Fine-grained Search Space Classification for Hard Enumeration Variants of Subset Problems

02/22/2019
by   Juho Lauri, et al.
0

We propose a simple, powerful, and flexible machine learning framework for (i) reducing the search space of computationally difficult enumeration variants of subset problems and (ii) augmenting existing state-of-the-art solvers with informative cues arising from the input distribution. We instantiate our framework for the problem of listing all maximum cliques in a graph, a central problem in network analysis, data mining, and computational biology. We demonstrate the practicality of our approach on real-world networks with millions of vertices and edges by not only retaining all optimal solutions, but also aggressively pruning the input instance size resulting in several fold speedups of state-of-the-art algorithms. Finally, we explore the limits of scalability and robustness of our proposed framework, suggesting that supervised learning is viable for tackling NP-hard problems in practice.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
01/05/2020

Learning fine-grained search space pruning and heuristics for combinatorial optimization

Combinatorial optimization problems arise in a wide range of application...
research
09/12/2019

Learning Multi-Stage Sparsification for Maximum Clique Enumeration

We propose a multi-stage learning approach for pruning the search space ...
research
01/25/2022

What's Wrong with Deep Learning in Tree Search for Combinatorial Optimization

Combinatorial optimization lies at the core of many real-world problems....
research
10/16/2015

Hybridization of Interval CP and Evolutionary Algorithms for Optimizing Difficult Problems

The only rigorous approaches for achieving a numerical proof of optimali...
research
11/06/2020

GHFP: Gradually Hard Filter Pruning

Filter pruning is widely used to reduce the computation of deep learning...
research
05/25/2023

Fine-Grained Complexity Analysis of Multi-Agent Path Finding on 2D Grids

Multi-Agent Path Finding (MAPF) is a fundamental motion coordination pro...
research
04/17/2023

Search-Space Pruning with Int-Splits for Faster QBF Solving

In many QBF encodings, sequences of Boolean variables stand for binary r...

Please sign up or login with your details

Forgot password? Click here to reset