together with brief user bio and description of her/his academic activity.

### Upcoming readings:
No upcoming readings for now...
### Past Readings:
- 21/05/2018 [Graph Embedding Techniques, Applications, and Performance: A Survey](https://papers-gamma.link/paper/52)
- 14/05/2018 [A Fast and Provable Method for Estimating Clique Counts Using Turán’s Theorem](https://papers-gamma.link/paper/24)
- 07/05/2018 [VERSE: Versatile Graph Embeddings from Similarity Measures](https://papers-gamma.link/paper/48)
- 30/04/2018 [Hierarchical Clustering Beyond the Worst-Case](https://papers-gamma.link/paper/45)
- 16/04/2018 [Scalable Motif-aware Graph Clustering](https://papers-gamma.link/paper/18)
- 02/04/2018 [Practical Algorithms for Linear Boolean-width](https://papers-gamma.link/paper/40)
- 26/03/2018 [New Perspectives and Methods in Link Prediction](https://papers-gamma.link/paper/28/New%20Perspectives%20and%20Methods%20in%20Link%20Prediction)
- 19/03/2018 [In-Core Computation of Geometric Centralities with HyperBall: A Hundred Billion Nodes and Beyond](https://papers-gamma.link/paper/37)
- 12/03/2018 [Diversity is All You Need: Learning Skills without a Reward Function](https://papers-gamma.link/paper/36)
- 05/03/2018 [When Hashes Met Wedges: A Distributed Algorithm for Finding High Similarity Vectors](https://papers-gamma.link/paper/23)
- 26/02/2018 [Fast Approximation of Centrality](https://papers-gamma.link/paper/35/Fast%20Approximation%20of%20Centrality)
- 19/02/2018 [Indexing Public-Private Graphs](https://papers-gamma.link/paper/19/Indexing%20Public-Private%20Graphs)
- 12/02/2018 [On the uniform generation of random graphs with prescribed degree sequences](https://papers-gamma.link/paper/26/On%20the%20uniform%20generation%20of%20random%20graphs%20with%20prescribed%20d%20egree%20sequences)
- 05/02/2018 [Linear Additive Markov Processes](https://papers-gamma.link/paper/21/Linear%20Additive%20Markov%20Processes)
- 29/01/2018 [ESCAPE: Efficiently Counting All 5-Vertex Subgraphs](https://papers-gamma.link/paper/17/ESCAPE:%20Efficiently%20Counting%20All%205-Vertex%20Subgraphs)
- 22/01/2018 [The k-peak Decomposition: Mapping the Global Structure of Graphs](https://papers-gamma.link/paper/16/The%20k-peak%20Decomposition:%20Mapping%20the%20Global%20Structure%20of%20Graphs)

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1

### Dynamic setting:
One of the motivations for the suggested framework is related to the dynamic nature of the reachability graph. However, the suggested framework does not seem to be particularly effective in a dynamic setting (need to recompute the sets "S" from scratch if the reachability graph is modified).
Recent work is dedicated to solving the k-center problem in a dynamic setting: "Fully Dynamic k-Center Clustering, Chan et al., WWW2018". The "asymmetric k-center problem" being a subproblem solved in the suggested framework, a more efficient algorithm in a dynamic setting seems possible.
### Effectiveness of greedy:
Nice to see that the greedy heuristic leads to a very good approximation on real-world instances for the considered problem (the exact result is known solving an integer program). On the contrary, an algorithm (Ullman and Yannakakis) having good theoretical guarantees performs poorly on the same real-world instances.
### Typos:
- "In Table 6.4, the column labeled...": should be "In Table 2, ..."

## Comments: