Found 7 relevant results in 2.38s where lecturer="Mohsen Ghaffari"
This is a graduate-level course on algorithm design (and analysis). It covers a range of topics and techniques in approximation algorithms, sketching and streaming algorithms, and online algorithms.
How can a network of computers solve the graph problems needed for running that network?
This is a theory seminar, where we present and discuss recent algorithmic developments forprocessing large-scale graphs. In particular, we focus on Massively Parallel Computation (MPC)algorithms. MPC is a clean and general theoretical framework that captures the essential aspectsof computational problems in large-scale processing settings such as MapReduce, Hadoop,Spark, Dryad, etc.
Advanced design and analysis methods for algorithms and data structures: Random(ized) Search Trees, Point Location, Minimum Cut, Linear Programming, Randomized Algebraic Algorithms (matchings), Probabilistically Checkable Proofs (introduction).
Students present current or classical results from theoretical computer science.
We study the fundamental issues underlying the design of distributed systems: communication, coordination, fault-tolerance, locality, parallelism, self-organization, symmetry breaking, synchronization, uncertainty. We explore essential algorithmic ideas and lower bound techniques.
Presentation of recent publications in theoretical computer science, including results by diploma, masters and doctoral candidates.