8 citations · 9 across the 8 of their papers we have counts for
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Flash PD-SSM: Memory-Optimized Structured Sparse State-Space Models
Aleksandar Terzić, Francesco Carzaniga, Nicolas Menet +4
State-space models (SSMs) face a fundamental trade-off between efficiency and expressivity that is mainly dictated by the structure of the model's transition matrix. Unstructured t…
POETS: Uncertainty-Aware LLM Optimization via Compute-Efficient Policy Ensembles
Nicolas Menet, Andreas Krause, Abbas Rahimi
Balancing exploration with exploitation is a core challenge in black-box optimization and reinforcement learning. We introduce POETS (licy nsembles for $\t…
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…
MIMONets: Multiple-Input-Multiple-Output Neural Networks Exploiting Computation in Superposition
Nicolas Menet, Michael Hersche, Geethan Karunaratne +3
With the advent of deep learning, progressively larger neural networks have been designed to solve complex tasks. We take advantage of these capacity-rich models to lower the cost…