Name: Texas Colloquium on Distributed Learning (TL;DR 2026)
Start: 2026-10-08T08:00:00-05:00
End: 2026-10-09T17:00:00-05:00
Location: Ralph S. O’Connor Building for Engineering and Science

Texas Colloquium on Distributed Learning (TL;DR 2026)

The Texas Colloquium on Distributed Learning: Frontiers on Agents and Systems (TL;DR 2026)
About this Event

The workshop on Future-proof Distributed/Federated Learning will take place October 8-9, 2026 in Houston, TX at Rice University.

Dates: October 8-9, 2026

Location: 5th Floor | O'Connor Building for Engineering and Science at Rice University | 6100 Main St, Houston, TX 77005

Summary: The Texas Colloquium on Distributed Learning: Frontiers on Agents and Systems (TL;DR 2026) will take place October 8–9, 2026, at Rice University in Houston, USA. To attend both days, it is probably best to arrive on the evening of October 7, 2026.

Information about the first TL;DR two workshops can be found here, here, and here.

We expect around 100 participants, including domestic and international researchers working in distributed learning, multi-agent systems, federated learning, optimization, large-scale AI systems, and responsible agentic AI. TL;DR 2026 has received support from the National Science Foundation, the Rice University Creative Venture Fund, the Rice University Department of Electrical and Computer Engineering, the Rice University Department of Mechanical Engineering, the Rice University Department of Computer Science, and the Ken Kennedy Institute, with the CORE-AI OWLS Cluster providing substantial assistance in organizing the workshop.

Aim of the symposium: The purpose of this workshop is to gather leading researchers on Federated Learning, Distributed Computing and Large-Scale ML at Rice University; the workshop will discuss and focus on efficient distributed learning algorithms on how to train such large models using less costly/specialized computing platforms. Topics of interest include, but are not limited to, Systems and infrastructure, Fairness, Hardware for on-device distributed learning, Privacy concerns, Optimization advances, Theoretical contributions, and Applications of distributed learning.

Website: View the workshop schedule, speaker lineup, venue and sponsorship details, and opportunities to participate through abstract or poster submissions. Website TBA.

Cost: The $100 registration fee covers breakfast, lunch, and refreshments on both days.

Refund Policy: A full refund is available up to one week out from the workshop. Refunds will not be processed within 7 days from the event start date.