A faster method for computing Gama-Nguyen-Regev's extreme pruning coefficients

Lattice Enumeration Using Extreme Pruning

Lattice enumeration algorithms are the most basic algorithms for solving hard lattice problems such as the shortest vector problem and the closest vector problem, and are often used in public-key cryptanalysis either as standalone algorithms, or as subroutines in lattice reduction algorithms. Here we revisit these fundamental algorithms and show that surprising exponential speedups can be achie...

A Comparative Study of Extreme Learning Machines and Support Vector Machines in Prediction of Sediment Transport in Open Channels

The limiting velocity in open channels to prevent long-term sedimentation is predicted in this paper using a powerful soft computing technique known as Extreme Learning Machines (ELM). The ELM is a single Layer Feed-forward Neural Network (SLFNN) with a high level of training speed. The dimensionless parameter of limiting velocity which is known as the densimetric Froude number (Fr) is predicte...

Solving BDD by Enumeration: An Update

Bounded Distance Decoding (BDD) is a basic lattice problem used in cryptanalysis: the security of most lattice-based encryption schemes relies on the hardness of some BDD, such as LWE. We study how to solve BDD using a classical method for finding shortest vectors in lattices: enumeration with pruning speedup, such as Gama-NguyenRegev extreme pruning from EUROCRYPT ’10. We obtain significant im...

An Elementary Method for Computing the Kostka Coefficients

Random Sampling Revisited: Lattice Enumeration with Discrete Pruning

In 2003, Schnorr introduced Random sampling to find very short lattice vectors, as an alternative to enumeration. An improved variant has been used in the past few years by Kashiwabara et al. to solve the largest Darmstadt SVP challenges. However, the behaviour of random sampling and its variants is not well-understood: all analyses so far rely on a questionable heuristic assumption, namely tha...