1 citations · 1 across the 4 of their papers we have counts for
5 papers
Fork-and-Flush: Escaping Idea Basins in Autoresearch Agents
Ziyang Cai, Christos Ziakas, Vasilis Kontonis +5
Autoresearch agents tackle open-ended problems by repeatedly proposing candidate solutions, evaluating them, and using feedback to guide subsequent experiments. We show that indepe…
Towards Shutdownable Agents: Generalizing Stochastic Choice in RL Agents and LLMs
Carissa Cullen, Harry Garland, Alexander Roman +3
Misaligned artificial agents might resist shutdown. One proposed solution is to train agents to lack preferences between different-length trajectories. The Discounted Reward for Sa…
Towards Shutdownable Agents via Stochastic Choice
Elliott Thornley, Alexander Roman, Christos Ziakas +2
The POST-Agents Proposal (PAP) is an idea for ensuring that advanced artificial agents never resist shutdown. A key part of the PAP is using a novel `Discounted Reward for Same-Len…
BackboneLearn: A Library for Scaling Mixed-Integer Optimization-Based Machine Learning
Vassilis Digalakis, Christos Ziakas
We present BackboneLearn: an open-source software package and framework for scaling mixed-integer optimization (MIO) problems with indicator variables to high-dimensional problems.…
Scalable Econometrics on Big Data -- The Logistic Regression on Spark
Aurélien Ouattara, Matthieu Bulté, Wan-Ju Lin +6
Extra-large datasets are becoming increasingly accessible, and computing tools designed to handle huge amount of data efficiently are democratizing rapidly. However, conventional s…