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DAGSTUHL
2007
15 years 8 months ago
Sampling-based Approximation Algorithms for Multi-stage Stochastic Optimization
Stochastic optimization problems provide a means to model uncertainty in the input data where the uncertainty is modeled by a probability distribution over the possible realizatio...
Chaitanya Swamy, David B. Shmoys
RTSS
1999
IEEE
15 years 10 months ago
Parallel Switching in Connection-Oriented Networks
Packet switching in connection-oriented networks that may have multiple parallel links between pairs of switches is considered. An e cient packet-scheduling algorithm that guarant...
James H. Anderson, Sanjoy K. Baruah, Kevin Jeffay
MOC
2011
15 years 1 months ago
Convergence of a mixed method for a semi-stationary compressible Stokes system
We propose and analyze a finite element method for a semi– stationary Stokes system modeling compressible fluid flow subject to a Navier– slip boundary condition. The veloci...
Kenneth H. Karlsen, Trygve K. Karper
ICML
2004
IEEE
16 years 7 months ago
SVM-based generalized multiple-instance learning via approximate box counting
The multiple-instance learning (MIL) model has been very successful in application areas such as drug discovery and content-based imageretrieval. Recently, a generalization of thi...
Qingping Tao, Stephen D. Scott, N. V. Vinodchandra...
INFOCOM
2009
IEEE
16 years 1 months ago
Approximation Algorithms for Data Broadcast in Wireless Networks
—Broadcasting is a fundamental operation in wireless networks and plays an important role in the communication protocol design. In multihop wireless networks, however, interferen...
Rajiv Gandhi, Yoo-Ah Kim, Seungjoon Lee, Jiho Ryu,...