Software Bridge Engineering.
Pradnya Desai, Phung Lai, NhatHai Phan, and My T. Thai.
Han Hu*, Xiaopeng Jiang*, Vijaya Datta Mayyuri, An Chen, Devu M. Shila, Adriaan Larmuseau, Ruoming Jin, Cristian Borcea, and NhatHai Phan. NhatHai Phan, David Kil, Brigitte Piniewski, and Dejing Dou.
success of previous ICMLA conferences, the conference aims to attract researchers and NhatHai Phan, Xintao Wu, Dejing Dou.
A research project that encompasses storytelling, a democratic decision making platform, a city model, and an immersive exhibit.
Research Lab, Barcelona, Spain 05/2013 08/2013, With the success of online social networks and microblogs such as Facebook, Flickr and Twitter, the phenomenon of influence exerted by users of such platforms on other users, and how it propagates in the network, has recently attracted the interest of computer scientists, information technologists, and marketing specialists. Extracting API Tips from Developer Question and Answer Websites. International Journal of Pattern Recognition and Artificial Intelligence, doi:10.1142/S0218001420520102. NhatHai Phan, and Hyoseop Shin. 5-Year IF = 10.47 [pdf] [code], SRBM+: Human Behavior Prediction with Explanations in a Health Social Network.
We offer a variety of membership categories to serve the needs of association professionals and vendors to the association community.
Invited talk at American Family Insurance, Madison, Wisconsin, USA, July 2015. IF = 1.664 [pdf] [demo] [code], Ontology-based Deep Learning for Human Behavior Prediction in Health Social Networks.
Guanxiong Liu, Issa Khalil, Abdallah Khreishah, and NhatHai Phan. Paper 2:Machine Learning Algorithms for Classification of Microcirculation Images from Septic and Non-Septic PatientsPerikumar Javia, Aman Rana, Nathan Shapiro, Pratik Shah, 12/19/18, 2:00-3:20pm, full paper and invited talk. We report a machine learning classifier capable of distinguishing non-septic and septic images from dark field microcirculation videos of patients.
[pdf]. Proceedings of the 6th ACM Conference on Bioinformatics, Computational Biology and Health Informatics (ACM BCB 2015), Atlanta, GA, September 2015. CIKM Conference Talk, Shanghai, China, December 2014. [pdf] [Github] (acceptance rate: 105 / 590), Adaptive Laplace Mechanism: Differential Privacy Preservation in Deep Learning. [pdf] [demo] [code] (acceptance rate: 11.3%), Co2Vis: A Visual Analytics Tool for Mining Co-expressed And Co-regulated Genes Implied in HIV Infections. games, are especially encouraged.
Model Transferring Attacks to Backdoor HyperNetwork in Personalized Federated Learning.
If you are already a member, simply click the first option below to access your accountand enter the email we have on file for you to begin taking advantage of your membership.
Donate to the Lab, Helping Emergency Care Physicians Diagnose Sepsis and Bacterial Infections with Machine Learning and Vision, AI Methods for Rapid Automated Staining and Destaining of Tissue Biopsies in Hospitals. [pdf] [Slides] [code] (Invited Article), Interaction Network Representations for Human Behavior Prediction.
NhatHai Phan, Yue Wang, Xintao Wu, and Dejing Dou. Computation Social Network - Springer, 2019.
NhatHai Phan, Minh Vu, Yang Liu, Ruoming Jin, Xintao Wu, Dejing Dou, and My T. Thai.
OnML: An Ontology-based Approach for Interpretable Machine Learning. Proceedings of 10th Conference on Science and Technology, HCM University of Technology, Ho Chi Minh city, Vietnam, October 2007. as well as other Abstracting and Indexing (A&I) databases. The 7th International Workshop on Information Search, Integration and Personalization (ISIP 2012), Sapporo, Japan, October 2012. [pdf] [Github] (acceptance rate: 9.25% = 72 / 778), Importance Sketching of Influence Dynamics in Billion-scale Networks. This Design Justice Pedagogy Summit and overarching project is motivated by the pressing need to center and incorporate principles of ethic, Accessibility
DPNE: Differentially Private Network Embedding.
Differentially Private Lifelong Learning. In Proceedings of the 8th International Conference on Advanced Data Mining and Applications (ADMA 2012), Nanjing, China, December 2012.
Authors names and affiliations should not appear in the submitted paper.
The maximum length of papers is 8 pages. Han Hu, NhatHai Phan*, James Geller, Stephen Iezzi, Huy Vo, Soon Ae Chun.
[link] [vimeo], An Efficient Spatio-Temporal Mining Approach to Really Know Who Travels with Whom!
Abdallah Khreishah, Issa Khalil, and Xintao Wu.
ACM Transactions on Intelligent Systems and Technology (ACM TIST), 2016.
It is advisable to check the official website for all the deadlines. 30th IEEE International Conference on Tools with Artificial Intelligence, Velos, Greece, November 2018.
ICSDM Conference Talk, Fuzhou China, June 2011.
NhatHai Phan, Dino Ienco, Donato Malerba, Pascal Poncelet, and Maguelonne Teisseire.
Invited to The 7th International Conference on Computational Data & Social Networks (CSoNet'18), Shanghai, China, December 2018.
Classification of Ecological Data by Deep Learning. APWeb Conference Talk, Busan, Korea, April 2010. Research Lab, Prof. Bruno Crmilleux - Universit de Caen, Human Behavior Modeling in Health Social Networks. NhatHai Phan, Hoang Van Duc Thong, and Hyoseop Shin. Imaging of microcirculatory dysfunction is a promising approach for automated diagnosis of sepsis. The 17th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD 2013), Goal Coast, Australia, April 2013.
We report two novel approaches for training machine learning models for the computational H&E staining and destaining of prostate core biopsy RGB images.
problems and interdisciplinary research involving machine learning, in fields like
Proceedings of the 15th IEEE International Conference on Machine Learning and Applications (IEEE ICMLA'16), Anaheim, California, USA, December 18-20, 2016. The Well-Dressed Spacecraft: Textiles for Cosmic Dust Metrology. Spoofing fan detection on social media communities. IF = 3.557 [pdf].
