Course:CPSC522/February2016

February Assignment

(February will spill into March, and the March assignment will spill into April.) Your February assignment is to describe some research that has been published. You should choose two papers, by different authors (no authors in common) where one builds on the other. You should describe the background, and then describe the incremental contribution of one paper over the other. What was the actual contribution of the latter paper? The reader should be able to understand the problem, where it fits into the big picture, the solution proposed and how that solution was evaluated. Add your own thoughts on how successful it was and how it can be improved. See http://www.cs.ubc.ca/~poole/cs522/2016/readings.html for some suggested topics.

Extra Rules

• You need to follow the rules on the main page and you should follow the guidelines there.
• Each page should have a principle author. You do not need co-authors but can have co-authors; co-authorship is encouraged. If others help you with your page, you should help them too.
• You need to add your page to the table of contents in a position that makes sense. Fell free to edit and change the structure of the table of content to give it a coherent structure.
• You will need to give a presentation.
• Please choose a topic that is different from other courses that you have done (or else you need to negotiate with the instructors to make sure you are not counting the same work multiple times).
• You should refer to wiki pages and to other research papers as appropriate. It should be clear what the two papers you are describing, but you should also refer to other papers.

Key Dates

• February 24 - choose pages
• March 7 - First Draft ready for critiquing
• March 7 & 9 - In class presentations. 5 minute talk + 2 minutes for questions.
• March 10 - Critiques due
• March 14 - Final pages ready for marking
• March 17 - Marking Completed

Marking Scheme

Here is a tentative marking scheme. This is subject to change. Feel free to add questions, and edit the questions if they do not make sense.

I a scale of 1 to 5, where 1 means "strongly disagree" and 5 means "strongly agree" please rate and comment on the following:

• The topic is relevant for the course.
• The writing is clear and the English is good.
• The page is written at an appropriate level for CPSC 522 students (where the students have diverse backgrounds).
• The formalism (definitions, mathematics) was well chosen to make the page easier to understand.
• The abstract is a concise and clear summary.
• There were appropriate (original) examples that helped make the topic clear.
• There was appropriate use of (pseudo-) code.
• It had a good coverage of representations, semantics, inference and learning (as appropriate for the topic).
• It is correct.
• It was neither too short nor too long for the topic.
• It was an appropriate unit for a page (it shouldn't be split into different topics or merged with another page).
• It links to appropriate other pages in the wiki.
• The references and links to external pages are well chosen.
• I would recommend this page to someone who wanted to find out about the topic.
• This page should be highlighted as an exemplary page for others to emulate.

If I was grading it out of 20, I would give it:

Talk Schedule

Monday Apr 7

1. Jiahong Chen, "Density-Based Unsupervised Learning"
2. Yu Yan, "Interactive Preference Elicitation"

Wed April 9

1. Yan Zhao, "Convolutional Neural Networks"
2. Arthur Sun, "Recommendation System using Matrix Factorization"
3. Jordon Johnson, "Learning Markov Logic Network Structure"
4. Mehrdad Ghomi, "Maximum Entropy Markov Models"
5. Ritika Jain, "Inductive Logic Programming"
6. Junyuan Zheng, "Problog"
7. Prithu Banerjee, "Latent Dirichlet Allocation"
8. Samprity Kashyap, "Ontology : Ontology Based Search Engine"

Monday Apr 14

1. Abed Rahman, "Predicting Affect of User's Interaction with an Intelligent Tutoring System"
2. Danya Wang, "Record Linkage and identity uncertainty"
3. Bahare Fatemi, "Identity Uncertainty"
4. Ke Dai, "Robot Scientist"
5. Adnan Reza, "Predicting Human Behavior in Normal-Form Games"
6. Ricky Chen, "Generative Adversarial Networks"
7. Yaashaar Hadadian Pour, "User-Adaptive Information Visualization"
8. Tanuj Kr Aasawat, "Deep Neural Network"