Class Presentations / Discussions

Presentation / Discussion on Tuesday, September 20
- Presenters: Selina Akter, Svetlana Lockwood
- Send paper: Tuesday, September 13
- Critiques due: Thursday, September 15
- Topic: semi-supervised learning
- Slides Part 1, Part 2, Part 3
Presentation / Discussion on Thursday, September 22
- Presenters: Joel Helkey, Ngizambote Mavana
- Send paper: Thursday, September 15
- Critiques due: Tuesday, September 20
- Topic: online learning and machine learning for security
- Slides Part 1
Presentation / Discussion on Tuesday, October 11
- Presenters: Ehsan Nazerfard, Gokcen Cilinngir
- Send paper: Tuesday, October 4
- Critiques due: Thursday, October 6
- Topic: probabilistic graphs, graph-based clustering
- Slides Part 1, Part 2
Presentation / Discussion on Thursday, October 13
- Presenters: Zachary Wemlinger, Abhik Ray
- Send paper: Tuesday, October 4
- Critiques due: Thursday, October 6
- Topic: graph analysis, social network mining
- Slides Part 1
Presentation / Discussion on Tuesday, October 18
- Presenters: Inna Rytsareva, Brian Thomas
- Send paper: Tuesday, October 11
- Critiques due: Thursday, October 13
- Topic: High-performance machine learning
- Slides Part 1
Presentation / Discussion on Thursday, October 27
- Presenters: Yunbing Tan, Barnan Das
- Send paper: Tuesday, October 18
- Critiques due: Thursday, October 20
- Topic: convex optimization, sampling
- Slides Part 1
Presentation / Discussion on Tuesday, November 1
- Presenters: Jeyanthi Narasi, Bryan Minor
- Send paper: Tuesday, October 25
- Critiques due: Thursday, October 27
- Topic: spectral clustering, particle filters
- Slides Part 1, Part 2
Presentation / Discussion on Thursday, November 3
- Presenters: Salikh Bagaveyev, Haque
- Send paper: Thursday, October 27
- Critiques due: Tuesday, November 1
- Topic: active learning
- Slides Part 1, Part 2, Part 3
Presentation / Discussion on Tuesday, November 8
- Presenters: Vikramaditya Jakkula, Prafulla Dawadi
- Send paper: Tuesday, November 1
- Critiques due: Thursday, November 3
- Topic: anomaly detection, rare class learning
- Slides Part 1
Presentation / Discussion on Thursday, November 17
- Presenter: Yujue Wang
- Send paper: Tuesday, November 8
- Critiques due: Thursday, November 10
- Topic: forecasting
Presentation / Discussion on Tuesday, December 6
- Presenter: Jen Williams, Kyle Feuz
- Send paper: Tuesday, November 29
- Critiques due: Thursday, December 1
- Topic: reinforcement learning, multi-task learning learning
- Slides Part 1