538 citations · 1.1k across the 31 of their papers we have counts for
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Unraveling the Interconnected Axes of Heterogeneity in Machine Learning for Democratic and Inclusive Advancements
Maryam Molamohammadi, Afaf Taik, Nicolas Le Roux +1
The growing utilization of machine learning (ML) in decision-making processes raises questions about its benefits to society. In this study, we identify and analyze three axes of h…
Joint Prompt Optimization of Stacked LLMs using Variational Inference
Alessandro Sordoni, Xingdi Yuan, Marc-Alexandre Côté +6
Large language models (LLMs) can be seen as atomic units of computation mapping sequences to a distribution over sequences. Thus, they can be seen as stochastic language layers in…
Decision-Aware Actor-Critic with Function Approximation and Theoretical Guarantees
Sharan Vaswani, Amirreza Kazemi, Reza Babanezhad +1
Actor-critic (AC) methods are widely used in reinforcement learning (RL) and benefit from the flexibility of using any policy gradient method as the actor and value-based method as…
Target-based Surrogates for Stochastic Optimization
Jonathan Wilder Lavington, Sharan Vaswani, Reza Babanezhad +2
We consider minimizing functions for which it is expensive to compute the (possibly stochastic) gradient. Such functions are prevalent in reinforcement learning, imitation learning…