@@ Line 1: / Line 1: @@
+{| align="right"
+ | __TOC__
+ |}
+* '''Instructor:''' [http://www.cse.wustl.edu/~lu Prof. Chenyang Lu]
+* '''Seminar time: Thursday at 4pm-5pm, Location: Jolley 224'''
+* '''Lab meeting time: Friday at 3pm-4pm, Location: Jolley 224'''
+* RTSS ([http://www.rtss.org/])
+* RTAS ([http://www.rtas.org/])
+* ICCPS ([http://www.iccps.org])
+* SenSys ([http://sensys.acm.org])
+* IPSN ([http://ipsn.acm.org])
+* MobiCom ([https://sigmobile.org/mobicom/2019/])
+* MobiSys ([http://www.sigmobile.org/mobisys/2019/])
+'''Guidelines'''
+* Please pick high-quality papers from top venues related to your research.
+* Email Dr. Lu your paper for approval one week before your presentation.
+* Post the approved paper on the wiki.
+* Prepare well and give good talks. The seminar is a significant investment of our time as a group and we want to make the best use of the time.
+=== ---May 28---===
+Seminar: Haoran
+Junqueira, F. P., Reed, B. C., & Serafini, M. (2011, June). Zab: High-performance broadcast for primary-backup systems. In 2011 IEEE/IFIP 41st International Conference on Dependable Systems & Networks (DSN) (pp. 245-256). IEEE. [http://deptinfo.unice.fr/twiki/pub/Minfo/DistributedAlgo/zab.pdf link]
+Hunt, P., Konar, M., Junqueira, F. P., & Reed, B. (2010, June). ZooKeeper: Wait-free Coordination for Internet-scale Systems. In USENIX annual technical conference (Vol. 8, No. 9) [https://static.usenix.org/event/atc10/tech/full_papers/Hunt.pdf link]
+Lab meeting: Canceled
+=== ---June 4---===
+Seminar: Hanyang
+Che, Zhengping, et al. "Recurrent neural networks for multivariate time series with missing values." Scientific reports 8.1 (2018): 1-12. [https://www.nature.com/articles/s41598-018-24271-9]
+Lab meeting: Ruixuan
-{| align="right"
+=== ---June 11---===
- | __TOC__
- |}
+Seminar: Ruixuan
+Huynh, Sinh, et al. "VitaMon: measuring heart rate variability using smartphone front camera." Proceedings of the 17th Conference on Embedded Networked Sensor Systems. 2019.[[https://dl.acm.org/doi/10.1145/3356250.3360036]]
+Lab meeting: Canceled
+=== ---June 18---===
+Seminar: Jingwen
+Cao, Wei, Dong Wang, Jian Li, Hao Zhou, Lei Li, and Yitan Li. "Brits: Bidirectional recurrent imputation for time series." In Advances in Neural Information Processing Systems, pp. 6775-6785. 2018. [https://papers.nips.cc/paper/7911-brits-bidirectional-recurrent-imputation-for-time-series.pdf]
+Lab meeting: Bing
+=== ---June 25--- ===
+Seminar: Dingwen
+E. Choi, et al. "GRAM: Graph-based Attention Model for Healthcare Representation Learning." In Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD ’17). [https://dl.acm.org/doi/10.1145/3097983.3098126 link]
+Lab meeting: Canceled
+=== ---July 2--- ===
+Seminar: Yehan
+Quindlen, John F., Ufuk Topcu, Girish Chowdhary, and Jonathan P. How. Active sampling-based binary verification of dynamical systems. In AIAA Guidance, Navigation, and Control Conference, 2018. [https://arc.aiaa.org/doi/abs/10.2514/6.2018-1107]
+Lab meeting: Public Holiday
+=== ---July 9--- ===
+Seminar: Bing
+Ribeiro, Marco Tulio, Sameer Singh, and Carlos Guestrin. "Why should i trust you?: Explaining the predictions of any classifier." Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. ACM, 2016. [https://www.kdd.org/kdd2016/papers/files/rfp0573-ribeiroA.pdf]
-* '''Instructor:''' [http://www.cse.wustl.edu/~lu Prof. Chenyang Lu]
