-
Notifications
You must be signed in to change notification settings - Fork 1
ML Papers
Timo Denk edited this page Jan 31, 2019
·
4 revisions
Collection of related/relevant ML papers. Ordered by priority (descending).
- Scarselli et al. (2008): The Graph Neural Network Model. First paper on graph nets.
- DeepMind (2018): Relational inductive biases, deep learning, and graph networks. Graph networks overview and generalization paper.
- Beltramelli (2017): pix2code: Generating Code from a Graphical User Interface Screenshot. CNN architecture that processes screenshots.
- Burges et al. (2015): Learning to Rank using Gradient Descent. Ranking with gradient descent, referenced by TF-ranking.
- Tie-Yan Liu (2009): Learning to Rank for Information Retrieval. Several book chapters on different ranking methods, such as pointwise, pairwise, and listwise.
- Burges (2015): Learning to Rank using Gradient Descent. Cited very frequently, perhaps more up to date than the Liu (2009) but GD focussed.
- Selsam et al. (2018). Learning a SAT Solver from Single-Bit Supervision. Single-bit supervision works in combination with gradient descent on graph problems.
- Cheng et al. (2007): A Neural Network Approach to Ordinal Regression. Output and loss for a bin-based ranking created for this Kaggle challenge.