Its a 4 days event starting on Dec 13, 2021 (Monday) and will be winded up on Dec 16, 2021 (Thursday).
[pdf] [demo] [code], An Efficient Spatio-Temporal Mining Approach to Really Know Who Travels with Whom!
International Journal of Environmental Research and Public Health (ISSN 1660-4601).
(* corresponding author). Hochiminh University of Technology Scholarship for good student, 2006-2007.
NhatHai Phan, Pascal Poncelet, and Maguelonne Teisseire. The conference will cover both machine learning theoretical research and its
Papers submitted for review should conform to IEEE specifications.
To speed up the growing of number of fans, some of them buy spoofing fans from fan suppliers. [pdf] [Github] Dataset released: 5,000 drug abuse risk behavior labeled tweets has been released at: https://github.com/hu7han73/DrugAbuseLabeledTweets. We use cookies to offer you a better browsing experience, "recognize" returning INSNA members, and analyze site traffic. Knowledge Representation & Reasoning Meets Machine Learning (KR2ML) Workshop at NeurIPS'19, December 8-14, 2019, Vancouver, Canada. The 37th International Conference on Machine Learning (ICML'20), July 12 - 18, 2020.
Han Hu, NhatHai Phan*, Xinyue Ye, Ruoming Jin, Kele Ding, Dejing Dou, and Huy T. Vo.
Conference content will be submitted for inclusion into IEEE Xplore The 8th International Conference on Computational Data & Social Networks (CSoNet'19), Hochiminh City, Vietnam, November 2019. The 10th International Conference on Computational Data and Social Networks (CSoNet'21), November 15 - 17, 2021.
IEEE International Conference on Big Data (IEEE BigData'21), December 15-18, 2021.
[1] ICMLA 2021 : 20th IEEE International Conference on Machine Learning and Applications.
Upon acceptance, authors should submit the final version of the manuscript on or before Oct 01, 2021 to the official website of the Conference. (* corresponding author), Lifelong DP: Consistently Bounded Differential Privacy in Lifelong Machine Learning.
[pdf], A 3D Atrous Convolutional Long Short-Term Memory Network for Background Subtraction.
NhatHai Phan, Javid Ebrahimi, Dejing Dou, David Kil, and Brigitte Piniewski. Javid Ebrahimi, NhatHai Phan, Dejing Dou, Brigitte Piniewski, and David Kil.
NhatHai Phan, Dino Ienco, Pascal Poncelet, and Maguelonne Teisseire.
Proceedings of the 23rd ACM Conference on Information and Knowledge Management (CIKM 2014), Shanghai, China, November 2014.
[pdf] (acceptance rate: 16%), An Empirical Analysis of User Clusters in Online Communities. NhatHai Phan, Hoang Anh Nguyen, Minh Quang Tran, Hoang Hai Ly, and Tran Khanh Dang.
NhatHai Phan, Dejing Dou, Hao Wang, David Kil, and Brigitte Piniewski. Han Hu, Pravani Moturu, Kannan Neten Dharan, James Geller, Sophie Di Iorio, NhatHai Phan*, Huy Vo, Soon Ae Chun. , Proceedings of Machine Learning Research (.
[pdf] [Slides] [code] (acceptance rate: 21.9%), Analysis of Physical Activity Propagation in a Health Social Network. International Journal of Information Technology & Decision Making (IJITDM), 2016. NhatHai Phan, Javid Ebrahimi, Brigitte Piniewski, David Kil, and Dejing Dou.
(Invited to IEEE J-BHI) [pdf] [Slides] [code] (Selected as Best Papers), Social Restricted Boltzmann Machine: Human Behavior Prediction in Health Social Networks.
The classifier achieves an accuracy of 89.45%.
Machine Learning 2017, ECML-PKDD Journal Track, Skopje, Macedonia 18-22 Sep 2017.
PAKDD'18, Melbourne, Australia, June 2018.
Ingnierie des Systmes d'Information (special issue, selected from BDA12), 2013.
, David Kil, Brigitte Piniewski, and Dejing Dou.
[Slides].
(Selected as Best Papers).
Research on designing communication method between traffic card and client server.
Van Duc Thong Hoang, NhatHai Phan, and Hyoseop Shin.
Journal of Combinatorial Optimization - Springer. This special session will also serve as a common ground to build collaborations, share datasets, and inspire machine learning on graphs research in areas where there are limitations in the existing approaches. provides a leading international forum for the dissemination of original research in ML,
Information about your use of this site is shared with Google.
Manuscript templates can be downloaded from the IEEE website.
ECML-PKDD Conference Talk, Bristol, UK, September 2012.
Outstanding Vietnamese Research Award of Montpellier, France, 2012. Authors of the best papers from this special session will be invited to extend their work and publish it in selected journals (SNAM, Applied Network Science, and Journal of Intelligent and Information Systems).Scope:We welcome novel research papers on the following algorithms and applications, including but not limited to: 2900 Delk Road Suite 700, PMB 321Marietta, GA 30067USA. IF = 2.9 [pdf] [Github] Arxiv version (acceptance rate: 13.5%), Ontology-based Deep Learning for Human Behavior Prediction with Explanations in Health Social Networks.
Hematoxylin and eosin stain (H&E) is one of the principal stains in histology but suffers from several shortcomings related to tissue preparation, staining protocols, slowness and human error.
[pdf].
Amnay Amimeur, NhatHai Phan, Dejing Dou, Brigitte Piniewski, and David Kil. [Slides], Mining Fuzzy Moving Object Clusters.
The 12th International Asia-Pacific Web Conference (APWeb 2010), Busan, Korea, April 2010.
In Proceedings of the 11th International Symposium on Intelligent Data Analysis (IDA 2012), Helsinki, Finland, October 2012.
(Invited Paper), Scalable Differential Privacy with Certified Robustness in Adversarial Learning. NhatHai Phan, Dejing Dou, David Kil, and Brigitte Piniewski.
