18 citations · 65 across the 25 of their papers we have counts for
5 papers · 1 filter
Scalable Principal-Agent Contract Design via Gradient-Based Optimization
Tomer Galanti, Aarya Bookseller, Korok Ray
We study a bilevel \emph{max-max} optimization framework for principal-agent contract design, in which a principal chooses incentives to maximize utility while anticipating the age…
On the Alignment Between Supervised and Self-Supervised Contrastive Learning
Achleshwar Luthra, Priyadarsi Mishra, Tomer Galanti
Self-supervised contrastive learning (CL) has achieved remarkable empirical success, often producing representations that rival supervised pre-training on downstream tasks. Recent…
LLM Priors for ERM over Programs
Shivam Singhal, Priyadarsi Mishra, Eran Malach +1
We study program-learning methods that are efficient in both samples and computation. Classical learning theory suggests that when the target admits a short program description, fo…
Self-Supervised Contrastive Learning is Approximately Supervised Contrastive Learning
Achleshwar Luthra, Tianbao Yang, Tomer Galanti
Despite its empirical success, the theoretical foundations of self-supervised contrastive learning (CL) are not yet fully established. In this work, we address this gap by showing…
DisCO: Reinforcing Large Reasoning Models with Discriminative Constrained Optimization
Gang Li, Ming Lin, Tomer Galanti +2
The recent success and openness of DeepSeek-R1 have brought widespread attention to Group Relative Policy Optimization (GRPO) as a reinforcement learning method for large reasoning…