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Learning over structured data
The
world is structured,
not IID. Accounting for relations often improve prediction. Sub-areas:
- Rank and permutation
- Undirected graphical
models
- Multiways
- Sequences &
hierarchies
- Graphs
Publications
- Relational dynamic memory networks, Trang Pham, Truyen Tran, Svetha Venkatesh, arXiv preprint arXiv:1808.04247
- Learning regularity in skeleton trajectories for anomaly detection in videos, Romero Morais, Vuong Le, Budhaditya Saha, Truyen Tran, Moussa Reda Mansour, Svetha Venkatesh, CVPR'19.
- Graph transformation policy network for chemical reaction prediction, Kien Do, Truyen Tran, Svetha Venkatesh, KDD'19.
- Lessons
learned from using a deep tree-based model for software defect
prediction in practice, HK Dam, T Pham, SW Ng, T Tran, J Grundy, A
Ghose, T Kim, CJ
Kim, MSR'19.
- Neural reasoning for chemical-chemical interaction. Trang Pham, Truyen Tran,
Svetha Venkatesh, NIPS 2018 Workshop on Machine Learning for Molecules and Materials.
- Attentional multilabel learning over graphs: A message passing approach, K Do, T Tran, T Nguyen, S Venkatesh, Machine Learning, 2019
- Knowledge Graph Embedding with Multiple Relation Projections, K Do, T Tran, S Venkatesh, ICPR'18.
- Resset: A Recurrent Model for Sequence of Sets with Applications to Electronic Medical Records, P Nguyen, T Tran, S Venkatesh, IJCNN'18.
- Graph Memory Networks for Molecular Activity Prediction, Trang Pham, Truyen Tran, Svetha Venkatesh, ICPR'18.
- Prelim version appears at NIPS Workshop on Deep learning for physical sciences, 2017.
- Graph Classification via Deep
Learning with Virtual Nodes Trang Pham, Truyen Tran, Hoa Dam, Svetha
Venkatesh, Third Representation
Learning for Graphs Workshop (ReLiG 2017).
- Preference
Relation-based Markov Random Fields in Recommender Systems,
Shaowu Liu, Gang Li,Truyen
Tran, Jiang Yuan. Machine Learning,
DOI 10.1007/s10994-016-5603-7. (This
is an extension of the ACML'15 paper).
- Column
Networks for Collective Classification, T Pham, T Tran, D Phung, S
Venkatesh, AAAI'17
- Graph-induced restricted
Boltzmann machines for document modeling, Tu D.
Nguyen, Truyen Tran,
D.
Phung, and S. Venkatesh, Information
Sciences.
doi: 10.1016/j.ins.2015.08.023
- Neural
Choice by Elimination via Highway Networks, Truyen Tran, Dinh
Phung and Svetha Venkatesh, PAKDD workshop on Biologically
Inspired Techniques for Data Mining (BDM'16), April 19-22
2016, Auckland, NZ.
- Collaborative filtering
via sparse Markov random fields, Truyen Tran, Dinh
Phung, Svetha Venkatesh, Information
Science, doi:10.1016/j.ins.2016.06.027.
- Hierarchical semi-Markov
conditional random fields for deep recursive sequential data,
Truyen Tran,
Dinh Phung, Hung Bui, Svetha Venkatesh, Artificial Intelligence,
Volume 246, May 2017, Pages 53–85. (Extension of the NIPS'08 paper).
- Preference
Relation-based Markov Random Fields in Recommender Systems,
Shaowu Liu, Gang Li,Truyen
Tran, Jiang Yuan, ACML'15, November 20-22, 2015, Hong
Kong.
- Predicting delays in
software projects using networked classification,
Morakot Choetikertikul, Hoa Khanh Dam, Truyen Tran, Aditya
Ghose, 30th IEEE/ACM
International Conference on Automated Software Engineering,
November 9–13, 2015 Lincoln, Nebraska, USA.
- Stabilizing
Sparse Cox
Model using Statistic and Semantic Structures in Electronic Medical
Records. Shivapratap
Gopakumar, Tu Dinh Nguyen, Truyen
Tran, Dinh
Phung, and Svetha Venkatesh,
PAKDD'15,
HCM City, Vietnam, May 2015. Won Best
Student Paper Runner-up.
- Modelling
Human Preferences for Ranking and Collaborative Filtering: A
Probabilistic Ordered Partition Approach, Truyen
Tran,
D.
Phung, and S. Venkatesh (extension of the SDM'11
paper). Knowledge
and Information
Systems, May
13, 2015, DOI: 10.1007/s10115-015-0840-9
- Learning
vector
representation of medical objects via EMR-driven nonnegative restricted
Boltzmann machines (e-NRBM),
Truyen Tran,
Tu
D. Nguyen, D.
Phung, and S. Venkatesh, Journal
of Biomedical Informatics, 2015, pii:
S1532-0464(15)00014-3. doi: 10.1016/j.jbi.2015.01.012.
- Tensor-variate
Restricted Boltzmann Machines, Tu D. Nguyen, Truyen Tran, D.
Phung, and S. Venkatesh, AAAI
2015.