Hung Nguyen, Tri Nguyen, NhatHai Phan, Thang Dinh. Graphs or networks are ubiquitous structures that appear in a multitude of complex systems like social networks, biological networks, knowledge graphs, the world wide web, transportation networks, and many more.
Arxiv 2021. NhatHai Phan, Pascal Poncelet, and Maguelonne Teisseire.
[pdf], Ontology-based Interpretable Machine Learning with Learnable Anchors. The proposed staining and destaining models can engender computational H&E staining and destaining of WSRI biopsies without additional equipment and devices.
Shaobo Liu, Frank Y. Shih, Gareth Russell, Kimberly Russell, and NhatHai Phan. Proceedings of the 30th AAAI Conference on Artificial Intelligence (AAAI-16), Phoenix, Arizona, USA, February 2016.
The International Joint Conference on Neural Networks (IJCNN'20), July 19 - 24th, 2020, Glasgow (UK).
IEEE Intelligent Systems, 2016. (acceptance rate: 24%) [pdf], Characterizing Physical Activity in a Health Social Network.
[pdf], Adaptive Combination of Tag and Link-based User Similarity in Flickr.
[pdf] [Github] [oral presentation] (acceptance rate: 549/2,132), Topic-aware Physical Activity Propagation in a Health Social Network. NhatHai Phan, Dino Ienco, Pascal Poncelet, and Maguelonne Teisseire.
Generally, events are strict with their deadlines. The 28th International Conference on Neural Information Processing (ICONIP'21), December 8 - 12, 2021.
IEEE Access, July 2018.
[Regular Paper][Acceptance Rate: 97 / 486][Github], c-Eval: A Unified Metric to Evaluate Feature-based Explanations via Perturbation.
(acceptance rate: 18%) (Invited to SNAM) [pdf] [Slides] [code] (Selected as Best Papers), Mining Multi-Relational Gradual Patterns [supplementary].
Distinguishing the Effect of Time Spent at Home During COVID-19 Pandemic on the Mental Health of Urban and Suburban College Students Using Cell Phone Geolocation.
A.Z.E. Effective Clustering of Dense and Concentrated Online Communities. NhatHai Phan, Xintao Wu, Han Hu, Dejing Dou. FedML: A Research Library and Benchmark for Federated Machine Learning, MutualNet: Adaptive ConvNet via Mutual Learning from Network Width and Resolution, FlexDNN: Input-Adaptive On-Device Deep Learning for Efficient Mobile Vision, Distream: Scaling Live Video Analytics with Workload-Adaptive Distributed Edge Intelligence, Wi-Fi See It All: Generative Adversarial Network-augmented Versatile Wi-Fi Imaging, SecWIR: Securing Smart Home IoT Communications via Wi-Fi Routers with Embedded Intelligence, SCYLLA: QoE-aware Continuous Mobile Vision with FPGA-based Dynamic Deep Neural Network Reconfiguration, Deep Learning in the Era of Edge Computing: Challenges and Opportunities, DQS: A Framework for Designing Tiny Neural Networks for On-Device AI, HM-NAS: Efficient Neural Architecture Search via Hierarchical Masking, Federated Learning: The Future of Distributed Machine Learning, AutoML Mobile: Automated ML Model Design for Every Mobile Device, NestDNN: Resource-Aware Multi-Tenant On-Device Deep Learning for Continuous Mobile Vision, The Dark Side of Operational Wi-Fi Calling Services, When Virtual Reality Meets Internet of Things in the Gym: Enabling Immersive Interactive Machine Exercises, When Mixed Reality Meets Internet of Things: Toward the Realization of Ubiquitous Mixed Reality, Exploring User Needs for a Mobile Behavioral-Sensing Technology for Depression Management: Qualitative Study, MobileDeepPill: A Small-Footprint Mobile Deep Learning System for Recognizing Unconstrained Pill Images, DeepASL: Enabling Ubiquitous and Non-Intrusive Word and Sentence-Level Sign Language Translation, SharpEar: Real-Time Speech Enhancement in Noisy Environments (Poster), Personal Sensing: Understanding Mental Health Using Ubiquitous Sensors and Machine Learning, Helping Universities Combat Depression with Mobile Technology, BodyScan: Enabling Radio-based Sensing on Wearable Devices for Contactless Activity and Vital Sign Monitoring, HeadScan: A Wearable System for Radio-based Sensing of Head and Mouth-related Activities, AirSense: An Intelligent Home-based Sensing System for Indoor Air Quality Analytics, DoppleSleep: A Contactless Unobtrusive Sleep Sensing System Using Short-Range Doppler Radar, MyBehavior: Automatic Personalized Health Feedback from User Behavior and Preference using Smartphones, Mobile Phone Sensor Correlates of Depressive Symptom Severity in Daily-Life Behavior: An Exploratory Study, The Relationship between Clinical, Momentary, and Sensor-based Assessment of Depression, Automated Personalized Feedback for Physical Activity and Dietary Behavior Change with Mobile Phones: A Randomized Controlled Trial on Adults, An Intelligent Crowd-Worker Selection Approach for Reliable Content Labeling of Food Images, BodyBeat: A Mobile System for Sensing Non-Speech Body Sounds, Towards Accurate Non-Intrusive Recollection of Stress Levels Using Mobile Sensing and Contextual Recall, Human Daily Activity Recognition with Sparse Representation Using Wearable Sensors, Towards Practical Energy Expenditure Estimation with Mobile Phones, Motion Primitive-Based Human Activity Recognition Using a Bag-of-Features Approach, Towards Pervasive Physical Rehabilitation Using Microsoft Kinect, Beyond the Standard Clinical Rating Scales: Fine-Grained Assessment of Post-Stroke Motor Functionality Using Wearable Inertial Sensors, USC-HAD: A Daily Activity Dataset for Ubiquitous Activity Recognition Using Wearable Sensors, A Preliminary Study of Sensing Appliance Usage for Human Activity Recognition Using Mobile Magnetometer, Sparse Representation for Motion Primitive-Based Human Activity Modeling and Recognition Using Wearable Sensors, Robust Human Activity and Sensor Location Co-Recognition via Sparse Signal Representation, Co-Recognition of Human Activity and Sensor Location via Compressed Sensing in Wearable Body Sensor Networks, Manifold Learning and Recognition of Human Activity Using Body-Area Sensors, A Feature Selection-Based Framework for Human Activity Recognition Using Wearable Multimodal Sensors, Context-Aware Fall Detection Using A Bayesian Network, OCRdroid: A Framework to Digitize Text Using Mobile Phones, A Customizable Framework of Body Area Sensor Network for Rehabilitation. Extracting Trajectories through an Efficient and Unifying Spatio-Temporal Pattern Mining System. [pdf] [Slides] [code], All in one: Mining Multiple Movement Patterns.
