Phung Lai, NhatHai Phan*, Abdall

2021/05/21

Phung Lai, NhatHai Phan*, Abdallah Khreishah, Issa Khalil, and Xintao Wu. This Design Justice Pedagogy Summit and overarching project is motivated by the pressing need to center and incorporate principles of ethic, Accessibility [pdf]. Research on designing communication method between traffic card and client server. Journal of Combinatorial Optimization - Springer. Invited talk at American Family Insurance, Madison, Wisconsin, USA, July 2015. Conference content will be submitted for inclusion into IEEE Xplore IEEE International Conference on Big Data (IEEE BigData'21), December 15-18, 2021. Imaging of microcirculatory dysfunction is a promising approach for automated diagnosis of sepsis. Deep Self-Taught Learning for Detecting Drug Abuse Risk Behavior in Tweets. NhatHai Phan, Pascal Poncelet, and Maguelonne Teisseire. Conference content will be submitted for inclusion into IEEE Xplore as well as other Abstracting and Indexing (A&I) databases. 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. Abdallah Khreishah, Issa Khalil, and Xintao Wu. Proceedings of the 30th AAAI Conference on Artificial Intelligence (AAAI-16), Phoenix, Arizona, USA, February 2016. (IEEE BioVis 2013), Atlanta, GA, USA, 13-14 October 2013. Hung Nguyen, Tri Nguyen, NhatHai Phan, Thang Dinh. Structural and anatomical details of prostate tissue and colors, shapes, geometries, locations of nuclei, stroma, vessels, glands and other cellular components were generated by both models with structural similarity indices of 0.68 (staining) and 0.84 (destaining). NhatHai Phan, Xintao Wu, Dejing Dou. The 10th International Conference on Computational Data and Social Networks (CSoNet'21), November 15 - 17, 2021. [pdf], Towards an Extensible Library System for Data Mining. This site uses cookies from Google to deliver its services and to analyze traffic. as well as other Abstracting and Indexing (A&I) databases. Guanxiong Liu, Issa Khalil, Abdallah Khreishah, and NhatHai Phan. CIKM Conference Talk, Shanghai, China, December 2014. Aabidine, A. Sallaberry, S. Bringay, M. Fabregue, C. Lecellier, NhatHai Phan, and P. Poncelet.

[pdf] [Slides] [code], Differential Privacy Preservation for Deep Auto-Encoders: an Application of Human Behavior Prediction.

Contributions describing machine learning techniques applied to real-world problems and interdisciplinary research involving machine learning, in fields like medicine, biology, industry, manufacturing, security, education, virtual environments, games, will be presented as oral presentations (full papers) and posters (short papers). [pdf] [Slides] [code] (Invited Article), Interaction Network Representations for Human Behavior Prediction. IF = 2.004[pdf] [Slides] [code] (*equal contribution), Topic-aware Physical Activity Propagation with Temporal Dynamics in a Health Social Network. [Slides]. Khanh Hoa Province Scholarship for good student on mathematics, 2002-2003. NhatHai Phan, Yue Wang, Xintao Wu, and Dejing Dou. Authors names and affiliations should not appear in the submitted paper. (* equal contribution) [Github], Guanxiong Liu, Issa Khalil, Abdallah Khreishah, and, IEEE International Conference on Big Data (. Research Lab, Prof. Bruno Crmilleux - Universit de Caen, Human Behavior Modeling in Health Social Networks. , David Kil, Brigitte Piniewski, and Dejing Dou. Arxiv 2022. [pdf] [Slides] [code], All in one: Mining Multiple Movement Patterns. Pelin Ayranci, Cesar Bandera, NhatHai Phan, Ruoming Jin, Dong Li, Deric Kenne. [Slides]. Wuji Liu, Xinyue Ye, NhatHai Phan, and Han Hu. IF = 4.832 [pdf] [code], Enabling Real-Time Drug Abuse Detection in Tweets. NhatHai Phan, Dino Ienco, Pascal Poncelet, and Maguelonne Teisseire. Machine Learning 2017, ECML-PKDD Journal Track, Skopje, Macedonia 18-22 Sep 2017. medicine, biology, industry, manufacturing, security, education, virtual environments, [Oral Presentation] [pdf], DrugTracker: A Community-focused Drug Abuse Monitoring and Supporting System using Social Media and Geospatial Data. Invited to The 7th International Conference on Computational Data & Social Networks (CSoNet'18), Shanghai, China, December 2018. The International Joint Conference on Neural Networks (IJCNN'20), July 19 - 24th, 2020, Glasgow (UK). Using an unsupervised convolutional autoencoder, independent of the clinical diagnosis, we also report clustering of learned features from a compressed representation associated with healthy images and those with microcirculatory dysfunction. International Journal of Environmental Research and Public Health (ISSN 1660-4601). Software Bridge Engineering. ACM Transactions on Intelligent Systems and Technology (ACM TIST), 2016. Information about your use of this site is shared with Google. (acceptance rate: 24%) [pdf], Characterizing Physical Activity in a Health Social Network. Ruoming Jin, Yelong Shen, Lin Liu, Xue-Wen Chen, and NhatHai Phan.

