Publications related to The Cost of Consistency: Submodular Maximization with Constant Recourse

Related publications (25)

Deterministic Online Bipartite Edge Coloring

We study online bipartite edge coloring, with nodes on one side of the graph revealed sequentially. The trivial greedy algorithm is (2 — o (1))-competitive, which is optimal for graphs of low maximum degree, Δ = O (log n) [BNMN IPL’92]. Numerous online edg ...

Society for Industrial and Applied Mathematics2025

Graph sparsification, sketching and adaptivity

Mikhail Makarov

Many challenges of modern graph processing stem from the fact that graphs have become massive and change frequently. Numerous techniques have been developed to address those issues, with graph cut sparsification offering to replace original graphs with th ...

EPFL2025

Constant-Cost Communication Is Not Reducible to k-Hamming Distance

Mika Tapani Göös, Nathaniel Idein Harms

Every known communication problem whose randomized communication cost is constant (independent of the input size) can be reduced to 𝑘-Hamming Distance, that is, solved with a constant number of deterministic queries to some 𝑘-Hamming Distance oracle. We ex ...

ACM2025

On the conjugate symmetry and sparsity of the harmonic decomposition of parametric surfaces with the randomised Kaczmarz method

Katrin Beyer

This limitation is circumvented by using scalable and non–memory–intensive harmonic expansions. In this paper, the projection of parametric surfaces onto disk and spherical harmonics bases is investigated, and three novel computationally efficient algorith ...

2024

Energy-Aware Decentralized Learning with Intermittent Model Training

Anne-Marie Kermarrec, Rafael Pereira Pires, Rishi Sharma, Marinus Abraham de Vos, Akash Balasaheb Dhasade

SKIPTRAIN is a novel Decentralized Learning (DL) algorithm, which minimizes energy consumption in decentralized learning by strategically skipping some training rounds and substituting them with synchronization rounds. These trainingsilent periods, besides ...

IEEE2024

Solving the Tensor Isomorphism Problem for Special Orbits with Low Rank Points: Cryptanalysis and Repair of an Asiacrypt 2023 Commitment Scheme

Laurane Chloé Angélina Marco

The Tensor Isomorphism Problem (TIP) has been shown equivalent to the matrix code equivalence problem, making it an interesting candidate on which to build post-quantum cryptographic primitives. These hard problems have already been used in protocol develo ...

Springer Cham2024

Differentially private multi-agent constraint optimization

Boi Faltings, Sujit Prakash Gujar, Aleksei Triastcyn, Sankarshan Damle

Distributed constraint optimization (DCOP) is a framework in which multiple agents with private constraints (or preferences) cooperate to achieve a common goal optimally. DCOPs are applicable in several multi-agent coordination/allocation problems, such as ...

Springer2024

Efficient Signature-Free Validated Agreement

Rachid Guerraoui, Jovan Komatovic, Manuel José Ribeiro Vidigueira, Pierre Philippe Civit

Byzantine agreement enables n processes to agree on a common L-bit value, despite up to t > 0 arbitrary failures. A long line of work has been dedicated to improving the bit complexity of Byzantine agreement in synchrony. This has culminated in COOL, an er ...

Schloss Dagstuhl- Leibniz-Zentrum fur Informatik GmbH, Dagstuhl Publishing2024

Maximum Independent Set: Self-Training through Dynamic Programming

Volkan Cevher, Grigorios Chrysos, Efstratios Panteleimon Skoulakis

This work presents a graph neural network (GNN) framework for solving the maximum independent set (MIS) problem, inspired by dynamic programming (DP). Specifically, given a graph, we propose a DP-like recursive algorithm based on GNNs that firstly construc ...

2023

Online Network Source Optimization with Graph-Kernel MAB

Pascal Frossard

We propose Grab-UCB, a graph-kernelmulti-arms bandit algorithm to learn online the optimal source placement in large scale networks, such that the reward obtained from a priori unknown network processes is maximized. The uncertainty calls for online learni ...

Springer International Publishing Ag2023

Distributed Shadow Dynamic Consensus Optimization Framework for Power Market with Parameterization Bidding Strategy of GENCOs

Liying Yu, Sidi-Rachid Cherkaoui

This paper presents a distributed shadow dynamic consensus (DSDC) framework to address the generation company (GENCO) strategic bidding problem in the independent system operator (ISO) operation. First, each sub-group is defined according to the communicat ...

IEEE2023

Retraction-based numerical methods for continuation, interpolation and time integration on manifolds

Axel Elie Joseph Séguin

The goal of this thesis is the development and the analysis of numerical methods for problems where the unknown is a curve on a smooth manifold. In particular, the thesis is structured around the three following problems: homotopy continuation, curve inter ...

EPFL2023

Quantization for Decentralized Learning Under Subspace Constraints

Ali H. Sayed, Stefan Vlaski, Roula Nassif

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 ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2023

Bridging the gap between theoretical and practical privacy technologies for at-risk populations

Kasra Edalatnejadkhamene

With the pervasive digitalization of modern life, we benefit from efficient access to information and services. Yet, this digitalization poses severe privacy challenges, especially for special-needs individuals. Beyond being a fundamental human right, priv ...

EPFL2023

Solving the Learning Parity with Noise Problem Using Quantum Algorithms

Serge Vaudenay, Bénédikt Minh Dang Tran

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 ...

Springer2022

Detailed Placement for Dedicated LUT-Level FPGA Interconnect

Paolo Ienne, Grace Zgheib, Stefan Nikolic

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 ...

ASSOC COMPUTING MACHINERY2022

Algorithms for Efficient and Robust Distributed Deep Learning

Tao Lin

The success of deep learning may be attributed in large part to remarkable growth in the size and complexity of deep neural networks. However, present learning systems raise significant efficiency concerns and privacy: (1) currently, training systems are l ...

EPFL2022

Practical Compilation of Quantum Programs

Bruno Schmitt Antunes

It's been a little more than 40 years since researchers first suggested exploiting quantum physics to build more powerful computers. During this time, we have seen the development of many quantum algorithms and significant technological advances to make th ...

EPFL2022

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

John Richard Thome, Gustavo Rabello Dos Anjos

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 ...

WILEY2022

Statistical Emulation of Neural Simulators: Application to Neocortical L2/3 Large Basket Cells

Idan Segev, Werner Alfons Hilda Van Geit

Many scientific systems are studied using computer codes that simulate the phenomena of interest. Computer simulation enables scientists to study a broad range of possible conditions, generating large quantities of data at a faster rate than the laboratory ...

FRONTIERS MEDIA SA2022