683 citations
- Space Telescope Science InstituteUS16 papers
- Cornell UniversityUS10 papers
- Boston UniversityUS9 papers
- Université de BordeauxFR9 papers
- Centre National de la Recherche ScientifiqueFR8 papers
- Evgeni Kharadze Georgian National Astrophysical ObservatoryGE8 papers
- Lafayette CollegeUS8 papers
- Laboratoire d'Astrophysique de BordeauxFR7 papers
- Osservatorio Astrofisico di TorinoIT7 papers
- Union CollegeUS7 papers
- University of ConnecticutUS7 papers
- University of Massachusetts AmherstUS7 papers
9 papers · 1 filter
Efficiently Enumerating all Maximal Cliques with Bit-Parallelism
Pablo San Segundo, Jorge Artieda, Darren Strash
The maximal clique enumeration (MCE) problem has numerous applications in biology, chemistry, sociology, and graph modeling. Though this problem is well studied, most current resea…
The Width of Downsets
Dwight Duffus, David Howard, Imre Leader
How large an antichain can we find inside a given downset in the lattice of subsets of [n]? Sperner's theorem asserts that the largest antichain in the whole lattice has size the b…
On the distribution of monochromatic complete subgraphs and arithmetic progressions
Aaron Robertson, William Cipolli, Maria Dascalu
We investigate the distributions of the number of: (1) monochromatic complete subgraphs over edgewise 2-colorings of complete graphs; and (2) monochromatic arithmetic progressions…
Thick Disks in the Hubble Space Telescope Frontier Fields
Bruce G. Elmegreen, Debra Meloy Elmegreen, Brittany Tompkins +1
Thick disk evolution is studied using edge-on galaxies in two Hubble Space Telescope Frontier Field Parallels. The galaxies were separated into 72 clumpy types and 35 spiral types…
Scalable Kernelization for Maximum Independent Sets
Demian Hespe, Christian Schulz, Darren Strash
The most efficient algorithms for finding maximum independent sets in both theory and practice use reduction rules to obtain a much smaller problem instance called a kernel. The ke…
Differentially Private Learning of Undirected Graphical Models using Collective Graphical Models
Garrett Bernstein, Ryan McKenna, Tao Sun +3
We investigate the problem of learning discrete, undirected graphical models in a differentially private way. We show that the approach of releasing noisy sufficient statistics usi…