Demo Data from EDBT 2026 / reviewers in the wild / expert
Raz Kupferman
dblp:33/3008
· DBLP profile ↗
7ranked-venue papers
0as first author
0since 2021 · last 2012
—ORCID · unresolved
Domains — the database's venue-derived domains; a paper can count in several
Artificial intelligence and machine learning · 6Theory of computation · 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
2 papers |
Probabilistic and Bayesian machine learning · 100% |
Topics — the 6 heaviest of 6, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Machine learning › Probabilistic and Bayesian machine learning › probabilistic inference › approximate inference
belief propagation |
0.1 | 1 | 2010 | Continuous-Time Belief Propagation · ICML 2010 |
Machine learning › Probabilistic and Bayesian machine learning › structured models › graphical models › bayesian network
continuous time bayesian networks |
0.1 | 1 | 2010 | Mean Field Variational Approximation for Continuous-Time Bayesian Networks · J. Mach. Learn. Res. 2010 |
Machine learning › Probabilistic and Bayesian machine learning › probabilistic inference
continuous-time inference |
0.1 | 1 | 2010 | Continuous-Time Belief Propagation · ICML 2010 |
Machine learning › Probabilistic and Bayesian machine learning › structured models
graphical models |
0.1 | 1 | 2010 | Mean Field Variational Approximation for Continuous-Time Bayesian Networks · J. Mach. Learn. Res. 2010 |
Machine learning › Probabilistic and Bayesian machine learning › probabilistic inference › approximate inference › variational inference
mean-field approximation |
0.1 | 1 | 2010 | Mean Field Variational Approximation for Continuous-Time Bayesian Networks · J. Mach. Learn. Res. 2010 |
Machine learning › Probabilistic and Bayesian machine learning › probabilistic inference › approximate inference
variational inference |
0.1 | 1 | 2010 | Mean Field Variational Approximation for Continuous-Time Bayesian Networks · J. Mach. Learn. Res. 2010 |
Methods — techniques the papers use, named apart from their topics
mean-field variational approximation · 0.1
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2012 | No justified complaints: on fair sharing of multiple resourcesabstractFair allocation has been studied intensively in both economics and computer science. This subject has aroused renewed interest with the advent of virtualization and cloud computing. Prior work has typically focused on mechanisms for fair sharing of a single resource. We consider a variant where each user is entitled to a certain fraction of the system's resources, and has a fixed usage profile describing how much he would want from each resource. We provide a new definition for the simultaneous fair allocation of multiple continuously-divisible resources that we call bottleneck-based fairness (BBF). Roughly speaking, an allocation of resources is considered fair if every user either gets all the resources he wishes for, or else gets at least his entitlement on some bottleneck resource, and therefore cannot complain about not receiving more. We show that BBF has several desirable properties such as providing an incentive for sharing, and also promotes high overall utilization of resources; we also compare BBF carefully to another notion of fairness proposed recently, dominant resource fairness. Danny Dolev, Dror G. Feitelson, Joseph Y. Halpern, Raz Kupferman, Nathan Linial |
ITCS | 4 |
| 2010 | Continuous-Time Belief Propagation
Tal El-Hay, Ido Cohn, Nir Friedman, Raz Kupferman |
ICML | 4 |
| 2010 | Mean Field Variational Approximation for Continuous-Time Bayesian Networks
Ido Cohn, Tal El-Hay, Nir Friedman, Raz Kupferman |
J. Mach. Learn. Res. | 4 |
| 2009 | Mean Field Variational Approximation for Continuous-Time Bayesian Networks
Ido Cohn, Tal El-Hay, Nir Friedman, Raz Kupferman |
UAI | 4 |
| 2008 | Gibbs Sampling in Factorized Continuous-Time Markov Processes
Tal El-Hay, Nir Friedman, Raz Kupferman |
UAI | 3 |
| 2006 | Continuous Time Markov Networks
Tal El-Hay, Nir Friedman, Daphne Koller, Raz Kupferman |
UAI | 4 |
| 2006 | Dimension Reduction in Singularly Perturbed Continuous-Time Bayesian Networks
Nir Friedman, Raz Kupferman |
UAI | 2 |