Program

For Participants

For Authors and Reviewers

Organization

Misc

UAI Workshops Program

Monday, July 15th


Workshops

1. Bayes Application Workshops
2. Approaches to Causal Structure Learning Workshop
3. New Challenges in E-Commerce Recommendations


Bayes Application Workshops (Room: Lake Washington A)

8:30am – Combined Applications Workshop Introductions

Application Workshop I: Big Data meets Complex Models

9:00 - 10:15
Session 1: Extracting information about individuals from complex data
  1. Identifying Learning Trajectories in an Educational Video Game – Kerr and Chung
  2. Using information to debug Complex Systems – Almond, Kim, Shute, & Ventura
  3. Transforming Personal Artifacts into Probabilistic Narratives – Rafatirad and Laskey
15' Open Discussion of Session 1
10:15 - 10:30 Coffee Break
10:30 - 11:45
Session 2: Combining Learning and Expert Opinion
  1. Bayesian Supervised Dictionary Learning – Babagholami-Mohamadabadi, Jourabloo, Zolfaghari, & Manzuir-Shalmani
  2. Learning Parameters by Prediction Markets and Kelly Rule for Graphical Models – Sun, Hanson, Twardy, & Laskey
  3. Predicting Latent Variables with Knowledge and Data: A Case Study in Trauma Care – Yet, Marsh, Perkins, Tai, & Fenton
15' Open Discussion of Session 2
11:45 - 13:00 Break (lunch on your own)

Application Workshop 2: Spatial, Temporal, and Network Models

13:00 - 14:30
Session 3
  1. An Object-oriented Spatial and Temporal Bayesian Network for Managing Willows in an American Heritage River Catchment – Wilkinson, Chee, Nicholson, & Quintana-Ascencio
  2. Product Trees for Gaussian Process Covariance in Sublinear Time – Moore & Russell
  3. Latent Topic Analysis for Predicting Group Purchasing Behavior on the Social Web – Sun, Yeh, Mengshoel, & Griss
15' Open Discussion of Session 3
14:30 - 14:45 Coffee Break
14:45 - 15:45
Session 4
  1. A lightweight inference method for image classification – Agosta and Pillai
  2. Exploring Multiple Dimensions of Parallelism in Junction Tree Message Passing – Zheng and Mengshoel
10' Open Discussion of Session 3
15:45 - 16:00 Coffee Break
16:00 - 17:00 Combined Applications Workshop Wrap-up and Planning Discussion

Approaches to Causal Structure Learning Workshop (Room: Lake Chelan)

8:45 - 10:00 Session 1 (75 minutes)
  • 8:45 - 9:20 Invited talk - David Heckerman
  • 9:20 - 9:55 Discovering Cyclic Causal Models with Latent Variables: A General SAT-Based Procedure - Hyttinen, Hoyer, Eberhardt, J√§rvisalo
10:00 - 10:30 Coffee Break
10:30 - 12:15 Session 2 (105 minutes)
  • 10:30 - 11:05 Reasoning about Independence in Probabilistic Models of Relational Data - Maier, Marazopoulou, Jensen
  • 11:05 - 11:40 A Sound and Complete Algorithm for Learning Causal Models from Relational Data - Maier, Marazopoulou, Arbour, Jensen
  • 11:40 - 12:15 Single World Intervention Graphs - Richardson and Robins
12:15 - 14:00 Break (lunch on your own)
14:00 - 15:25 Session 3 (85 minutes)
  • 14:00 - 14:50 Invited Talk - Joris Mooij
  • 14:50 - 15:25 Identifiability of binary directed graphical models with hidden variables - Allman, Rhodes, Stanghellini and Valtorta
15:25 - 15:35 Poster spotlights
15:35 - 16:50 Posters (and coffee from 16:00)
16:50 - 18:00 Session 4 (70 minutes)
  • 16:50 - 17:25 Maximum Likelihood estimation of structural nested logistic model with an instrumental variable - Matsouaka and Tchetgen
  • 17:25 - 18:00 A finite population test of the sharp null hypothesis for Compliers - Loh and Richardson

New Challenges in E-Commerce Recommendations (Room: Lake Coeur d'Alene)

8:30 - 9:30 Alex Smola
9:30 - 10:00 Coffee Break
Oral Presentation 1
  • 10:00 - 10:30 Ratings Re-specification for Rank Ordered Recommendations - Oluwasanmi Koyejo, Sreangsu Archaryya, Joydeep Ghosh
  • 10:30 - 11:00 On the Evaluation of Rating-Prediction and Ranking - Harald Steck
  • 11:00 - 11:30 Exploiting Similarity to Optimize Recommendations Lists from Click Feedback - Hastagiri Prakash Vanchinathan, Isidor Nikolic, Fabio De Bona, Andreas Krause
  • 11:30 - 12:15 Collaborative filtering Graphlab - Danny Bickson
12:15 - 14:00 Break (lunch on your own)
14:00 - 15:00 Recommendations at Netflix - Carlos Gomez Uribe (Netflix)
15:00 - 15:15 Coffee Break
Oral Presentation 2
  • 15:15 - 15:45 Lei Tang (Walmart Labs)
  • 15:45 - 16:15 Vaclav Petricek (eHarmony)
  • 16:15 - 16:45 Bo Long A ds Recommendation and Large-Scale Machine Learning at LinkedIn
16:45 - 17:00 Panel Discussion

Please visit our
Sponsors


microsoft research logo

artificial intelligence journal

amazon

google logo

cras logo

ITC logo

Facebook logo

IBM Research logo