The Parameterized Approximation Algorithms Workshop (PAAW) will take place
as a satellite workshop of ICALP 2018 in Prague, Czechia, on Monday July
9th 2018.
https://sites.google.com/site/aefeldmann/workshop
--- Registration ---
To participate at the workshop please register through the ICALP
registration page (early registration deadline is May 31):
https://iuuk.mff.cuni.cz/~icalp2018/registration
--- Contributed talks ---
Parinya Chalermsook: From Gap-ETH to FPT-Inapproximability: Clique,
Dominating Set, and More
Michael Dinitz: Characterizing Demand Graphs for (Fixed-Parameter)
Shallow-Light Steiner Network
Eduard Eiben: Lossy Kernels for Connected Dominating Set on Sparse Graphs
Ariel Kulik: Parameterized Approximation via Fidelity Preserving
Transformations
Bundit Laekhanukit: On the Inapproximability of Parameterized Dominating Set
Michael Lampis: Parameterized (Approximate) Defective Coloring
Euiwoong Lee: Losing Treewidth by Separating Subsets
Jason Li: An FPT Algorithm Beating 2-Approximation for k-Cut
Bingkai Lin: FPT-Inapproximability of Minimum Codeword Problem over Large
Fields
Tomáš Masařík: Parameterized Approximation Schemes for Steiner Trees with
Small Number of Steiner Vertices
Krzysztof Sornat: Approximation and Parameterized Complexity of Minimax
Approval Voting
Daniel Vaz: Beyond Metric Embedding: Approximating Group Steiner Trees on
Bounded Treewidth Graphs
--- Scope ---
Two standard approaches to handle hard (typically NP-hard) optimization
problems are to develop approximation and parameterized algorithms. For the
former, the runtime should be polynomial in the input size, but the
computed solution may deviate from the optimum. For the latter, the optimum
solution should be computed, but any super-polynomial runtime should be
isolated to some parameter of the input. Some problems however are hard to
approximate on one hand, and on the other it is also hard to obtain
parameterized algorithms for some given parameter. In this case one may
still hope to obtain parameterized approximation algorithms, which combine
the two paradigms, i.e. the computed solution may deviate from the optimum
and the runtime should have super-polynomial dependence only in some given
parameter. Recently there has been a great deal of development in proving
the existence or non-existence of parameterized approximation algorithms,
and the aim of this workshop is to bring together active researchers of
this emerging field, so that they may share their results and insights.
--- Topics of interest ---
- Parameterized approximation algorithms
- Lossy kernelization
- Parameterized inapproximability
- Fine-grained complexity of approximation
- Efficient polynomial-time approximation schemes
--- Important dates ---
Submission deadline: Friday April 20th, 2018
Notification: Friday May 18th, 2018
Early registration deadline: Thursday May 31, 2018
Workshop: Monday July 9th, 2018
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