The weighted averages algorithm revisited

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Collaborative learning algorithms, such as distributed SGD (or D-SGD), are prone to faulty machines that may deviate from their prescribed algorithm because of software or hardware bugs, poisoned data or malicious behaviors. While many solutions have been ...

In this thesis, we give new approximation algorithms for some NP-hard problems arising in resource allocation and network design. As a resource allocation problem, we study the Santa Claus problem (also known as the MaxMin Fair Allocation problem) in which ...

In this article, we consider decentralized optimization problems where agents have individual cost functions to minimize subject to subspace constraints that require the minimizers across the network to lie in low-dimensional subspaces. This constrained fo ...

One of the most basic graph problems, All-Pairs Shortest Paths (APSP) is known to be solvable in n^{3-o(1)} time, and it is widely open whether it has an O(n^{3-ε}) time algorithm for ε > 0. To better understand APSP, one often strives to obtain subcubic t ...

Weighted flow time is a fundamental and very well-studied objective function in scheduling. In this paper, we study the setting of a single machine with preemptions. ...

Non-convex constrained optimization problems have become a powerful framework for modeling a wide range of machine learning problems, with applications in k-means clustering, large- scale semidefinite programs (SDPs), and various other tasks. As the perfor ...

In this manuscript, we present a collective multigrid algorithm to solve efficiently the large saddle-point systems of equations that typically arise in PDE-constrained optimization under uncertainty, and develop a novel convergence analysis of collective ...

We propose a variance reduced algorithm for solving monotone variational inequalities. Without assuming strong monotonicity, cocoercivity, or boundedness of the domain, we prove almost sure convergence of the iterates generated by the algorithm to a soluti ...

Astrobot swarms are used to capture astronomical signals to generate the map of the observable universe for the purpose of dark energy studies. The convergence of each swarm in the course of its coordination has to surpass a particular threshold to yield a ...

In this work, we develop timing-driven CAD support for FPGA architectures with direct connections between LUTs. We do so by proposing an efficient ILP-based detailed placer, which moves a carefully selected subset of LUTs from their original positions, so ...

We study the computations that Bayesian agents undertake when exchanging opinions over a network. The agents act repeatedly on their private information and take myopic actions that maximize their expected utility according to a fully rational posterior be ...

Semi-Lagrangian (SL) schemes are of utmost relevance to simulate two-phase flows where advection dominates. The combination of SL schemes with the finite element (FE) method and arbitrary Lagrangian-Eulerian (ALE) dynamic meshes yields a strong ingredient ...

Proximal splitting methods are standard tools for nonsmooth optimization. While primal-dual methods have become very popular in the last decade for their flexibility, primal methods may still be preferred for two reasons: acceleration schemes are more effe ...

This thesis focuses on designing spectral tools for graph clustering in sublinear time. With the emergence of big data, many traditional polynomial time, and even linear time algorithms have become prohibitively expensive. Processing modern datasets requir ...

Two prominent categories for achieving coordinated multirobot displacement are flocking and navigation in formation. Both categories have their own body of literature and characteristics, including their respective advantages and disadvantages. While typic ...

We are interested in a reduced order method for the efficient simulation of blood flow in arteries. The blood dynamics is modeled by means of the incompressible Navier–Stokes equations. Our algorithm is based on an approximated domain-decomposition of the ...

We show that a constant factor approximation of the shortest and closest lattice vector problem in any l(p)-norm can be computed in time 2((0.802 + epsilon)n). This matches the currently fastest constant factor approximation algorithm for the shortest vect ...

The Learning Parity with Noise (LPN) problem is a famous cryptographic problem consisting in recovering a secret from noised samples. This problem is usually solved via reduction techniques, that is, one reduces the original instance to a smaller one befor ...

We present a quasilinear time algorithm to decide the word problem on a natural algebraic structures we call orthocomplemented bisemilattices, a subtheory of boolean algebra. We use as a base a variation of Hopcroft, Ullman and Aho algorithm for tree isomo ...

We study different symbolic algorithms to solve two related reconfiguration problems on graphs: the token swapping problem and the permutation routing via matchings problem. Input to both problems is a connected graph with labeled vertices and a token in e ...

The weighted averages algorithm revisited

Chattez avec Graph Search

Robust Collaborative Learning with Linear Gradient Overhead

Approximation Algorithms for Allocation and Network Design

Quantization for Decentralized Learning Under Subspace Constraints

Faster Monotone Min-Plus Product, Range Mode, and Single Source Replacement Paths

A (2+epsilon)-Approximation Algorithm for Preemptive Weighted Flow Time on a Single Machine

Augmented Lagrangian Methods for Provable and Scalable Machine Learning

A multigrid method for PDE-constrained optimization with uncertain inputs

Forward-reflected-backward method with variance reduction

Learning convergence prediction of astrobots in multi-object spectrographs

Detailed Placement for Dedicated LUT-Level FPGA Interconnect

Bayesian Decision Making in Groups is Hard

One- and two-step semi-Lagrangian integrators for arbitrary Lagrangian-Eulerian-finite element two-phase flow simulations

Yapa: Accelerated Proximal Algorithm For Convex Composite Problems

Sublinear Algorithms for Spectral Graph Clustering

Hybrid Flock - Formation Control Algorithms

Model order reduction of flow based on a modular geometrical approximation of blood vessels

Approximate CVPp in time 2(0.802n)

Solving the Learning Parity with Noise Problem Using Quantum Algorithms

Equivalence Checking for Orthocomplemented Bisemilattices in Log-Linear Time

Symbolic Algorithms for Token Swapping