ICDE (2014)
Xuan-Hong Dang, Ambuj K. Singh, Petko Bogdanov, Hongyuan You, Bayyuan Hsu
Discriminative Subnetworks with Regularized Spectral Learning for Global-State Network Data. ECML/PKDD (1) (2014)
Ira Assent, Xuan-Hong Dang, Barbora Micenková, Raymond T. Ng
Outlier Detection with Space Transformation and Spectral Analysis. SDM (2013)
Xuan-Hong Dang, Barbora Micenková, Ira Assent, Raymond T. Ng
Local Outlier Detection with Interpretation. ECML/PKDD (3) (2013)
Barbora Micenková, Raymond T. Ng, Xuan-Hong Dang, Ira Assent
Explaining Outliers by Subspace Separability. ICDM (2013)
Xuan-Hong Dang, Ira Assent, James Bailey
Multiple Clustering Views via Constrained Projections. MultiClust@SDM (2012)
Xuan-Hong Dang, Kok-Leong Ong, Vincent C. S. Lee
An Adaptive Algorithm for Finding Frequent Sets in Landmark Windows. SUM (2012)
Xuan-Hong Dang, James Bailey
A hierarchical information theoretic technique for the discovery of non linear alternative clusterings. KDD (2010)
Xuan-Hong Dang, James Bailey
Generation of Alternative Clusterings Using the CAMI Approach. SDM (2010)
Li Wan, Wee Keong Ng, Xuan-Hong Dang, Philip S. Yu, Kuan Zhang
Density-based clustering of data streams at multiple resolutions. ACM Trans. Knowl. Discov. Data 3 (3) (2009)
Xuan-Hong Dang, Vincent C. S. Lee, Wee Keong Ng, Arridhana Ciptadi, Kok-Leong Ong
An EM-Based Algorithm for Clustering Data Streams in Sliding Windows. DASFAA (2009)
Xuan-Hong Dang, Vincent C. S. Lee, Wee Keong Ng, Kok-Leong Ong
Incremental and Adaptive Clustering Stream Data over Sliding Window. DEXA (2009)
Xuan-Hong Dang, Wee Keong Ng, Kok-Leong Ong
Online mining of frequent sets in data streams with error guarantee. Knowl. Inf. Syst. 16 (2) (2008)
Xuan-Hong Dang, Wee Keong Ng, Kok-Leong Ong, Vincent C. S. Lee
Discovering Frequent Sets from Data Streams with CPU Constraint. AusDM (2007)
Xuan-Hong Dang, Wee Keong Ng, Kok-Leong Ong
EStream: Online Mining of Frequent Sets with Precise Error Guarantee. DaWaK (2006)
Xuan-Hong Dang, Wee Keong Ng, Kok-Leong Ong
Adaptive Load Shedding for Mining Frequent Patterns from Data Streams. DaWaK (2006)