From the 2 of 15 linked papers with an AI index.
15 papers
Generative Learning for Quantum Measurement Design
Jun Dai, Olivier Nahman-Lévesque, Guillaume Rabusseau +2
Extracting quantum information from a quantum state is a fundamental task of quantum computation, often requiring the estimation of many non-commuting observables under a finite me…
Benefits and Limitations of Communication in Multi-Agent Reasoning
Michael Rizvi-Martel, Satwik Bhattamishra, Neil Rathi +2
The paper introduces a theoretical framework for analyzing how communication among multiple agents affects their ability to perform complex reasoning tasks, providing bounds on req…
From Expressivity to Sample Complexity: Narrow Teachers for Transformers via C-RASP
Michael Rizvi-Martel, Satwik Bhattamishra, Guillaume Rabusseau +1
The paper derives preliminary sample complexity bounds for learning C‑RASP constructions with Transformer models, linking their expressive power to learnability.
TN-SHAP-G: Graph-Structured Tensor Network Surrogates for Shapley Values and Interactions
Farzaneh Heidari, Guillaume Rabusseau
Shapley values are a widely used tool for attributing importance and interactions among input variables in black-box models, but their computation involves a function defined over…
Tractable Shapley Values and Interactions via Tensor Networks
Farzaneh Heidari, Chao Li, Guillaume Rabusseau
We show how to replace the O(2^n) coalition enumeration over n features behind Shapley values and Shapley-style interaction indices with a few-evaluation scheme on a tensor-network…
Tensor Cookbook: Mastering Tensors through Diagrams
Beheshteh T. Rakhshan, Guillaume Rabusseau
High-dimensional data arise naturally in many areas of science and engineering, including machine learning, signal processing, computational physics, and statistics. Such data are…