[pdf], Mining Fuzzy Moving Object Clusters.
17th IEEE International Conference on Machine Learning and Applications (ICMLA 2018) aims to bring together researchers and practitioners to present their latest achievements and innovations in the area of machine learning. This special session at ICMLA 2021 aims to bring researchers across disciplines to share their innovative ideas on learning with graphs and leverage existing methodologies across several application domains.
NhatHai Phan, Dejing Dou, Hao Wang, David Kil, Brigitte Piniewski.
The conference
Proceedings of the 6th ACM International Conference on Digital Health (ACM DH'16), Montreal, Canada, April 2016.
The 28th International Joint Conference on Artificial Intelligence (IJCAI'19), August 10-16, 2019, Macao, China. Human Behavior Modeling in Health Social Networks. [pdf] [Github] (acceptance rate: 9.25% = 72 / 778) (Selected as Best Papers), Preserving Differential Privacy in Convolutional Deep Belief Networks.
IEEE ICHI'18, New York City, NY, USA, June 2018.
The 8th International Conference on Computational Data & Social Networks (CSoNet'19), Hochiminh City, Vietnam, November 2019.
(IEEE BioVis 2013), Atlanta, GA, USA, 13-14 October 2013. The trained staining model can then generate computationally H&E-stained prostate core WSRIs using previously unseen non-stained biopsy images as input. Arxiv 2022. Analysis of Physical Activity Propagation in a Health Social Network, Deep Learning and Its Applications in Health Social Networks.
Authors can expect the result of submission by Sep 04, 2021.
Tutorial on Deep Learning and Applications.
Invited talk at UNC Charlotte, North Carolina, USA, July 2014. Tutorial on Deep Learning and Applications. Information Sciences - Elsevier.
(* equal contribution), FLSys: Toward an Open Ecosystem for FederatedLearning Mobile Apps. We welcome novel research papers on the following algorithms and applications, including but not limited to: Networks 2021: A Joint Sunbelt and NetSci Conference, North American Social Networks Conference (NASN), Conferences, Workshops, and Call for Proposals in the Field, Australian Social Network Analysis Conference (ASNAC), European Conference on Social Networks (EUSN), INSNA Board and Executive Committee: Qualifications and Roles.
ACM SIGSpatial GIS Conference Talk, Redondo Beach, Los Angeles, USA, November 2012. Following the
ICMLA 2021 : 20th IEEE International Conference on Machine Learning and Applications will take place in Pasadena, California, USA.
[Oral Presentation] [Github] (Pradnya Desai is an honor undergraduate student), Social and Motivational Factors for the Spread of Physical Activities in a Health Social Network.
with emphasis on applications as well as novel algorithms and systems.
Han Hu, NhatHai Phan*, James Geller, Soon Ae Chun, Ruoming Jin, Kele Ding, Deric Kenne, and Dejing Dou.
PC & External Reviewer: ICDM ('12, '13, '14, '15, '17), CIKM'17, ADMA'17, IDA'12, DBKDA ('14, '15), DEXA ('13, '14), NFMCP'13, DS ('13, '14), ADMA'12, ECML-PKDD'14, DASFAA ('10, '14), DSAA ('14, '15), BigSim ('14, '15, '16, '17). Does Unsupervised Architecture Representation Learning Help Neural Architecture Search? The 17th World Congress of Medical and Health Informatics (MedInfo'19), Lyon, France, August 2019.
International Conference on Advances in Geographic Information Systems 2019 (ACM SIGSPATIAL'19), Nov 5-8, 2019, Chicago.
Zhihang Hu, Turki Turki, NhatHai Phan, Jason Wang. 2010 ACM Multimedia International Conference (ACM MM 2010), Firenze, Italy, October 2010. [pdf] [Slides] [code] (acceptance rate: 20%), Mining Representative Movement Patterns through Compression. learning through evolution (evolutionary algorithms), machine learning and natural language processing, multi-lingual knowledge acquisition and representation, machine learning and information retrieval, machine learning for bioinformatics and computational biology, machine learning for web navigation and mining, text and multimedia mining through machine learning, distributed and parallel learning algorithms and applications, theories and models for plausible reasoning, o industrial and engineering applications, o medicine, bioinformatics and systems biology, o economics, business and forecasting applications. Indeed, there are many social media communities such as Youtube, Facebook and also Tweets. NhatHai Phan, Pascal Poncelet, and Maguelonne Teisseire.
(* equal contribution) [Github], Guanxiong Liu, Issa Khalil, Abdallah Khreishah, and, IEEE International Conference on Big Data (.
Privacy in Machine Learning (PriML), NeurIPS'19 Workshop, December 8-14, 2019, Vancouver, Canada.
Deep Self-Taught Learning for Detecting Drug Abuse Risk Behavior in Tweets. Analyze, report and deliver Japanese customer requirements to software development team. Basic Algorithms Library System for Data Mining. Yelong Shen*, NhatHai Phan*, Xiao Xiao, Ruoming Jin, Dejing Dou, Junfeng Sun, Brigitte Piniewski, and David Kil. The staining model uses a conditional generative adversarial network that learns hierarchical non-linear mappings between whole slide RGB image (WSRI) pairs of prostate core biopsy before and after H&E staining.
