56 citations · 72 across the 8 of their papers we have counts for
21 papers
Spectral Regularization: an Inductive Bias for Sequence Modeling
Kaiwen Hou, Guillaume Rabusseau
Various forms of regularization in learning tasks strive for different notions of simplicity. This paper presents a spectral regularization technique, which attaches a unique induc…
Extracting Weighted Automata for Approximate Minimization in Language Modelling
Clara Lacroce, Prakash Panangaden, Guillaume Rabusseau
In this paper we study the approximate minimization problem for language modelling. We assume we are given some language model as a black box. The objective is to obtain a weighted…
Lower and Upper Bounds on the VC-Dimension of Tensor Network Models
Behnoush Khavari, Guillaume Rabusseau
Tensor network methods have been a key ingredient of advances in condensed matter physics and have recently sparked interest in the machine learning community for their ability to…
Optimal Spectral-Norm Approximate Minimization of Weighted Finite Automata
Borja Balle, Clara Lacroce, Prakash Panangaden +2
We address the approximate minimization problem for weighted finite automata (WFAs) with weights in , over a one-letter alphabet: to compute the best possible approxima…
Assessing the Impact: Does an Improvement to a Revenue Management System Lead to an Improved Revenue?
Greta Laage, Emma Frejinger, Andrea Lodi +1
Airlines and other industries have been making use of sophisticated Revenue Management Systems to maximize revenue for decades. While improving the different components of these sy…
Quantum Tensor Networks, Stochastic Processes, and Weighted Automata
Siddarth Srinivasan, Sandesh Adhikary, Jacob Miller +2
Modeling joint probability distributions over sequences has been studied from many perspectives. The physics community developed matrix product states, a tensor-train decomposition…