Big Data and Machine Learning Seminar

Spring 2019

Time & Location: Friday 10-12 at 289 Engineering VI.

Welcome to our Big Data and Machine Learning Seminar! Each week, we invite a researcher to give a talk on the latest advancement in big data and machine learning. Questions, as well as open discussions, are welcome in the seminar.

Everyone is encouraged to sign-up for the presentations!  Please email me (keweicheng@g.ucla.edu) the topic you would like to present beforehand if you are interested. The topic ideally is related to “Data mining and Machine Learning”. To make it easier for you to check the schedule, I create a google doc for the syllabus of our Big Data and Machine Learning Seminar where you can find the date and topic for the registered presentations.

Schedule

Date TITLE Speaker Abstract Paper Slide
04/05 Cancel
04/12 Generalization Error Bounds of Gradient Descent for Learning Over-parameterized Deep ReLU Networks Yuan Cao abstract pdf ppt
04/19 Cancel
04/26 Some recent advances in GANs Ting Chen abstract pdf ppt
05/03 Cancel
05/10 Cancel
05/17 Aggregates in Recursive Programs  and Declarative Algorithms for BigData Carlo Zaniolo abstract pdf ppt
05/21 Graph Representation Learning: Algorithms, Applications and Systems Jian Tang abstract pdf ppt
05/24 Geometric Scattering on Graphs and Manifolds Feng Gao abstract pdf ppt
05/31 Bridging adversarial robustness with generative adversarial networks Xuanqing Liu abstract pdf ppt
06/07 Robustness Verification of Neural Networks Huan Zhang abstract pdf ppt
06/10 Random Search and Reproducibility for Neural Architecture Search
Liam Li abstract pdf ppt

Winter 2018

Date TITLE Speaker Abstract Paper Slide
01/11 Multi-relational Knowledge Representation and Acquisition Muhao Chen abstract pdf ppt
01/18 Grounding Reinforcement Learning with Real-world Dialog Applications Zhou Yu abstract pdf ppt
01/25 Combining Behavioral and Generative Models for Product Recommendation and Design Julian McAuley abstract pdf ppt
02/01 Cancel
02/08 Recent advance on deep learning optimization theory Difan Zou abstract pdf ppt
02/15 A New Synthesis of Knowledge Representation and Learning Yitao Liang abstract pdf ppt
02/22 Cancel
03/01 Understanding the Bias and Data Efficiency of Uncertainty Sampling Steve Mussmann abstract pdf ppt
03/08 Cancel
03/15 Cancel
03/22 Embedding Uncertain Knowledge Graphs Xuelu Chen abstract pdf ppt

Fall 2018

Date TITLE Speaker Abstract Paper Slide
10/05 CoQA: A Conversational Question Answering Challenge Siva Reddy abstract pdf ppt
10/12 Efficient Deep Learning Ting Chen abstract pdf ppt
10/19 Optimization from A Continuous-time View Pan Xu abstract pdf ppt
10/26 Conversational Question Answering Scott Yih abstract pdf ppt
11/02 Modeling and Distinguishing User Behaviors on the Web Jyun-Yu Jiang abstract pdf ppt
11/09 Diversity-promoting and Large-scale ML for Healthcare Pengtao Xie abstract pdf ppt
11/16 Adopting Machine Learning techniques in Database System Jin Wang abstract pdf ppt
11/23 Thanksgiving Day (cancel)
11/30 Learning to Generate Language and Actions with Structured Agents William Wang abstract pdf ppt
12/07 Democratize Data Science: NLI to Data Xifeng Yan abstract pdf ppt
12/14 PaperRobot: Incremental Drafting of Ideas in Biomedical Domain Heng Ji abstract pdf ppt

Before Fall 2018

Schedule


If you have any questions or suggestions, feel free to email me (keweicheng@g.ucla.edu).