7:00 – 3:30 ASRC TL
- Register for Tech Summit – done
- Ask for a week of time to prep for talk – done
- Panos read the paper and has some suggestions. Need to implement
- This might be important: Neural Logic Machines
- We propose the Neural Logic Machine (NLM), a neural-symbolic architecture for both inductive learning and logic reasoning. NLMs exploit the power of both neural networks—as function approximators, and logic programming—as a symbolic processor for objects with properties, relations, logic connectives, and quantifiers. After being trained on small-scale tasks (such as sorting short arrays), NLMs can recover lifted rules, and generalize to large-scale tasks (such as sorting longer arrays). In our experiments, NLMs achieve perfect generalization in a number of tasks, from relational reasoning tasks on the family tree and general graphs, to decision making tasks including sorting arrays, finding shortest paths, and playing the blocks world. Most of these tasks are hard to accomplish for neural networks or inductive logic programming alone.
- Need to read the Nature “Behavior” paper. Notes probably go straight into the dissertation lit review – done
- Continuing to read Army of None, which is ridiculously good. This figure has been making me think: This implies that the idea that a set of diverse ML systems all agreeing is a warning condition is worth exploring.
- Finished read through of Tao’s paper
- Need to find a cardiologist for Arpita