Decomposition of Geometric Set Systems and Graphs

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We consider distributed optimization over several devices, each sending incremental model updates to a central server. This setting is considered, for instance, in federated learning. Various schemes have been designed to compress the model updates in orde ...

The metric dimension (MD) of a graph is a combinatorial notion capturing the minimum number of landmark nodes needed to distinguish every pair of nodes in the graph based on graph distance. We study how much the MD can increase if we add a single edge to t ...

In this paper, we formulate a mixed integer linear program (MILP) for the simulated maximum likelihood estimation (MLSE) problem and devise a Benders decomposition approach to speed up the solution process. This framework can be applied to any advanced dis ...

Consider the family of bounded degree graphs in any minor-closed family (such as planar graphs). Let d be the degree bound and n be the number of vertices of such a graph. Graphs in these classes have hyperfinite decompositions, where, one removes a small ...

This paper proposes a method for the construction of quadratic serendipity element (QSE) shape functions on planar convex and concave polygons. Existing approaches for constructing QSE shape functions are linear combinations of the pair-wise products of ge ...

In this paper, we analyze the recently proposed stochastic primal-dual hybrid gradient (SPDHG) algorithm and provide new theoretical results. In particular, we prove almost sure convergence of the iterates to a solution with convexity and linear convergenc ...

In light of the energy transition, it becomes a widespread solution to decentralize and to decarbonize energy systems. However, limited transformer capacities are a hurdle for large-scale integration of solar energy in the electricity grid. The aim of this ...

Information retrieval (IR) systems such as search engines are important for people to find what they need among the tremendous amount of data available in their organization or on the Internet. These IR systems enable users to search in a large data collec ...

This work develops new algorithms with rigorous efficiency guarantees for infinite horizon imitation learning (IL) with linear function approximation without restrictive coherence assumptions. We begin with the minimax formulation of the problem and then o ...

With the increasing prevalence of massive datasets, it becomes important to design algorithmic techniques for dealing with scenarios where the input to be processed does not fit in the memory of a single machine. Many highly successful approaches have emer ...

There has been a recent surge of interest in the study of asymptotic reconstruction performance in various cases of generalized linear estimation problems in the teacher-student setting, especially for the case of i.i.d standard normal matrices. Here, we g ...

We consider the problem of provably finding a stationary point of a smooth function to be minimized on the variety of bounded-rank matrices. This turns out to be unexpectedly delicate. We trace the difficulty back to a geometric obstacle: On a nonsmooth se ...

Decomposition of Geometric Set Systems and Graphs

Chattez avec Graph Search

Stochastic distributed learning with gradient quantization and double-variance reduction

On the robustness of the metric dimension of grid graphs to adding a single edge

A Benders decomposition for maximum simulated likelihood estimation of advanced discrete choice models

Random walks and forbidden minors III: poly(d epsilon(-1))-time partition oracles for minor-free graph classes

Quadratic serendipity element shape functions on general planar polygons

On The Convergence Of Stochastic Primal-Dual Hybrid Gradient

Decomposition Strategy for Districts as Renewable Energy Hubs

Graph Embedding for Retrieval

Proximal Point Imitation Learning

Space-Efficient Representations of Graphs

Asymptotic Errors for Teacher-Student Convex Generalized Linear Models (Or: How to Prove Kabashima’s Replica Formula)

Finding stationary points on bounded-rank matrices: a geometric hurdle and a smooth remedy