Demo Data from SIGIR 2026 / reviewers in the wild / expert
Raymond Hemmecke
dblp:48/6653 · also Ray Hemmecke
· DBLP profile ↗
12ranked-venue papers
3as first author
0since 2021 · last 2015
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Theory of computation · 9 · 2 first-authorArtificial intelligence and machine learning · 3 · 1 first-author
Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.
| Theoretical computer science
2 papers |
Mathematical optimization · 46% Automated reasoning and model checking · 40% Approximation and online algorithms · 14% | |
| Artificial intelligence
1 paper |
Probabilistic and Bayesian machine learning · 100% |
Topics — the 5 heaviest of 6, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Mathematical optimization › integer programming
mixed-integer optimization |
0.1 | 1 | 2006 | FPTAS for mixed-integer polynomial optimization with a fixed number of variables · SODA 2006 |
Mathematical optimization › global optimization
polynomial optimization |
0.1 | 1 | 2006 | FPTAS for mixed-integer polynomial optimization with a fixed number of variables · SODA 2006 |
Machine learning › Probabilistic and Bayesian machine learning › structured models
graphical models |
0.0 | 1 | 2010 | Efficient Algorithms for Conditional Independence Inference · J. Mach. Learn. Res. 2010 |
Approximation and online algorithms
approximation schemes |
0.0 | 1 | 2006 | FPTAS for mixed-integer polynomial optimization with a fixed number of variables · SODA 2006 |
Approximation and online algorithms › approximation schemes
FPTAS |
0.0 | 1 | 2006 | FPTAS for mixed-integer polynomial optimization with a fixed number of variables · SODA 2006 |
Methods — techniques the papers use, named apart from their topics
graphical models · 0.1graphical model · 0.1
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2015 | On the Circuit Diameter of Dual Transportation PolyhedraabstractIn this paper we introduce the circuit diameter of polyhedra, which is always bounded from above by the combinatorial diameter. We consider dual transportation polyhedra defined on general bipartite graphs. For complete $M{\times}N$ bipartite graphs the Hirsch bound (M-1)(N-1) on the combinatorial diameter is a known tight bound [Math. Oper. Res., 9 (1984), pp. 629--633]. For the circuit diameter we show the much stronger bound M+N-2 for all dual transportation polyhedra defined on arbitrary bipartite graphs with $M{+}N$ nodes. Steffen Borgwardt, Elisabeth Finhold, Raymond Hemmecke |
SIAM J. Discret. Math. | 3 |
| 2013 | Inequalities for the Number of Walks in Graphs
Hanjo Täubig, Jeremias Weihmann, Sven Kosub, Raymond Hemmecke, Ernst W. Mayr |
Algorithmica | 4 |
| 2012 | Characteristic imsets for learning Bayesian network structure
Raymond Hemmecke, Silvia Lindner, Milan Studený |
Int. J. Approx. Reason. | 1 |
| 2010 | A Polynomial-Time Algorithm for Optimizing over N-Fold 4-Block Decomposable Integer Programs
Raymond Hemmecke, Matthias Köppe, Robert Weismantel |
IPCO | 1 |
| 2010 | A geometric view on learning Bayesian network structures
Milan Studený, Jirí Vomlel, Raymond Hemmecke |
Int. J. Approx. Reason. | 3 |
| 2010 | Efficient Algorithms for Conditional Independence Inference
Remco R. Bouckaert, Raymond Hemmecke, Silvia Lindner, Milan Studený |
J. Mach. Learn. Res. | 2 |
| 2009 | Pareto Optima of Multicriteria Integer Linear ProgramsabstractWe settle the computational complexity of fundamental questions related to multicriteria integer linear programs, when the dimensions of the strategy space and of the outcome space are considered fixed constants. In particular we construct: (1) polynomial-time algorithms to determine exactly the number of Pareto optima and Pareto strategies; (2) a polynomial-space polynomial-delay prescribed-order enumeration algorithm for arbitrary projections of the Pareto set; (3) a polynomial-time algorithm to minimize the distance of a Pareto optimum from a prescribed comparison point with respect to arbitrary polyhedral norms; and (4) a fully polynomial-time approximation scheme for the problem of minimizing the distance of a Pareto optimum from a prescribed comparison point with respect to the Euclidean norm. Jesús A. De Loera, Raymond Hemmecke, Matthias Köppe |
INFORMS J. Comput. | 2 |
| 2009 | Computing generating sets of lattice ideals and Markov bases of lattices
Raymond Hemmecke, Peter N. Malkin |
J. Symb. Comput. | 1 |
| 2006 | FPTAS for mixed-integer polynomial optimization with a fixed number of variables
Jesús A. De Loera, Raymond Hemmecke, Matthias Köppe, Robert Weismantel |
SODA | 2 |
| 2004 | Three Kinds of Integer Programming Algorithms Based on Barvinok's Rational Functions
Jesús A. De Loera, David Haws, Raymond Hemmecke, Peter Huggins, Ruriko Yoshida |
IPCO | 3 |
| 2004 | Short rational functions for toric algebra and applications
Jesús A. De Loera, David Haws, Raymond Hemmecke, Peter Huggins, Bernd Sturmfels, Ruriko Yoshida |
J. Symb. Comput. | 3 |
| 2004 | Effective lattice point counting in rational convex polytopes
Jesús A. De Loera, Raymond Hemmecke, Jeremiah Tauzer, Ruriko Yoshida |
J. Symb. Comput. | 2 |