ACOMP Conference Talk, Hochiminh, Vietnam, March 2008. Proceedings of the 15th IEEE International Conference on Machine Learning and Applications (IEEE ICMLA'16), Anaheim, California, USA, December 18-20, 2016. challenges. We use cookies to offer you a better browsing experience, "recognize" returning INSNA members, and analyze site traffic. 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. 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.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. Human Behavior Modeling in Health Social Networks. Contributions describing machine learning techniques applied to real-world We report two novel approaches for training machine learning models for the computational H&E staining and destaining of prostate core biopsy RGB images. (with Dr.Francesco Bonchi), Data Mining Specialist, R&D Dept, Pyramid Consulting Corp 03/2013 05/2013. NhatHai Phan, Pascal Poncelet, and Maguelonne Teisseire. Adaptive Combination of Tag and Link-based User Similarity in Flickr. NhatHai Phan, Minh Vu, Yang Liu, Ruoming Jin, Xintao Wu, Dejing Dou, and My T. Thai. 2022 www.resurchify.com All Rights Reserved. achievements and innovations in the area of machine learning (ML). 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. [Github] [Oral Presentation]. [pdf] [Slides] [code] (acceptance rate: 20%), Mining Representative Movement Patterns through Compression. NhatHai Phan, Hoang Van Duc Thong, and Hyoseop Shin.

Han Hu, NhatHai Phan*, Xinyue Ye, Ruoming Jin, Kele Ding, Dejing Dou, and Huy T. Vo.

Social Network Analysis and Mining (SNAM), 2016. [Regular Paper][Acceptance Rate: 97/486][Github], Continual Learning with Differential Privacy. (acceptance rate: 18%) (Invited to SNAM) [pdf] [Slides] [code] (Selected as Best Papers), Mining Multi-Relational Gradual Patterns [supplementary]. Han Hu, Pravani Moturu, Kannan Neten Dharan, James Geller, Sophie Di Iorio, NhatHai Phan*, Huy Vo, Soon Ae Chun. Limiting the Neighborhood: De-Small-World Network for Outbreak Prevention.

Phung Lai, NhatHai Phan*, Han Hu, Anuja Badeti, David Newman, and Dejing Dou. IEEE ICDM'17, New Orleans, USA 18-21 November 2017. [pdf] [code] (acceptance rate: 19%), Mining Time Relaxed Gradual Moving Object Clusters. NhatHai Phan, Pascal Poncelet, and Maguelonne Teisseire. In Proceedings of the 8th International Conference on Advanced Data Mining and Applications (ADMA 2012), Nanjing, China, December 2012. with emphasis on applications as well as novel algorithms and systems. [pdf] [Github] (acceptance rate: 9.25% = 72 / 778), Importance Sketching of Influence Dynamics in Billion-scale Networks. Basic Algorithms Library System for Data Mining. [pdf] [Github] [oral presentation] (acceptance rate: 549/2,132), Topic-aware Physical Activity Propagation in a Health Social Network. (* equal contribution), FLSys: Toward an Open Ecosystem for FederatedLearning Mobile Apps. An Insight Analysis and Detection of Drug Abuse Risk Behavior on Twitter with Self-Taught Deep Learning. PAKDD'18, Melbourne, Australia, June 2018. Proceedings of 10th Conference on Science and Technology, HCM University of Technology, Ho Chi Minh city, Vietnam, October 2007. [pdf] (acceptance rate: 16%), An Empirical Analysis of User Clusters in Online Communities. The 8th International Conference on Computational Data & Social Networks (CSoNet'19), Hochiminh City, Vietnam, November 2019. [pdf] (Selected as Best Papers), Recursive Structure Similarity: A Novel Algorithm for Graph Clustering. Members often receive discounts from publishers on new books on social network analysis. DPNE: Differentially Private Network Embedding.