+Lundberg, Scott M., and Su-In Lee. "A unified approach to interpreting model predictions." Advances in neural information processing systems. 2017.[http://papers.nips.cc/paper/7062-a-unified-approach-to-interpreting-model-predictions.pdf]
-* '''Time: Thursday at 4pm-4:50pm, Location: Jolley 309 (''New Location'')'''
-* '''Google group:''' [https://groups.google.com/forum/#!forum/wustlmlseminar group for machine learning seminar]
-This seminar examines machine learning by studying seminal papers and recent research results. Each semester, the seminar emphasizes different themes reflecting the current research interests of the participants. The theme of this semester's seminar is '''Machine Learning for Health'''. We will read and discuss papers from recent major conferences and journals on machine learning, data mining, and AI related to healthcare.  These conferences and journals include:
+Lundberg, Scott M., et al. "From local explanations to global understanding with explainable AI for trees." Nature machine intelligence 2.1 (2020): 2522-5839.[https://arxiv.org/pdf/1905.04610.pdf]
-* NeurIPS ([http://nips.cc/])
+Lab meeting: Jiangnan
-* ICML ([http://icml.cc/])
-* AAAI ([http://www.aaai.org/])
-* SIGKDD ([http://www.kdd.org/])
-* IJCAI ([http://www.ijcai.org/])
-* IMWUT ([http://dl.acm.org/journal/imwut])
-* Digital Medicine ([http://www.nature.com/npjdigitalmed/])
-* HEALTH ([http://dl.acm.org/journal/health])
-* Lancet Digital Health ([https://www.thelancet.com/journals/landig/issues#decade=loi_decade_201])
+=== ---July 16 --- ===
-=== ---Jan 23 ---===
+Seminar: Jiangnan
-Presenter: Dingwen Li
+Liu, Zihao, et al. "DeepN-JPEG: A deep neural network favorable JPEG-based image compression framework." Proceedings of the 55th Annual Design Automation Conference. 2018.
+[https://arxiv.org/pdf/1803.05788.pdf]
-Paper: DeepAlerts: Deep Learning Based Multi-horizon Alerts for Clinical Deterioration on Oncology Hospital Wards, AAAI-2020, D. Li, P. Lyons, C. Lu, M. Kollef. ([https://www.cse.wustl.edu/~lu/papers/aaai20.pdf])
-=== ---Jan 30 ---===
+Lab meeting: Haoran
-Presenter: Ruixuan Dai
+=== ---July 23 --- ===
-Paper: Shen, Yichen, et al. "Ambulatory Atrial Fibrillation Monitoring Using Wearable Photoplethysmography with Deep Learning." Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining. 2019.
+Seminar: Haoran
-URL: https://www.kdd.org/kdd2019/accepted-papers/view/ambulatory-atrial-fibrillation-monitoring-using-wearable-photoplethysmograp
-=== ---Feb 06 ---===
+El-Sanosi, I., & Ezhilchelvan, P. (2018). Improving ZooKeeper Atomic Broadcast Performance When a Server Quorum Never Crashes. EAI Endorsed Transactions on Energy Web. [https://eprints.ncl.ac.uk/file_store/production/253982/0AB5212D-4E87-474C-8487-AED4E008F64A.pdf link]
-Presenter: Ali Ghubaish
+Ibrahim, E. S. (2018). Mechanisms for Improving ZooKeeper Atomic Broadcast Performance. Computing. [https://pdfs.semanticscholar.org/4203/4d0f80a9e0517403eab3ef6e3722be8d1041.pdf Ph.D. Dissertation]
-Paper: MiME: Multilevel Medical Embedding of Electronic Health Records for Predictive Healthcare, NeurIPS 2018, E. Choi, et al. ([https://papers.nips.cc/paper/7706-mime-multilevel-medical-embedding-of-electronic-health-records-for-predictive-healthcare.pdf])
+Lab meeting: Jingwen
-=== ---Feb 13 ---===
+=== ---July 30 --- ===
-Presenter: Hanyang Liu
-Paper: Alaa, Ahmed M., and Mihaela van der Schaar. "Bayesian inference of individualized treatment effects using multi-task gaussian processes." Advances in Neural Information Processing Systems. 2017.