- Tree-based
Iterated Local Search for Markov Random Fields with Applications in
Image Analysis, Truyen
Tran, Dinh Phung and Svetha Venkatesh, Journal of Heuristics,
2014, DOI:10.1007/s10732-014-9270-1
- Stabilizing
high-dimensional
prediction models using feature graphs, Shivapratap
Gopakumar, Truyen Tran,
Tu Dinh Nguyen, Dinh Phung, and Svetha Venkatesh, IEEE Journal of
Biomedical and
Health Informatics, 2014
DOI:10.1109/JBHI.2014.2353031S
- Ordinal
random fields for recommender systems, Shaowu Liu,
Truyen Tran,
Gang Li, Yuan Jiang, ACML'14,
Nha Trang,
Vietnam, Nov 2014.
- Stabilizing
sparse Cox model using clinical structures in electronic medical records,
S Gopakumar, Truyen Tran,
D Phung, S Venkatesh, 2nd
International Workshop on Pattern Recognition for Healthcare Analytics,
August 2014
- Stabilized
sparse ordinal regression for medical risk stratification,
Truyen Tran,
Dinh
Phung, Wei Luo, and Svetha Venkatesh, Knowledge and Information
Systems,
2014, DOI: 10.1007/s10115-014-0740-4.
- Learning
from Ordered Sets and
Applications in Collaborative Ranking,
Truyen Tran,
Dinh Phung and
Svetha Venkatesh, in Proc.
of. the 4th Asian Conference on
Machine Learning (ACML2012), Singapore, Nov 2012.
- Cumulative
Restricted
Boltzmann Machines for Ordinal Matrix Data Analysis,
Truyen Tran,
Dinh Phung and
Svetha Venkatesh, in Proc.
of. the 4th Asian Conference on
Machine Learning (ACML2012), Singapore, Nov 2012.
- A
Sequential Decision Approach
to Ordinal Preferences in Recommender Systems, Truyen
Tran, Dinh Phung, Svetha Venkatesh, in Proc.
of 25-th Conference on Artificial Intelligence (AAAI-12),
Toronto,
Canada, July 2012.
- Probabilistic
Models over Ordered Partitions with Applications in Document Ranking
and Collaborative Filtering
T. Truyen,
D.
Phung, and S. Venkatesh, in Proc.
of SIAM Int. Conf. on Data
Mining (SDM11), April, Arizona, USA, 2011
- MCMC
for Hierarchical
Semi-Markov Conditional Random Fields, Truyen Tran,
Dinh Q. Phung, Svetha Venkatesh and Hung H. Bui. In NIPS'09
Workshop on Deep Learning for Speech
Recognition and Related Applications. December, 2009,
Whistler, BC, Canada.
- Ordinal
Boltzmann Machines for
Collaborative Filtering. Truyen
Tran, Dinh Q. Phung and Svetha Venkatesh. In
Proc. of 25th
Conference on Uncertainty in Artificial Intelligence,
June, 2009, Montreal, Canada. Runner-up
for the best paper award.
- Hierarchical
Semi-Markov
Conditional Random Fields for Recursive Sequential Data,
Truyen
Tran, Dinh Q. Phung, Hung H. Bui, and Svetha Venkatesh.
In Proc.
of 21st
Annual Conference on Neural Information Processing Systems,
Dec 2008, Vancouver, Canada. [See technical
report
and thesis
for more
details and
extensions.]
- Constrained
Sequence
Classification for Lexical Disambiguation, Truyen
Tran, Dinh Q. Phung and Svetha Venkatesh. In Proc.
of 10th Pacific Rim International Conference on Artificial Intelligence
(PRICAI-08), 15-19 Dec 2008, Hanoi, Vietnam.
- Learning
Discriminative
Sequence Models from Partially Labelled Data for Activity Recognition,
Truyen
Tran, Hung Hai Bui, Dinh Q. Phung and Svetha Venkatesh.
In Proc. of 10th
Pacific Rim
International Conference on Artificial Intelligence
(PRICAI-08), 15-19 Dec 2008, Hanoi, Vietnam.
-
Preference
Networks:
probabilistic models for recommendation systems, Truyen
Tran, Dinh Q. Phung and Svetha Venkatesh, In Proc.
of 6th Australasian Data Mining Conference: AusDM 2007,
3-4
Dec, Gold Coast, Australia.
-
AdaBoost.MRF:
Boosted Markov
random forests and application to multilevel activity recognition,
Truyen
Tran, Dinh Quoc Phung, Hung Hai Bui,
and Svetha Venkatesh. In Proc.
of IEEE Conference
on Computer Vision and Pattern Recognition,
volume Volume 2, pages 1686-1693, New York, USA, June 2006.
- Boosted
Markov networks for activity recognition, Truyen Tran,
Hung Hai Bui and Svetha Venkatesh, In Proc. of International
Conference on Intelligent Sensors, Sensor Networks and Information
Processing (ISSNIP2005), 5-8 Dec, Melbourne, Australia.
- Human
Activity Learning and Segmentation using Partially Hidden
Discriminative Models, Truyen Tran,
Hung Hai Bui and Svetha Venkatesh, HAREM
2005: Proceedings of the International Workshop on Human Activity
Recognition.
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