12 citations · 48 across the 11 of their papers we have counts for
13 papers
The NFA Acceptance Hypothesis: Non-Combinatorial and Dynamic Lower Bounds
Karl Bringmann, Allan Grønlund, Marvin Künnemann +1
We pose the fine-grained hardness hypothesis that the textbook algorithm for the NFA Acceptance problem is optimal up to subpolynomial factors, even for dense NFAs and fixed alphab…
Learning to Detect Fortified Areas
Allan Grønlund, Jonas Tranberg
High resolution data models like grid terrain models made from LiDAR data are a prerequisite for modern day Geographic Information Systems applications. Besides providing the found…
Margins are Insufficient for Explaining Gradient Boosting
Allan Grønlund, Lior Kamma, Kasper Green Larsen
Boosting is one of the most successful ideas in machine learning, achieving great practical performance with little fine-tuning. The success of boosted classifiers is most often at…
Near-Tight Margin-Based Generalization Bounds for Support Vector Machines
Allan Grønlund, Lior Kamma, Kasper Green Larsen
Support Vector Machines (SVMs) are among the most fundamental tools for binary classification. In its simplest formulation, an SVM produces a hyperplane separating two classes of d…
Learning to Find Hydrological Corrections
Lars Arge, Allan Grønlund, Svend Christian Svendsen +1
High resolution Digital Elevation models, such as the (Big) grid terrain model of Denmark with more than 200 billion measurements, is a basic requirement for water flow modelling a…
Margin-Based Generalization Lower Bounds for Boosted Classifiers
Allan Grønlund, Lior Kamma, Kasper Green Larsen +2
Boosting is one of the most successful ideas in machine learning. The most well-accepted explanations for the low generalization error of boosting algorithms such as AdaBoost stem…
Algorithms Clearly Beat Gamers at Quantum Moves. A Verification
Allan Grønlund
The paper [Sørensen et al., Nature 532] considers how human players compare to algorithms for solving the Quantum Moves game BringHomeWater and design new algorithms based on the i…
Optimal Minimal Margin Maximization with Boosting
Allan Grønlund, Kasper Green Larsen, Alexander Mathiasen
Boosting algorithms produce a classifier by iteratively combining base hypotheses. It has been observed experimentally that the generalization error keeps improving even after achi…
Upper and lower bounds for dynamic data structures on strings
Raphael Clifford, Allan Grønlund, Kasper Green Larsen +1
We consider a range of simply stated dynamic data structure problems on strings. An update changes one symbol in the input and a query asks us to compute some function of the patte…
New Unconditional Hardness Results for Dynamic and Online Problems
Raphael Clifford, Allan Grønlund, Kasper Green Larsen
There has been a resurgence of interest in lower bounds whose truth rests on the conjectured hardness of well known computational problems. These conditional lower bounds have beco…
Towards Tight Lower Bounds for Range Reporting on the RAM
Allan Grønlund, Kasper Green Larsen
In the orthogonal range reporting problem, we are to preprocess a set of points with integer coordinates on a grid. The goal is to support reporting all points…
Approximate Range Emptiness in Constant Time and Optimal Space
Mayank Goswami, Allan Grønlund, Kasper Green Larsen +1
This paper studies the \emph{-approximate range emptiness} problem, where the task is to represent a set of points from and answer emptiness…
Geometric Computations on Indecisive and Uncertain Points
Allan Jorgensen, Maarten Löffler, Jeff M. Phillips
We study computing geometric problems on uncertain points. An uncertain point is a point that does not have a fixed location, but rather is described by a probability distribution.…