Publications related to Hardness of Approximating Flow and Job Shop Scheduling Problems

Results on Sparse Integer Programming and Geometric Independent Sets

An integer linear program is a problem of the form max{c^T x : Ax=b, x >= 0, x integer}, where A is in Z^(n x m), b in Z^m, and c in Z^n.Solving an integer linear program is NP-hard in general, but there are several assumptions for which it becomes fixed p ...

EPFL2023

The One-Way Communication Complexity of Submodular Maximization with Applications to Streaming and Robustness

Ola Nils Anders Svensson, Moran Feldman, Rico Zenklusen, Ashkan Norouzi Fard

We consider the classical problem of maximizing a monotone submodular function subject to a cardinality constraint, which, due to its numerous applications, has recently been studied in various computational models. We consider a clean multi-player model t ...

ASSOC COMPUTING MACHINERY2020

Graph fragmentation problem: analysis and synthesis

Manuel Francesco Aprile

Vulnerability metrics play a key role in the understanding of cascading failures and target/random attacks to a network. The graph fragmentation problem (GFP) is the result of a worst-case analysis of a random attack. We can choose a fixed number of indivi ...

WILEY2019

Strengths and Limitations of Linear Programming Relaxations

Abbas Bazzi

Many of the currently best-known approximation algorithms for NP-hard optimization problems are based on Linear Programming (LP) and Semi-definite Programming (SDP) relaxations. Given its power, this class of algorithms seems to contain the most favourable ...

EPFL2017

Streaming Robust Submodular Maximization: A Partitioned Thresholding Approach

Volkan Cevher, Ilija Bogunovic, Slobodan Mitrovic, Ashkan Norouzi Fard, Jakub Tarnawski

We study the classical problem of maximizing a monotone submodular function subject to a cardinality constraint k, with two additional twists: (i) elements arrive in a streaming fashion and (ii) m items from the algorithm’s memory might be removed after th ...

2017

Proactive Synthesis of Recursive Tree-to-String Functions from Examples

Viktor Kuncak, Mikaël Mayer, Jad Hamza

Synthesis from examples enables non-expert users to generate programs by specifying examples of their behavior. A domain-specific form of such synthesis has been recently deployed in a widely used spreadsheet software product. In this paper we contribute t ...

2017

Group-Sparse Model Selection: Hardness and Relaxations

Volkan Cevher, Anastasios Kyrillidis, Luca Baldassarre, Nirav Bhan

Group-based sparsity models are proven instrumental in linear regression problems for recovering signals from much fewer measurements than standard compressive sensing. The main promise of these models is the recovery of ``interpretable" signals along with ...

Institute of Electrical and Electronics Engineers2016

Approximation algorithms for regret minimization in vehicle routing problems

Adrian Aloysius Bock

In this thesis, we present new approximation algorithms as well as hardness of approximation results for NP-hard vehicle routing problems related to public transportation. We consider two different problem classes that also occur frequently in areas such a ...

EPFL2014

Node-weighted network design and maximum sub-determinants

Carsten Moldenhauer

We consider the Node-weighted Steiner Forest problem on planar graphs. Demaine et al. showed that a generic primal-dual algorithm gives a 6-approximation. We present two different proofs of an approximation factor of~

3

. Then, we draw a connection to Goem ...

EPFL2014

Socially-Aware Large-Scale Crowd Forecasting

Alexandre Massoud Alahi, Vignesh Ramanathan

In crowded spaces such as city centers or train stations, human mobility looks complex, but is often influenced only by a few causes. We propose to quantitatively study crowded environments by introducing a dataset of 42 million trajectories collected in t ...

IEEE2014

Hardness of Approximating Flow and Job Shop Scheduling Problems

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Results on Sparse Integer Programming and Geometric Independent Sets

The One-Way Communication Complexity of Submodular Maximization with Applications to Streaming and Robustness

Graph fragmentation problem: analysis and synthesis

Strengths and Limitations of Linear Programming Relaxations

Streaming Robust Submodular Maximization: A Partitioned Thresholding Approach

Proactive Synthesis of Recursive Tree-to-String Functions from Examples

Group-Sparse Model Selection: Hardness and Relaxations

Approximation algorithms for regret minimization in vehicle routing problems

Node-weighted network design and maximum sub-determinants

Socially-Aware Large-Scale Crowd Forecasting

Graph fragmentation problem: analysis and synthesis

Group-Sparse Model Selection: Hardness and Relaxations

Results on Sparse Integer Programming and Geometric Independent Sets

The One-Way Communication Complexity of Submodular Maximization with Applications to Streaming and Robustness

Streaming Robust Submodular Maximization: A Partitioned Thresholding Approach

Approximation algorithms for regret minimization in vehicle routing problems

Node-weighted network design and maximum sub-determinants

Socially-Aware Large-Scale Crowd Forecasting

Proactive Synthesis of Recursive Tree-to-String Functions from Examples

Strengths and Limitations of Linear Programming Relaxations