39 citations · 41 across the 4 of their papers we have counts for
4 papers
Puzzle: Distillation-Based NAS for Inference-Optimized LLMs
Akhiad Bercovich, Tomer Ronen, Talor Abramovich +23
Large language models (LLMs) offer remarkable capabilities, yet their high inference costs restrict wider adoption. While increasing parameter counts improves accuracy, it also bro…
Temporal support vectors for spiking neuronal networks
Ran Rubin, Haim Sompolinsky
When neural circuits learn to perform a task, it is often the case that there are many sets of synaptic connections that are consistent with the task. However, only a small number…
New Heuristics for Parallel and Scalable Bayesian Optimization
Ran Rubin
Bayesian optimization has emerged as a strong candidate tool for global optimization of functions with expensive evaluation costs. However, due to the dynamic nature of research in…
Theory of spike timing based neural classifiers
Ran Rubin, Remi Monasson, Haim Sompolinsky
We study the computational capacity of a model neuron, the Tempotron, which classifies sequences of spikes by linear-threshold operations. We use statistical mechanics and extreme…