For basic:
GAN: https://www.youtube.com/watch?v=AJVyzd0rqdc
Causality: https://www.youtube.com/watch?v=7gktywp6j1Y
Deep Learning:
(Summer School) http://videolectures.net/deeplearning2016_montreal/?q=machine%20learning%20summer%20school
https://www.youtube.com/watch?v=cbeTc-Urqak&list=PLoRl3Ht4JOcdU872GhiYWf6jwrk_SNhz9
Active learning: http://videolectures.net/icml09_dasgupta_langford_actl/?q=active%20learning
Reinforcement learning: http://videolectures.net/rldm2015_silver_reinforcement_learning/
Graphical models: http://videolectures.net/mlss2012_ghahramani_graphical_models/?q=Bayesian%20graphical%20models
Bayesian Inference: http://videolectures.net/mlss09uk_bishop_ibi/?q=Bayesian%20graphical%20models
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IRKM Paper Reading Day
Lanbo:
Jian: Towards a Theory Model for Product Search (www2011), Predicting consumer behavior with Web search
Sarah: Diversifying search results of controversial queries, Entropy of Search Logs: How Hard is Search? With Personalization? With Backoff?
Aaron:
Yunfei:
Qi:
Shawn: In search of quality in crowdsourcing for search engine evaluation, Future directions in learning to rank, Yahoo! Learning to Rank Challenge Overview (bonus)
2011-2012 (Birthday seminar: , E2-475)
Nov. 3 Aaron (12:30pm Oct. 5)
Dec. 1, Jian Wang (1pm Oct. 1)
Dec. 7, Sarah Tyler (11am, Dec. 7)
Feb. 23, Yi Zhang
Mar. 12, YunFei Chen
Mar. 19, Lanbo Zhang
Spring 2011 3pm-4pm E2-475
Week 1
Week 2 TREC (Qianli qxing@soe)
Week 3 SIGIR 2010 Review (Lanbo lanbo@soe)
Week 4 NLP for IR (Aaron amichelo@soe)
Week 5 Jian
Week 6 Lanbo
Week 7 Qianli
Week 8 Aaron
Week 9 Qi
Week 10 Trust-based Search and Recommender Systems in a Networked Marketplace. Dr. Neel Sundaresan, EBAY Research (11:30am, Simularium. E2-180)
Fall 2010
Oct 6 Wed. 10:30-1:30 E2-475
10:30-10:40: introduction
10:40-11:00: Lanbo Zhang
11:00-11:20: Sarah Tyler
11:20-11:40: Qianli Xing
11:40-12:10: Shawn Wolf: Multiple Aspect Information Retrieval
12:10-12:30: Jiazhong Nie
12:30-12:40: Break, Lunch will be provided
12:40-1:00: Jian Wang
1:00-1:30: Xiaoou Li
Spring 2010
Week 2: NIPS Review (Jiazhong)
Week 3: WSDM review (Sarah)
Week 4: Large scale machine learning (optimizating algorithms: Mario & Rob: stochastic gradient descent, online learning, conjugrate gradient descent, variational methods, message passing)
Week 5: Large scale machine learning (Mapreduce, RPC, GPU etc. Lanbo)
Week 6: Marketing research related to recommender systems (Jian & Tao)
Week 7: Research presentation (Sarah)
Week 8: Research presentation (Jiazhong)
Week 9: Research presentation (Jian, Shawn)
Week 10: Research presentation (Lanbo)
Fall 2009 (10:00am - 11:00am Tuesday, E2-475)
Week 9: Yize Li; Lanbo (TREC review)
Week 10: Xing Xing; Lanbo
summer 2009 (E2-475, 12pm-2pm Tuesday, Pizza)
Note to presentor: please email irkm-lab mailing list the papers you will discuss by Saturday. Please upload your presentation slides here. Here is a guidance for reading other's paper
Past Topics to review in winter/spring 2009 (E2-475, 12pm-1pm, Pizza)
Attachment | Size |
---|---|
20090212_Personalized_Information_Retrieval.pdf | 232.31 KB |
2009_02_05_transferlearning.pdf | 201.55 KB |
A_Framework_for_Learning_Predictive_Structures_from_Multiple_Tasks_and_Unlabeled_Data.p df | 626.93 KB |
IRKMpowerpoint_template08.ppt | 160.5 KB |
MatrixFactReview.pdf | 455.51 KB |
NetworkModelsNoteJianWang.doc | 32.5 KB |
note - Mining larget grpahs laws and tools.pdf | 32.63 KB |
DiscussionNotePredictiveMethodsforTextMining.pdf | 50.53 KB |
Note for Graphical Model.pdf | 157.53 KB |
Introduction to Mechanical Turk.pdf | 224.83 KB |
HadoopTutorial.ppt | 2.27 MB |
Large Scale Machine Learning - Stochastic Gradient Descent | 917.52 KB |
MapReduce&GPU.ppt | 967.33 KB |
TREC 2009 Review.ppt | 1.76 MB |
SIGIR 2010 Review - new.ppt | 944.5 KB |