Pradnya Desai, Phung Lai, NhatHai Phan, and My T. Thai.
Han Hu*, Xiaopeng Jiang*, Vijaya Datta Mayyuri, An Chen, Devu M. Shila, Adriaan Larmuseau, Ruoming Jin, Cristian Borcea, and NhatHai Phan. NhatHai Phan, David Kil, Brigitte Piniewski, and Dejing Dou.
success of previous ICMLA conferences, the conference aims to attract researchers and NhatHai Phan, Xintao Wu, Dejing Dou.
A research project that encompasses storytelling, a democratic decision making platform, a city model, and an immersive exhibit.
Research Lab, Barcelona, Spain 05/2013 08/2013, With the success of online social networks and microblogs such as Facebook, Flickr and Twitter, the phenomenon of influence exerted by users of such platforms on other users, and how it propagates in the network, has recently attracted the interest of computer scientists, information technologists, and marketing specialists. Extracting API Tips from Developer Question and Answer Websites. International Journal of Pattern Recognition and Artificial Intelligence, doi:10.1142/S0218001420520102. NhatHai Phan, and Hyoseop Shin. 5-Year IF = 10.47 [pdf] [code], SRBM+: Human Behavior Prediction with Explanations in a Health Social Network.
We offer a variety of membership categories to serve the needs of association professionals and vendors to the association community.
Invited talk at American Family Insurance, Madison, Wisconsin, USA, July 2015. IF = 1.664 [pdf] [demo] [code], Ontology-based Deep Learning for Human Behavior Prediction in Health Social Networks.
Guanxiong Liu, Issa Khalil, Abdallah Khreishah, and NhatHai Phan. Paper 2:Machine Learning Algorithms for Classification of Microcirculation Images from Septic and Non-Septic PatientsPerikumar Javia, Aman Rana, Nathan Shapiro, Pratik Shah, 12/19/18, 2:00-3:20pm, full paper and invited talk. We report a machine learning classifier capable of distinguishing non-septic and septic images from dark field microcirculation videos of patients.
[pdf]. Proceedings of the 6th ACM Conference on Bioinformatics, Computational Biology and Health Informatics (ACM BCB 2015), Atlanta, GA, September 2015. CIKM Conference Talk, Shanghai, China, December 2014. [pdf] [Github] (acceptance rate: 105 / 590), Adaptive Laplace Mechanism: Differential Privacy Preservation in Deep Learning. [pdf] [demo] [code] (acceptance rate: 11.3%), Co2Vis: A Visual Analytics Tool for Mining Co-expressed And Co-regulated Genes Implied in HIV Infections. games, are especially encouraged.
Model Transferring Attacks to Backdoor HyperNetwork in Personalized Federated Learning.
If you are already a member, simply click the first option below to access your accountand enter the email we have on file for you to begin taking advantage of your membership.
Donate to the Lab, Helping Emergency Care Physicians Diagnose Sepsis and Bacterial Infections with Machine Learning and Vision, AI Methods for Rapid Automated Staining and Destaining of Tissue Biopsies in Hospitals. [pdf] [Slides] [code] (Invited Article), Interaction Network Representations for Human Behavior Prediction.
NhatHai Phan, Yue Wang, Xintao Wu, and Dejing Dou. Computation Social Network - Springer, 2019.
NhatHai Phan, Minh Vu, Yang Liu, Ruoming Jin, Xintao Wu, Dejing Dou, and My T. Thai.
OnML: An Ontology-based Approach for Interpretable Machine Learning. Proceedings of 10th Conference on Science and Technology, HCM University of Technology, Ho Chi Minh city, Vietnam, October 2007. as well as other Abstracting and Indexing (A&I) databases. The 7th International Workshop on Information Search, Integration and Personalization (ISIP 2012), Sapporo, Japan, October 2012. [pdf] [Github] (acceptance rate: 9.25% = 72 / 778), Importance Sketching of Influence Dynamics in Billion-scale Networks. This Design Justice Pedagogy Summit and overarching project is motivated by the pressing need to center and incorporate principles of ethic, Accessibility
DPNE: Differentially Private Network Embedding.
Differentially Private Lifelong Learning. In Proceedings of the 8th International Conference on Advanced Data Mining and Applications (ADMA 2012), Nanjing, China, December 2012.
Authors names and affiliations should not appear in the submitted paper.
The maximum length of papers is 8 pages. Han Hu, NhatHai Phan*, James Geller, Stephen Iezzi, Huy Vo, Soon Ae Chun.
[link] [vimeo], An Efficient Spatio-Temporal Mining Approach to Really Know Who Travels with Whom!
Abdallah Khreishah, Issa Khalil, and Xintao Wu.
ACM Transactions on Intelligent Systems and Technology (ACM TIST), 2016.
It is advisable to check the official website for all the deadlines. 30th IEEE International Conference on Tools with Artificial Intelligence, Velos, Greece, November 2018.
ICSDM Conference Talk, Fuzhou China, June 2011.
NhatHai Phan, Dino Ienco, Donato Malerba, Pascal Poncelet, and Maguelonne Teisseire.
Invited to The 7th International Conference on Computational Data & Social Networks (CSoNet'18), Shanghai, China, December 2018.
Classification of Ecological Data by Deep Learning. APWeb Conference Talk, Busan, Korea, April 2010. Research Lab, Prof. Bruno Crmilleux - Universit de Caen, Human Behavior Modeling in Health Social Networks. NhatHai Phan, Hoang Van Duc Thong, and Hyoseop Shin. Imaging of microcirculatory dysfunction is a promising approach for automated diagnosis of sepsis. The 17th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD 2013), Goal Coast, Australia, April 2013.
We report two novel approaches for training machine learning models for the computational H&E staining and destaining of prostate core biopsy RGB images.
problems and interdisciplinary research involving machine learning, in fields like
Proceedings of the 15th IEEE International Conference on Machine Learning and Applications (IEEE ICMLA'16), Anaheim, California, USA, December 18-20, 2016. The Well-Dressed Spacecraft: Textiles for Cosmic Dust Metrology. Spoofing fan detection on social media communities. IF = 3.557 [pdf].
