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19 papers · 1 filter
Unifying lower bounds for algebraic machines, semantically
Thomas Seiller, Luc Pellissier, Ulysse Léchine
This paper presents a new abstract method for proving lower bounds in computational complexity. Based on the notion of topological and measurable entropy for dynamical systems, it…
Numerical methods for piecewise deterministic Markov processes with boundary
Ludovic Goudenège
In this paper is described the general aspect of a numerical method for piecewise determin-istic Markov processes with boundary. Under very natural hypotheses, a crucial result abo…
Distributed Hypothesis Testing with Collaborative Detection
Pierre Escamilla, Abdellatif Zaidi, Michèle Wigger
A detection system with a single sensor and two detectors is considered, where each of the terminals observes a memoryless source sequence, the sensor sends a message to both detec…
Generalizations of the associative operad and convergent rewrite systems
Cyrille Chenavier, Christophe Cordero, Samuele Giraudo
The associative operad is the quotient of the magmatic operad by the operad congruence identifying the two binary trees of degree . We introduce here a generalization of the ass…
Optimal Bounds on the VC-dimension
Monika Csikos, Andrey Kupavskii, Nabil H. Mustafa
The VC-dimension of a set system is a way to capture its complexity and has been a key parameter studied extensively in machine learning and geometry communities. In this paper, we…
A Review of Innovation-Based Methods to Jointly Estimate Model and Observation Error Covariance Matrices in Ensemble Data Assimilation
Pierre Tandeo, Pierre Ailliot, Marc Bocquet +4
Data assimilation combines forecasts from a numerical model with observations. Most of the current data assimilation algorithms consider the model and observation error terms as ad…