Presentations
The presentations for the curation project and literature review will be on 11/30 in zoom . Given the we were not able to get a room of sufficient size, the presentations will be done over zoom and in my office. Beacon students will upload videos to cloud storage (an email was send to those students). For in-person and online students (sections 1 + 2), there will be two sessions of presentations. You are expected to attend the session for your group (but are of course welcome to attend the other session too) and actively participate in discussions (participation will factor into your grade for the presentations). Each group has 30 min in total and should leave at least 5 minutes for discussion. That is plan for 10 minutes each for the literature review and curation project. We will use the following zoom link:
https://uic.zoom.us/j/3273262403?pwd=RWN6TEZYOEZwemtqZWhCWDN0dXN4Zz09
The two sessions are:
Thu Nov 30 2:00pm-8:00pm
| timeslot | group | paper |
|---|---|---|
| 2:00-2:30 | 10 | Benchmarking Filtering Techniques for Entity Resolution |
| 2:30-3:00 | 11 | Auto-Tables: Synthesizing Multi-Step Transformations to Relationalize Tables without Using Examples |
| 3:00-3:30 | 12 | Explaining Dataset Changes for Semantic Data Versioning with Explain-Da-V |
| 3:30-4:00 | 13 | Witan: Unsupervised Labelling Function Generation for Assisted Data Programming |
| 4:00-4:30 | 14 | EDA4SUM: Guided Exploration of Data Summaries |
| 4:30-5:00 | 15 | Computing the Shapley Value of Facts in Query Answering |
| 5:00-5:30 | BREAK | |
| 5:30-6:00 | 16 | Erebus: Explaining the Outputs of Data Streaming Queries |
| 6:00-6:30 | 17 | Fast Detection of Denial Constraint Violations |
| 6:30-7:00 | 18 | FEDEX: An Explainability Framework for Data Exploration Steps |
| 7:00-7:30 | 19 | Automated Data Cleaning Can Hurt Fairness in Machine Learning-Based Decision Making |
| 7:30-8:00 | 20 | Efficient and Effective Data Imputation with Influence Functions |
Fri Nov 30: 12:00pm-4:00pm
| timeslot | group | paper |
|---|---|---|
| 12:00-12:30 | 21 | HypeR: Hypothetical Reasoning with What-If and How-to Queries Using a Probabilistic Causal Approach |
| 12:30-1:00 | 22 | Data Provenance for Recursive SQL Queries |
| 1:00-1:30 | 23 | Computing Rule-Based Explanations by Leveraging Counterfactuals |
| 1:30-2:00 | 24 | Data Shapley: Equitable Valuation of Data for Machine Learning |
| 2:00-2:30 | 25 | Xinsight: Explainable Data Analysis through the Lens of Causality |
| 2:30-3:00 | 26 | MATE: Multi-Attribute Table Extraction |
| 3:00-3:30 | 27 | Reptile: Aggregation-Level Explanations for Hierarchical Data |
| 3:30-4:00 | 28 | JEDI: These Aren'T the JSON Documents You'Re Looking for? |