Mining Object Movement Patterns: Challenges and Directions, Mining Time Relaxed Gradual Moving Object Clusters, Extracting Trajectories through an Efficient and Unifying Spatio-Temporal Pattern Mining System, GeT_Move: An Efficient and Unifying Movement Pattern Mining Algorithm, Moving Object: Combining Gradual Rules and Spatio-Temporal Patterns, Effective Clustering of Dense and Concentrated Online Communities, Adaptive Combination of Tag and Link-based User Similarity in Flickr, Basic Algorithms Library System for Data Mining, The Conference on Lifelong Learning Agents (, The 28th International Conference on Neural Information Processing (, The 37th International Conference on Machine Learning (, The International Joint Conference on Neural Networks (, International Journal of Pattern Recognition and Artificial Intelligence, Knowledge Representation & Reasoning Meets Machine Learning (, The 28th International Joint Conference on Artificial Intelligence (, The 17th World Congress of Medical and Health Informatics (, The 8th International Conference on Computational Data & Social Networks (, The 16th International Conference on Mining Software Repositories (, The 7th International Conference on Computational Data & Social Networks (, 30th IEEE International Conference on Tools with Artificial Intelligence, https://github.com/hu7han73/DrugAbuseLabeledTweets, Mining Object Movement Patterns from Trajectory Data. Shaobo Liu, Frank Y. Shih, Gareth Russell, Kimberly Russell, and NhatHai Phan. Its a 4 days event starting on Dec 13, 2021 (Monday) and will be winded up on Dec 16, 2021 (Thursday). Invited talk at Yahoo! Generally, events are strict with their deadlines. applications. ECML-PKDD Conference Talk, Bristol, UK, September 2012. NhatHai Phan, Soon Ae Chun, Manasi Bhole, and James Geller. NhatHai Phan, My T. Thai, Han Hu, Ruoming Jin, Tong Sun, and Dejing Dou. NhatHai Phan, Dejing Dou, Hao Wang, David Kil, and Brigitte Piniewski. INSNA publishes or supports several key publications in the field, including: Connections, whose emphasis is to reflect the ever-growing and continually expanding community of scholars using network analytic techniques, as well as provide an outlet for sharing news about social network concepts and techniques and new tools for research; the Journal of Social Structure, an electronic journal designed to facilitate timely dissemination of state-of-the-art results in the interdisciplinary research area of social structure as well as publish empirical, theoretical and methodological articles; and Social Networks, an interdisciplinary and international quarterly providing a common forum for representatives of anthropology, sociology, history, social psychology, political science, human geography, biology, economics, communications science and other disciplines who share an interest in the study of the empirical structure of social relations and associations that may be expressed in network form. Mining Time Relaxed Gradual Moving Object Clusters. [pdf] [demo] [code] (acceptance rate: 22%), How to Extract Relevant Knowledge from Tweets?