Its a 4 days event starting on Dec 13, 2021 (Monday) and will be winded up on Dec 16, 2021 (Thursday).
[pdf] [demo] [code], An Efficient Spatio-Temporal Mining Approach to Really Know Who Travels with Whom!
International Journal of Environmental Research and Public Health (ISSN 1660-4601).
(* corresponding author). Hochiminh University of Technology Scholarship for good student, 2006-2007.
NhatHai Phan, Pascal Poncelet, and Maguelonne Teisseire. The conference will cover both machine learning theoretical research and its
Papers submitted for review should conform to IEEE specifications.
To speed up the growing of number of fans, some of them buy spoofing fans from fan suppliers. [pdf] [Github] Dataset released: 5,000 drug abuse risk behavior labeled tweets has been released at: https://github.com/hu7han73/DrugAbuseLabeledTweets. We use cookies to offer you a better browsing experience, "recognize" returning INSNA members, and analyze site traffic. Knowledge Representation & Reasoning Meets Machine Learning (KR2ML) Workshop at NeurIPS'19, December 8-14, 2019, Vancouver, Canada. The 37th International Conference on Machine Learning (ICML'20), July 12 - 18, 2020.
Han Hu, NhatHai Phan*, Xinyue Ye, Ruoming Jin, Kele Ding, Dejing Dou, and Huy T. Vo.
Conference content will be submitted for inclusion into IEEE Xplore The 8th International Conference on Computational Data & Social Networks (CSoNet'19), Hochiminh City, Vietnam, November 2019. The 10th International Conference on Computational Data and Social Networks (CSoNet'21), November 15 - 17, 2021.
IEEE International Conference on Big Data (IEEE BigData'21), December 15-18, 2021.
[1] ICMLA 2021 : 20th IEEE International Conference on Machine Learning and Applications.
Upon acceptance, authors should submit the final version of the manuscript on or before Oct 01, 2021 to the official website of the Conference. (* corresponding author), Lifelong DP: Consistently Bounded Differential Privacy in Lifelong Machine Learning.
[pdf], A 3D Atrous Convolutional Long Short-Term Memory Network for Background Subtraction.
NhatHai Phan, Javid Ebrahimi, Dejing Dou, David Kil, and Brigitte Piniewski. Javid Ebrahimi, NhatHai Phan, Dejing Dou, Brigitte Piniewski, and David Kil.
NhatHai Phan, Dino Ienco, Pascal Poncelet, and Maguelonne Teisseire.
Proceedings of the 23rd ACM Conference on Information and Knowledge Management (CIKM 2014), Shanghai, China, November 2014.
[pdf] (acceptance rate: 16%), An Empirical Analysis of User Clusters in Online Communities. NhatHai Phan, Hoang Anh Nguyen, Minh Quang Tran, Hoang Hai Ly, and Tran Khanh Dang.
NhatHai Phan, Dejing Dou, Hao Wang, David Kil, and Brigitte Piniewski. Han Hu, Pravani Moturu, Kannan Neten Dharan, James Geller, Sophie Di Iorio, NhatHai Phan*, Huy Vo, Soon Ae Chun. , Proceedings of Machine Learning Research (.
[pdf] [Slides] [code] (acceptance rate: 21.9%), Analysis of Physical Activity Propagation in a Health Social Network. International Journal of Information Technology & Decision Making (IJITDM), 2016. NhatHai Phan, Javid Ebrahimi, Brigitte Piniewski, David Kil, and Dejing Dou.
(Invited to IEEE J-BHI) [pdf] [Slides] [code] (Selected as Best Papers), Social Restricted Boltzmann Machine: Human Behavior Prediction in Health Social Networks.
The classifier achieves an accuracy of 89.45%.
Machine Learning 2017, ECML-PKDD Journal Track, Skopje, Macedonia 18-22 Sep 2017.
PAKDD'18, Melbourne, Australia, June 2018.
Ingnierie des Systmes d'Information (special issue, selected from BDA12), 2013.
, David Kil, Brigitte Piniewski, and Dejing Dou.
[Slides].
(Selected as Best Papers).
Research on designing communication method between traffic card and client server.
Van Duc Thong Hoang, NhatHai Phan, and Hyoseop Shin.
Journal of Combinatorial Optimization - Springer. This special session will also serve as a common ground to build collaborations, share datasets, and inspire machine learning on graphs research in areas where there are limitations in the existing approaches. provides a leading international forum for the dissemination of original research in ML,
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Manuscript templates can be downloaded from the IEEE website.
ECML-PKDD Conference Talk, Bristol, UK, September 2012.
Outstanding Vietnamese Research Award of Montpellier, France, 2012. Authors of the best papers from this special session will be invited to extend their work and publish it in selected journals (SNAM, Applied Network Science, and Journal of Intelligent and Information Systems).Scope:We welcome novel research papers on the following algorithms and applications, including but not limited to: 2900 Delk Road Suite 700, PMB 321Marietta, GA 30067USA. IF = 2.9 [pdf] [Github] Arxiv version (acceptance rate: 13.5%), Ontology-based Deep Learning for Human Behavior Prediction with Explanations in Health Social Networks.
Hematoxylin and eosin stain (H&E) is one of the principal stains in histology but suffers from several shortcomings related to tissue preparation, staining protocols, slowness and human error.
[pdf].
Amnay Amimeur, NhatHai Phan, Dejing Dou, Brigitte Piniewski, and David Kil. [Slides], Mining Fuzzy Moving Object Clusters.
The 12th International Asia-Pacific Web Conference (APWeb 2010), Busan, Korea, April 2010.
In Proceedings of the 11th International Symposium on Intelligent Data Analysis (IDA 2012), Helsinki, Finland, October 2012.
(Invited Paper), Scalable Differential Privacy with Certified Robustness in Adversarial Learning. NhatHai Phan, Dejing Dou, David Kil, and Brigitte Piniewski.