+Seminar: Hanyang
-URL: https://papers.nips.cc/paper/6934-bayesian-inference-of-individualized-treatment-effects-using-multi-task-gaussian-processes.pdf
-=== ---Feb 20 ---===
+J. Futoma, S. Hariharan, and K. Heller. “Learning to Detect Sepsis with a Multitask Gaussian Process RNN Classifier,” in Proceedings of the 34th International Conference on Machine Learning (ICML), Sydney, Australia, Aug 2017. [https://arxiv.org/abs/1706.04152]
-Presenter: Jingwen Zhang
-Paper: Song, Huan, Deepta Rajan, Jayaraman J. Thiagarajan, and Andreas Spanias. "Attend and diagnose: Clinical time series analysis using attention models." In Thirty-second AAAI conference on artificial intelligence. 2018.
+Lab meeting: Yehan
-URL: https://www.aaai.org/ocs/index.php/AAAI/AAAI18/paper/viewPaper/16325
-=== ---Feb 27 ---===
+=== ---Aug 6 --- ===
-Canceled for Big Ideas event
+Seminar: Ruixuan
+Liao, Peng, et al. "Personalized HeartSteps: A Reinforcement Learning Algorithm for Optimizing Physical Activity." Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies 4.1 (2020): 1-22.
-=== ---Mar 05 ---===
+Lab meeting:  Dingwen
-Presenter: Joss Wang
-Paper: Maithra Raghu, Chiyuan Zhang, Jon Kleinberg, Samy Bengio, Transfusion: Understanding Transfer Learning for Medical Imaging, NeurIPS 2019. URL: https://arxiv.org/pdf/1902.07208.pdf
+=== ---Aug 13 --- ===
-=== ---Mar 12 ---===
+Seminar: Yehan
-Spring Break - No Seminar
-=== ---Mar 19 ---===
+Ahlén, Anders, Johan Akerberg, Markus Eriksson, Alf J. Isaksson, Takuya Iwaki, Karl Henrik Johansson, Steffi Knorn, Thomas Lindh, and Henrik Sandberg. "Toward wireless control in industrial process automation: A case study at a paper mill." IEEE Control Systems Magazine 39, no. 5 (2019): 36-57.
-Spring Break - No Seminar
-=== ---Mar 26 ---===
+Lab meeting: Hanyang
-'''Double Header'''
+=== ---Aug 20 --- ===
-Presenters: Hao Liu and Adith Boloor
+Seminar: Jingwen
-Paper 1: X. Zhang et al., MetaPred: Meta-Learning for Clinical Risk Prediction with Limited Patient Electronic Health Records, KDD 2019. URL: https://dl.acm.org/doi/10.1145/3292500.3330779
+Zheng, Kaiping, et al. "TRACER: A Framework for Facilitating Accurate and Interpretable Analytics for High Stakes Applications." Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data. 2020 [https://dl.acm.org/doi/10.1145/3318464.3389720]
-Paper 2: A. Rajkomar et al., Scalable and Accurate Deep Learning with Electronic Health Records, npj Digital Medicine (2018) 1:18. URL: https://www.nature.com/articles/s41746-018-0029-1.pdf
+Lab meeting: Ruixuan
-=== ---Apr 02 ---===
+===  --- Aug 27 --- ===
-'''Double Header'''
-Presenters: Zhuangzhuang Zhang and Bing Xue
+Seminar: Cancelled
-Paper 1: Hybrid Retrieval-Generation Reinforced Agent for Medical Image Report Generation, NIPS 2018, Y. Li, et al. ([https://papers.nips.cc/paper/7426-hybrid-retrieval-generation-reinforced-agent-for-medical-image-report-generation])
+Lab meeting: Haoran
-Paper 2: Hao Wang, Chengzhi Mao, Hao He, Mingmin Zhao, Tommi S. Jaakkola, and Dina Katabi, Bidirectional Inference Networks:A Class of Deep Bayesian Networks for Health Profiling, AAAI Conference on Artificial Intelligence (AAAI-19), 2019.
