Demo Data from VLDB 2026 / reviewers in the wild / expert
Patrice Marcotte
dblp:24/4052
· DBLP profile ↗
6ranked-venue papers
0as first author
0since 2021 · last 2010
0000-0002-1935-2554ORCID · corroborated
Domains — the database's venue-derived domains; a paper can count in several
Computer networks · 3Theory of computation · 2Artificial intelligence and machine learning · 1
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.
| Artificial intelligence
1 paper |
Deep learning architectures and training · 100% | |
| Theoretical computer science
1 paper |
Mathematical optimization · 100% |
Topics — the 2 heaviest of 2, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Machine learning › Deep learning architectures and training › feedforward neural network
convex neural network |
0.1 | 1 | 2005 | Convex Neural Networks · NIPS 2005 |
Mathematical optimization › continuous optimization
convex optimization |
0.0 | 1 | 2005 | Convex Neural Networks · NIPS 2005 |
Methods — techniques the papers use, named apart from their topics
convex optimization · 0.1
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2010 | A polyhedral study of the network pricing problem with connected toll arcsabstractAbstract We consider the problem of setting revenue‐maximizing tolls on a subset of arcs of a transportation network, assuming that the users of the network are assigned to shortest paths with respect to the sum of tolls and initial costs. Our main results are concerned with a polyhedral study of the problem, i.e., the design of valid inequalities and facets for this pricing problem and some of its variants. © 2009 Wiley Periodicals, Inc. NETWORKS, 2010 Géraldine Heilporn, Martine Labbé, Patrice Marcotte, Gilles Savard |
Networks | 3 |
| 2007 | On a network pricing problem with consecutive toll arcs
Géraldine Heilporn, Martine Labbé, Patrice Marcotte, Gilles Savard |
CTW | 3 |
| 2005 | Convex Neural NetworksabstractConvexity has recently received a lot of attention in the machine learning community, and the lack of convexity has been seen as a major disadvantage of many learning algorithms, such as multi-layer artificial neural networks. We show that training multi-layer neural networks in which the number of hidden units is learned can be viewed as a convex optimization problem. This problem involves an infinite number of variables, but can be solved by incrementally inserting a hidden unit at a time, each time finding a linear classifier that minimizes a weighted sum of errors. Yoshua Bengio, Nicolas Le Roux, Pascal Vincent, Olivier Delalleau, Patrice Marcotte |
NIPS | 5 |
| 2005 | An approximation algorithm for Stackelberg network pricingabstractAbstract We consider the problem of maximizing the revenue raised from tolls set on the arcs of a transportation network, under the constraint that users are assigned to toll‐compatible shortest paths. We first prove that this problem is strongly NP‐hard. We then provide a polynomial time algorithm with a worst‐case precision guarantee of ${{1 \over 2}\log_2 m_T+1}$ , where mT denotes the number of toll arcs. Finally, we show that the approximation is tight with respect to a natural relaxation by constructing a family of instances for which the relaxation gap is reached. © 2005 Wiley Periodicals, Inc. NETWORKS, Vol. 46(1), 57–67 2005 Sébastien Roch, Gilles Savard, Patrice Marcotte |
Networks | 3 |
| 1996 | A hybrid Tabu-ascent algorithm for the linear Bilevel Programming Problem
Michel Gendreau, Patrice Marcotte, Gilles Savard |
J. Glob. Optim. | 2 |
| 1985 | On the relationship between Nash - Cournot and Wardrop equilibriaabstractAbstract A noncooperative game is formulated on a transportation network with congestion. The players are associated with origin‐destination pairs, and are facing demand functions at their respective destination nodes. A Nash‐Cournot equilibrium is defined and conditions for existence and uniqueness of this solution are provided. The asymptotic behavior of the Nash‐Cournot equilibrium is then shown to yield (under appropriate assumptions) a total flow vector corresponding to a Wardrop equilibrium. Alain Haurie, Patrice Marcotte |
Networks | 2 |