Hung Nguyen, Tri Nguyen, NhatHai Phan, Thang Dinh. Graphs or networks are ubiquitous structures that appear in a multitude of complex systems like social networks, biological networks, knowledge graphs, the world wide web, transportation networks, and many more.
Arxiv 2021. NhatHai Phan, Pascal Poncelet, and Maguelonne Teisseire.
[pdf], Ontology-based Interpretable Machine Learning with Learnable Anchors. The proposed staining and destaining models can engender computational H&E staining and destaining of WSRI biopsies without additional equipment and devices.
Shaobo Liu, Frank Y. Shih, Gareth Russell, Kimberly Russell, and NhatHai Phan. Proceedings of the 30th AAAI Conference on Artificial Intelligence (AAAI-16), Phoenix, Arizona, USA, February 2016.
The International Joint Conference on Neural Networks (IJCNN'20), July 19 - 24th, 2020, Glasgow (UK).
IEEE Intelligent Systems, 2016. (acceptance rate: 24%) [pdf], Characterizing Physical Activity in a Health Social Network.
[pdf], Adaptive Combination of Tag and Link-based User Similarity in Flickr.
[pdf] [Github] [oral presentation] (acceptance rate: 549/2,132), Topic-aware Physical Activity Propagation in a Health Social Network. NhatHai Phan, Dino Ienco, Pascal Poncelet, and Maguelonne Teisseire.
Generally, events are strict with their deadlines. The 28th International Conference on Neural Information Processing (ICONIP'21), December 8 - 12, 2021.
IEEE Access, July 2018.
[Regular Paper][Acceptance Rate: 97 / 486][Github], c-Eval: A Unified Metric to Evaluate Feature-based Explanations via Perturbation.
(acceptance rate: 18%) (Invited to SNAM) [pdf] [Slides] [code] (Selected as Best Papers), Mining Multi-Relational Gradual Patterns [supplementary].
Distinguishing the Effect of Time Spent at Home During COVID-19 Pandemic on the Mental Health of Urban and Suburban College Students Using Cell Phone Geolocation.
A.Z.E. Effective Clustering of Dense and Concentrated Online Communities. NhatHai Phan, Xintao Wu, Han Hu, Dejing Dou. FedML: A Research Library and Benchmark for Federated Machine Learning, MutualNet: Adaptive ConvNet via Mutual Learning from Network Width and Resolution, FlexDNN: Input-Adaptive On-Device Deep Learning for Efficient Mobile Vision, Distream: Scaling Live Video Analytics with Workload-Adaptive Distributed Edge Intelligence, Wi-Fi See It All: Generative Adversarial Network-augmented Versatile Wi-Fi Imaging, SecWIR: Securing Smart Home IoT Communications via Wi-Fi Routers with Embedded Intelligence, SCYLLA: QoE-aware Continuous Mobile Vision with FPGA-based Dynamic Deep Neural Network Reconfiguration, Deep Learning in the Era of Edge Computing: Challenges and Opportunities, DQS: A Framework for Designing Tiny Neural Networks for On-Device AI, HM-NAS: Efficient Neural Architecture Search via Hierarchical Masking, Federated Learning: The Future of Distributed Machine Learning, AutoML Mobile: Automated ML Model Design for Every Mobile Device, NestDNN: Resource-Aware Multi-Tenant On-Device Deep Learning for Continuous Mobile Vision, The Dark Side of Operational Wi-Fi Calling Services, When Virtual Reality Meets Internet of Things in the Gym: Enabling Immersive Interactive Machine Exercises, When Mixed Reality Meets Internet of Things: Toward the Realization of Ubiquitous Mixed Reality, Exploring User Needs for a Mobile Behavioral-Sensing Technology for Depression Management: Qualitative Study, MobileDeepPill: A Small-Footprint Mobile Deep Learning System for Recognizing Unconstrained Pill Images, DeepASL: Enabling Ubiquitous and Non-Intrusive Word and Sentence-Level Sign Language Translation, SharpEar: Real-Time Speech Enhancement in Noisy Environments (Poster), Personal Sensing: Understanding Mental Health Using Ubiquitous Sensors and Machine Learning, Helping Universities Combat Depression with Mobile Technology, BodyScan: Enabling Radio-based Sensing on Wearable Devices for Contactless Activity and Vital Sign Monitoring, HeadScan: A Wearable System for Radio-based Sensing of Head and Mouth-related Activities, AirSense: An Intelligent Home-based Sensing System for Indoor Air Quality Analytics, DoppleSleep: A Contactless Unobtrusive Sleep Sensing System Using Short-Range Doppler Radar, MyBehavior: Automatic Personalized Health Feedback from User Behavior and Preference using Smartphones, Mobile Phone Sensor Correlates of Depressive Symptom Severity in Daily-Life Behavior: An Exploratory Study, The Relationship between Clinical, Momentary, and Sensor-based Assessment of Depression, Automated Personalized Feedback for Physical Activity and Dietary Behavior Change with Mobile Phones: A Randomized Controlled Trial on Adults, An Intelligent Crowd-Worker Selection Approach for Reliable Content Labeling of Food Images, BodyBeat: A Mobile System for Sensing Non-Speech Body Sounds, Towards Accurate Non-Intrusive Recollection of Stress Levels Using Mobile Sensing and Contextual Recall, Human Daily Activity Recognition with Sparse Representation Using Wearable Sensors, Towards Practical Energy Expenditure Estimation with Mobile Phones, Motion Primitive-Based Human Activity Recognition Using a Bag-of-Features Approach, Towards Pervasive Physical Rehabilitation Using Microsoft Kinect, Beyond the Standard Clinical Rating Scales: Fine-Grained Assessment of Post-Stroke Motor Functionality Using Wearable Inertial Sensors, USC-HAD: A Daily Activity Dataset for Ubiquitous Activity Recognition Using Wearable Sensors, A Preliminary Study of Sensing Appliance Usage for Human Activity Recognition Using Mobile Magnetometer, Sparse Representation for Motion Primitive-Based Human Activity Modeling and Recognition Using Wearable Sensors, Robust Human Activity and Sensor Location Co-Recognition via Sparse Signal Representation, Co-Recognition of Human Activity and Sensor Location via Compressed Sensing in Wearable Body Sensor Networks, Manifold Learning and Recognition of Human Activity Using Body-Area Sensors, A Feature Selection-Based Framework for Human Activity Recognition Using Wearable Multimodal Sensors, Context-Aware Fall Detection Using A Bayesian Network, OCRdroid: A Framework to Digitize Text Using Mobile Phones, A Customizable Framework of Body Area Sensor Network for Rehabilitation. Extracting Trajectories through an Efficient and Unifying Spatio-Temporal Pattern Mining System. [pdf] [Slides] [code], All in one: Mining Multiple Movement Patterns.
