🛬 Vancouver for #icml, I’ll be presenting our work on Subgoal Guided Heuristic Search with Learned Subgoals on Tuesday from 4:30-7:00pm. Come stop by and say hello 👋

🧵1/ New paper! 📄 Subgoal-Guided Policy Heuristic Search with Learned Subgoals, led by my PhD student @tuero.ca. arxiv.org/pdf/2506.07255 This paper follows the Levin tree search (LTS) research line and focuses on learning subgoal-based policies.

Excited to share our paper "Subgoal-Guided Policy Heuristic Search with Learned Subgoals" has been accepted to #icml2025! Paper Preview: arxiv.org/pdf/2506.07255 I'll be attending ICML-25 in Vancouver, and I'm looking forward to chatting with anyone who is interested in our work!

I implemented a pytorch-like cuda accelerated autograd library in C++ to learn cuda and the performance pain points when using these frameworks. Check it out! github.com/tuero/tinyte... #cpp #cplusplus #cuda #MLSky #DeepLearning

Sometimes it’s beneficial to try and reformulate a problem into another so that you can lean on the solutions the other provides. A Conv2D can be rewritten as a series of matrix multiplications, and I’ve gained a 2x speed up by reusing my fast matmul kernels for my Conv2D implementation!

So much for sleep, I’m glued here finding everyone to follow!