The feature space used by our trained classifier to distinguish between images from septic and non-septic patients has potential diagnostic application. A.Z.E. The area under the receiver operating characteristics of the classifier was 0.92, the precision was 0.92 and the recall was 0.84. Papers must be submitted via the. [Slides], Mining Object Movement Patterns: Challenges and Directions. [pdf], Mining Fuzzy Moving Object Clusters. Papers submitted for review should conform to IEEE specifications. F. Bouillot, NhatHai Phan, N. Bchet, S. Bringay, D. Ienco, S. Matwin, P. Poncelet, M. Roche, and M. Teisseire. Amnay Amimeur, NhatHai Phan, Dejing Dou, Brigitte Piniewski, and David Kil. Depeng Xu, Shuhan Yuan, Xintao Wu, NhatHai Phan. Internship, R&D Center, EB Corp, Seoul, South Korea 03/2008 09/2008. Han Hu, NhatHai Phan, James Geller, Huy Vo, Bhole Manasi, Xueqi Huang, Sophie Di Lorio, Thang Dinh, Soon Ae Chun. Membership benefits include: reduced conference registration fees, a reduced subscription rate for the journal Social Networks, a subscription to Connections, the association's bulletin and journal, and through Connections, access to a bank of network datasets. Additional membership benefits include timely notifications of conferences, symposia, and workshops in network analysis held throughout the year at various locations in the many countries represented by the INSNA membership and access to the world's leading experts on social network analysis through SOCNET (INSNAs online discussion forum) and at INSNAs signature conference, the Sunbelt conference. ICMLA 2018 aims to bring together researchers and practitioners to present their latest Deep Learning Model for Classifying Drug Abuse Risk Behavior in Tweets. Codes representing the learned feature space of trained classifier were visualized using t-SNE embedding and were separable and distinguished between images from critically ill and non-septic patients. ACM Multimedia Conference Poster Presentation, Firenze, Italy, October 2010. Knowledge Representation & Reasoning Meets Machine Learning (KR2ML) Workshop at NeurIPS'19, December 8-14, 2019, Vancouver, Canada. Proceedings of International Workshop on Advanced Computing and Applications(ACOMP 2008), Ho Chi Minh City, Vietnam, March 2008. In this work we take a data mining perspective and we discuss what (and how) can be learned from the available traces of past propagations. 2010 ACM Multimedia International Conference (ACM MM 2010), Firenze, Italy, October 2010. Invited talk at UNC Charlotte, North Carolina, USA, July 2014. NhatHai Phan, Dino Ienco, Pascal Poncelet, and Maguelonne Teisseire. Extracting Trajectories through an Efficient and Unifying Spatio-Temporal Pattern Mining System. The 17th World Congress of Medical and Health Informatics (MedInfo'19), Lyon, France, August 2019. IF = 3.532 [pdf] [Slides] [code], Dynamic Socialized Gaussian Process Models for Human Behavior Prediction in a Health Social Network. , Proceedings of Machine Learning Research (. 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. In Proceedings of the 20th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems (ACM GIS 2012), Redondo Beach, California, November 2012. The proposed staining and destaining models can engender computational H&E staining and destaining of WSRI biopsies without additional equipment and devices. We offer a variety of membership categories to serve the needs of association professionals and vendors to the association community.

[pdf] [demo] [video] [code] (Selected as Best papers), Extracting Trajectories through an Efficient and Unifying Spatio-Temporal Pattern Mining System. Proceedings of the SIAM International Conference on Data Mining (SDM 2015), Vancouver, Canada, May 2015. of Big Data processing brings an urgent need for machine learning to address these new (Selected as Best Papers). The 37th International Conference on Machine Learning (ICML'20), July 12 - 18, 2020. Proceedings of the 6th ACM Conference on Bioinformatics, Computational Biology and Health Informatics (ACM BCB 2015), Atlanta, GA, September 2015. Oct 2013 - Mining Object Movement Patterns from Trajectory Data - [pdf] [Slides], Supervisors: Dr. Dino ienco, Prof. Pascal Poncelet, Prof. Maguelonne Teisseire, Prof. Osmar Zaane - University of Alberta, Prof. Arno Siebes - Utrech University, Dr. Francesco Bonchi - Yahoo! Information Sciences - Elsevier. Tutorial on Deep Learning and Applications. The issue here is that many artists desire to have many fans following their activities. The 17th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD 2013), Goal Coast, Australia, April 2013. 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. Pelin Ayranci*, Phung Lai*, NhatHai Phan, Han Hu, David Newman, Alexander Kalinowski, and Dejing Dou. provides a leading international forum for the dissemination of original research in ML, GeT_Move: An Efficient and Unifying Movement Pattern Mining Algorithm.

