27 citations · 57 across the 10 of their papers we have counts for
7 papers · 1 filter
The Power of Hashing with Mersenne Primes
Thomas Dybdahl Ahle, Jakob Tejs Bæk Knudsen, Mikkel Thorup
The classic way of computing a -universal hash function is to use a random degree- polynomial over a prime field . For a fast computation of the polynomial,…
Similarity Search with Tensor Core Units
Thomas D. Ahle, Francesco Silvestri
Tensor Core Units (TCUs) are hardware accelerators developed for deep neural networks, which efficiently support the multiplication of two dense matrices,…
On the Problem of in Locality-Sensitive Hashing
Thomas Dybdahl Ahle
A Locality-Sensitive Hash (LSH) function is called -sensitive, if two data-points with a distance less than collide with probability at least while data p…
Subsets and Supermajorities: Optimal Hashing-based Set Similarity Search
Thomas Dybdahl Ahle, Jakob Bæk Tejs Knudsen
We formulate and optimally solve a new generalized Set Similarity Search problem, which assumes the size of the database and query sets are known in advance. By creating polylog co…
Optimal Las Vegas Locality Sensitive Data Structures
Thomas Dybdahl Ahle
We show that approximate similarity (near neighbour) search can be solved in high dimensions with performance matching state of the art (data independent) Locality Sensitive Hashin…
Parameter-free Locality Sensitive Hashing for Spherical Range Reporting
Thomas D. Ahle, Martin Aumüller, Rasmus Pagh
We present a data structure for *spherical range reporting* on a point set , i.e., reporting all points in that lie within radius of a given query point . Our solutio…
On the Complexity of Inner Product Similarity Join
Thomas D. Ahle, Rasmus Pagh, Ilya Razenshteyn +1
A number of tasks in classification, information retrieval, recommendation systems, and record linkage reduce to the core problem of inner product similarity join (IPS join): ident…