[pdf], Mining Fuzzy Moving Object Clusters.
17th IEEE International Conference on Machine Learning and Applications (ICMLA 2018) aims to bring together researchers and practitioners to present their latest achievements and innovations in the area of machine learning. This special session at ICMLA 2021 aims to bring researchers across disciplines to share their innovative ideas on learning with graphs and leverage existing methodologies across several application domains.
NhatHai Phan, Dejing Dou, Hao Wang, David Kil, Brigitte Piniewski.
The conference
Proceedings of the 6th ACM International Conference on Digital Health (ACM DH'16), Montreal, Canada, April 2016.
The 28th International Joint Conference on Artificial Intelligence (IJCAI'19), August 10-16, 2019, Macao, China. Human Behavior Modeling in Health Social Networks. [pdf] [Github] (acceptance rate: 9.25% = 72 / 778) (Selected as Best Papers), Preserving Differential Privacy in Convolutional Deep Belief Networks.
IEEE ICHI'18, New York City, NY, USA, June 2018.
The 8th International Conference on Computational Data & Social Networks (CSoNet'19), Hochiminh City, Vietnam, November 2019.
(IEEE BioVis 2013), Atlanta, GA, USA, 13-14 October 2013. The trained staining model can then generate computationally H&E-stained prostate core WSRIs using previously unseen non-stained biopsy images as input. Arxiv 2022. Analysis of Physical Activity Propagation in a Health Social Network, Deep Learning and Its Applications in Health Social Networks.
Authors can expect the result of submission by Sep 04, 2021.
Tutorial on Deep Learning and Applications.
Invited talk at UNC Charlotte, North Carolina, USA, July 2014. Tutorial on Deep Learning and Applications. Information Sciences - Elsevier.
(* equal contribution), FLSys: Toward an Open Ecosystem for FederatedLearning Mobile Apps. We welcome novel research papers on the following algorithms and applications, including but not limited to: Networks 2021: A Joint Sunbelt and NetSci Conference, North American Social Networks Conference (NASN), Conferences, Workshops, and Call for Proposals in the Field, Australian Social Network Analysis Conference (ASNAC), European Conference on Social Networks (EUSN), INSNA Board and Executive Committee: Qualifications and Roles.
ACM SIGSpatial GIS Conference Talk, Redondo Beach, Los Angeles, USA, November 2012. Following the
ICMLA 2021 : 20th IEEE International Conference on Machine Learning and Applications will take place in Pasadena, California, USA.
[Oral Presentation] [Github] (Pradnya Desai is an honor undergraduate student), Social and Motivational Factors for the Spread of Physical Activities in a Health Social Network.
with emphasis on applications as well as novel algorithms and systems.
Han Hu, NhatHai Phan*, James Geller, Soon Ae Chun, Ruoming Jin, Kele Ding, Deric Kenne, and Dejing Dou.
PC & External Reviewer: ICDM ('12, '13, '14, '15, '17), CIKM'17, ADMA'17, IDA'12, DBKDA ('14, '15), DEXA ('13, '14), NFMCP'13, DS ('13, '14), ADMA'12, ECML-PKDD'14, DASFAA ('10, '14), DSAA ('14, '15), BigSim ('14, '15, '16, '17). Does Unsupervised Architecture Representation Learning Help Neural Architecture Search? The 17th World Congress of Medical and Health Informatics (MedInfo'19), Lyon, France, August 2019.
International Conference on Advances in Geographic Information Systems 2019 (ACM SIGSPATIAL'19), Nov 5-8, 2019, Chicago.
Zhihang Hu, Turki Turki, NhatHai Phan, Jason Wang. 2010 ACM Multimedia International Conference (ACM MM 2010), Firenze, Italy, October 2010. [pdf] [Slides] [code] (acceptance rate: 20%), Mining Representative Movement Patterns through Compression. learning through evolution (evolutionary algorithms), machine learning and natural language processing, multi-lingual knowledge acquisition and representation, machine learning and information retrieval, machine learning for bioinformatics and computational biology, machine learning for web navigation and mining, text and multimedia mining through machine learning, distributed and parallel learning algorithms and applications, theories and models for plausible reasoning, o industrial and engineering applications, o medicine, bioinformatics and systems biology, o economics, business and forecasting applications. Indeed, there are many social media communities such as Youtube, Facebook and also Tweets. NhatHai Phan, Pascal Poncelet, and Maguelonne Teisseire.
(* equal contribution) [Github], Guanxiong Liu, Issa Khalil, Abdallah Khreishah, and, IEEE International Conference on Big Data (.
Privacy in Machine Learning (PriML), NeurIPS'19 Workshop, December 8-14, 2019, Vancouver, Canada.
Deep Self-Taught Learning for Detecting Drug Abuse Risk Behavior in Tweets. Analyze, report and deliver Japanese customer requirements to software development team. Basic Algorithms Library System for Data Mining. Yelong Shen*, NhatHai Phan*, Xiao Xiao, Ruoming Jin, Dejing Dou, Junfeng Sun, Brigitte Piniewski, and David Kil. The staining model uses a conditional generative adversarial network that learns hierarchical non-linear mappings between whole slide RGB image (WSRI) pairs of prostate core biopsy before and after H&E staining.