IF = 3.557 [pdf]. APWeb Conference Talk, Busan, Korea, April 2010. NhatHai Phan, Xintao Wu, Han Hu, Dejing Dou. Hochiminh University of Technology Scholarship for good student, 2006-2007. International Journal of Pattern Recognition and Artificial Intelligence, doi:10.1142/S0218001420520102. Indeed, there are many social media communities such as Youtube, Facebook and also Tweets. The authors prior work should be cited in the third person. Does Unsupervised Architecture Representation Learning Help Neural Architecture Search? Classification of Ecological Data by Deep Learning. [pdf], A 3D Atrous Convolutional Long Short-Term Memory Network for Background Subtraction. (Invited to IEEE J-BHI) [pdf] [Slides] [code] (Selected as Best Papers), Social Restricted Boltzmann Machine: Human Behavior Prediction in Health Social Networks. [Regular Paper][Acceptance Rate: 97 / 486][Github], c-Eval: A Unified Metric to Evaluate Feature-based Explanations via Perturbation. Organization Committee: IEEE ICMLA'20, DOCTISS'12. The conference will cover both machine learning theoretical research and its Proceedings of the IEEE/ACM International Conference on Advances in Social Network Analysis and Mining (ASONAM 2015), Paris, France, August 2015. [pdf], Effective Clustering of Dense and Concentrated Online Communities. In ECML-PKDD 2012, Demo Paper, Bristol, UK, September 2012. Minh Vu, Truc D. Nguyen, NhatHai Phan, Ralucca Gera, My T. Thai. [GitHub], Heterogeneous Gaussian Mechanism: Preserving Differential Privacy in Deep Learning with Provable Robustness. By using the site, you consent to our use of cookies. Following the BDA Summer School Talk, Aussois, France, August 2012. Authors can expect the result of submission by Sep 04, 2021.

NhatHai Phan, Dino Ienco, Pascal Poncelet, and Maguelonne Teisseire. The 8th International Conference on Computational Data & Social Networks (CSoNet'19), Hochiminh City, Vietnam, November 2019. Select a membership type below to get started! The 28th International Joint Conference on Artificial Intelligence (IJCAI'19), August 10-16, 2019, Macao, China.

Scalable Self-Taught Deep-embedded Learning Framework for Drug Abuse Behaviors Detection with Spatial Effects. The 2nd International Conference on Emerging Databases (EDB 2010), Jeju Korea, August 2010. Model Transferring Attacks to Backdoor HyperNetwork in Personalized Federated Learning. IEEE ICDM'17, New Orleans, USA 18-21 November 2017. The 12th International Asia-Pacific Web Conference (APWeb 2010), Busan, Korea, April 2010.

Van Duc Thong Hoang, NhatHai Phan, and Hyoseop Shin. application developers from a wide range of ML related areas, and the recent emergence Abstract: Histopathology tissue samples are widely available in two states: paraffin-embedded unstained and non-paraffin-embedded stained whole slide RGB images (WSRI). [pdf] [demo] [code] (acceptance rate: 11.3%), Co2Vis: A Visual Analytics Tool for Mining Co-expressed And Co-regulated Genes Implied in HIV Infections. A research project that encompasses storytelling, a democratic decision making platform, a city model, and an immersive exhibit. The 28th International Conference on Neural Information Processing (ICONIP'21), December 8 - 12, 2021. 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. Differentially Private Lifelong Learning. Proceedings of the 6th ACM International Conference on Digital Health (ACM DH'16), Montreal, Canada, April 2016. Please check the official event website for possible changes before you make any travelling arrangements. , Han Hu, David Newman, Alexander Kalinowski, and Dejing Dou. 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. NhatHai Phan, David Kil, Brigitte Piniewski, and Dejing Dou. To speed up the growing of number of fans, some of them buy spoofing fans from fan suppliers. Computation Social Network - Springer, 2019. To withdraw consent, please adjust your cookie settings in your browser. ICSDM Conference Talk, Fuzhou China, June 2011. The conference Han Hu*, Xiaopeng Jiang*, Vijaya Datta Mayyuri, An Chen, Devu M. Shila, Adriaan Larmuseau, Ruoming Jin, Cristian Borcea, and NhatHai Phan. ICMLA 2021 : 20th IEEE International Conference on Machine Learning and Applications will take place in Pasadena, California, USA.

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