+===  --- Sep 03 --- ===
-URL: https://www.aaai.org/ojs/index.php/AAAI/article/view/3855
-=== ---Apr 09 ---===
+Seminar: Bing
-'''Double Header'''
+Schwab, Patrick, and Walter Karlen. "CXPlain: Causal explanations for model interpretation under uncertainty." Advances in Neural Information Processing Systems. 2019.[https://papers.nips.cc/paper/9211-cxplain-causal-explanations-for-model-interpretation-under-uncertainty]
-Presenters: Liang Tong and Kathryn Sarullo
+Lab meeting: Celebration
-Paper 1: Z. Zhang, C. Yan, D.A. Mesa, J. Sun, and B.A. Malin, Ensuring Electronic Medical Record Simulation through Better Training, Modeling, and Evaluation, Journal of the American Medical Informatics Association, Volume 27, Issue 1, January 2020, Pages 99–108. URL: https://doi.org/10.1093/jamia/ocz161
+===  --- Sep 10 --- ===
-Paper 2: P. Washington et al.,Feature Selection and Dimension Reduction of Social Autism Data, Pacific Symposium on Biocomputing 2020. URL: https://psb.stanford.edu/psb-online/proceedings/psb20/Washington.pdf
+Seminar: Haoran
-=== ---Apr 16 ---===
+Lamport, L. (2019). The part-time parliament. In Concurrency: the Works of Leslie Lamport (pp. 277-317).
-Presenter: Sayantan Kumar
-Paper: Deep Learning Global Glomerulosclerosis in Transplant Kidney Frozen Sections, IEEE Transactions on Medical Imaging, 2018, J. Marsh, et al. ([https://ieeexplore.ieee.org/document/8398488])
+Lamport, L. (2001). Paxos made simple. ACM Sigact News, 32(4), 18-25. [https://dl.acm.org/doi/pdf/10.1145/1281100.1281103?casa_token=OqME2nQOrhsAAAAA:MqeYSeAvx1dZ72Lp3QzToDYKmNnnZb57qwJdmXNGlnNN3pfiVeFHxxvrrtXRlsBuHCHlfc2DKD4C Paper]
-=== ---Apr 23 ---===
-Presenter: Raj Venkatesaramani
-Paper: Peng Han, Peng Yang, Peilin Zhao, Shuo Shang, Yong Liu, Jiayu Zhou, Xin Gao, and Panos Kalnis. 2019. GCN-MF: Disease-Gene Association Identification By Graph Convolutional Networks and Matrix Factorization. In Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining (KDD ’19). Association for Computing Machinery, New York, NY, USA, 705–713. URL: https://www.kdd.org/kdd2019/accepted-papers/view/gcn-mf-disease-gene-association-identification-by-graph-convolutional-netwo
+Lab meeting: Jingwen
 ==Previous Semesters==
+* [[Seminar Summer 2020|Summer 2020]]
+* [[Lab Meeting Spring 2020|Spring 2020]]
 * [[Seminar Fall 2019|Fall 2019]]
 * [[Seminar Summer 2019|Summer 2019]]
@@ Line 168: / Line 221: @@
 ==Previous Lab Meetings==
-* [[Labmeeting Spring 2020|Spring 2020]]
 * [[Labmeeting Fall 2014|Fall 2014]]
 * [[Labmeeting Summer 2014|Summer 2014]]
 * [[Labmeeting Spring 2014|Spring 2014]]

Difference between revisions of "Seminar Summer 2020"

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