8 citations · 9 across the 8 of their papers we have counts for
3 papers · 1 filter
Thompson Sampling via Fine-Tuning of LLMs
Nicolas Menet, Aleksandar Terzić, Michael Hersche +2
Bayesian optimization in large unstructured discrete spaces is often hindered by the computational cost of maximizing acquisition functions due to the absence of gradients. We prop…
Structured Sparse Transition Matrices to Enable State Tracking in State-Space Models
Aleksandar Terzić, Nicolas Menet, Michael Hersche +2
Modern state-space models (SSMs) often utilize transition matrices which enable efficient computation but pose restrictions on the model's expressivity, as measured in terms of the…
LITE: Efficiently Estimating Gaussian Probability of Maximality
Nicolas Menet, Jonas Hübotter, Parnian Kassraie +1
We consider the problem of computing the probability of maximality (PoM) of a Gaussian random vector, i.e., the probability for each dimension to be maximal. This is a key challeng…