The 20th International Workshop on Approximation Algorithms for Combinatorial Optimization Problems (APPROX'2017), and the 21st International Workshop on Randomization and Computation (RANDOM'2017) will be held on the 16-18 of August 2017 at University of California, Berkeley .
APPROX'2017 focuses on algorithmic and complexity theoretic issues relevant to the development of efficient approximate solutions to computationally difficult problems, while RANDOM'2017 focuses on applications of randomness to computational and combinatorial problems. RANDOM'2017 is the twentyfirst workshop in the series; APPROX'2017 is the twentieth in the series.
Papers are solicited in all research areas related to randomization and approximation, including, but not limited to:
APPROX
Approx 2017 + Random 2017
UC Berkeley
Wed, August 16 - Fri, August 18, 2017
The 20th International Workshop on Approximation Algorithms for Combinatorial Optimization Problems (APPROX'2017), and the 21st International Workshop on Randomization and Computation (RANDOM'2017) will be held on the 16-18 of August 2017 at University of California, Berkeley .
APPROX'2017 focuses on algorithmic and complexity theoretic issues relevant to the development of efficient approximate solutions to computationally difficult problems, while RANDOM'2017 focuses on applications of randomness to computational and combinatorial problems. RANDOM'2017 is the twentyfirst workshop in the series; APPROX'2017 is the twentieth in the series.
Topics
Papers are solicited in all research areas related to randomization and approximation, including, but not limited to:
APPROX
- approximation algorithms
- hardness of approximation
- small space, sub-linear time and streaming algorithms
- online algorithms
- approaches that go beyond worst case analysis
- distributed and parallel approximation
- embeddings and metric space methods
- mathematical programming methods
- spectral methods
- combinatorial optimization in graphs and networks
- algorithmic game theory, mechanism design and economics
- computational geometric problems
- approximate learning
- design and analysis of randomized algorithms
- randomized complexity theory
- pseudorandomness and derandomization
- random combinatorial structures
- random walks/Markov chains
- expander graphs and randomness extractors
- probabilistic proof systems
- random projections and embeddings
- error-correcting codes
- average-case analysis
- property testing
- computational learning theory