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--- magistraleinformatica:ad:ad_19:start [12/05/2020 alle 06:47 (6 anni fa)] – Roberto Grossi
+++ magistraleinformatica:ad:ad_19:start [07/07/2020 alle 07:59 (6 anni fa)] (versione attuale) – Roberto Grossi
@@ Linea 11: / Linea 11: @@
 You student, what can you do next for getting a lecture?
-  - Join the class on **Google Classroom** (use Android/iOS or connect to the [[https://classroom.google.com/u/1/c/NjI0NjI4NjExNzRa|Algorithm Design link]]), and use the code below: {{:magistraleinformatica:ad:ad_19:code.jpg?400|}}\\ \\
+  - Join the class on Google Classroom (use Android/iOS or connect to the [[https://classroom.google.com/u/1/c/NjI0NjI4NjExNzRa|Algorithm Design link]]).
   - Click on the link for streaming on [[https://meet.google.com/rco-fojo-cqn|Google Meet]] for attending the classes. Please note that we //keep our schedule for time//, the only difference is that you have connect to the link instead of physically coming to the room.
@@ Linea 83: / Linea 83: @@
 |24.04.2020| NP-hard problems: download file manager and the knapsack problem. Reduction from Partition to Knapsack (restriction). Dynamic programming algorithms for Knapsack: Case 1: integer weights, complexity O(nW). Case 2: integer values, complexity O(n<sup>2</sup>vmax). Examples. | {{ :magistraleinformatica:ad:ad_17:partition-knapsack.pdf | PDF}}  [[https://repl.it/@grossiroberto/knapsack|code]] |
 |28.04.2019| NP-hard problems: heuristics based on dynamic programming; approximation algorithms. Case study: knapsack problem. | [[http://www.dis.uniroma1.it/~ausiello/InfoTeoIIRM/book/chapter02.pdf| chapt.2: par. 2.1.1]] [[https://repl.it/@grossiroberto/knapsack|code]]  |
+|30.04.2019| Clique-based social network analysis (seminar by F.Geraci) | classroom drive |
 |05.05.2020| NP-hard problems: counting version (#P) based on dynamic programming, uniform random sampling of the feasible solutions. Case study: #knapsack problem. | {{ :magistraleinformatica:ad:ad_17:notesknapsack2.pdf |notes}} [[https://repl.it/@grossiroberto/ApproxKnapsack|code]] |
 |07.05.2020| NP-hard problems: fully polynomial-time randomized approximation schemes (FPRASs). Case study: #knapsack problem. | {{ :magistraleinformatica:ad:ad_17:notesknapsack2.pdf |notes}} [[https://repl.it/@grossiroberto/ApproxKnapsack|code]] |