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magistraleinformatica:ad:ad_17:start [27/12/2017 alle 14:57 (7 anni fa)] – [Topics] Roberto Grossimagistraleinformatica:ad:ad_17:start [03/09/2018 alle 22:02 (7 anni fa)] (versione attuale) – [Schedule] Roberto Grossi
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 ==== Schedule ==== ==== Schedule ====
  
 +  * Regarding your exam planning: I'll be on leave during 19.09.18-15.10.18 and 01.11.2018-28.02.19.
   * Timetable: [[https://www.di.unipi.it/en/education/mcs/timetable-wif/myschedule-wif?courses%5B%5D=58926_u&cds=WIF-LM&dip=Informatica&test=10&sem=1&anno=2017#|weekly timetable]] with changes: (Oct.5 -> Oct.4, 14-16, I-Lab); (Oct.9 -> Oct.2, 14-16, room A1); (Oct.10 -> Oct.23, 14-16, room A1).   * Timetable: [[https://www.di.unipi.it/en/education/mcs/timetable-wif/myschedule-wif?courses%5B%5D=58926_u&cds=WIF-LM&dip=Informatica&test=10&sem=1&anno=2017#|weekly timetable]] with changes: (Oct.5 -> Oct.4, 14-16, I-Lab); (Oct.9 -> Oct.2, 14-16, room A1); (Oct.10 -> Oct.23, 14-16, room A1).
   * Office hours: Thu. 14-17 or by appointment.   * Office hours: Thu. 14-17 or by appointment.
- 
 ==== Overview ==== ==== Overview ====
  
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 ==== Exams ==== ==== Exams ====
  
-Written exam:+//Written exam://
   - choose one of the topics discussed in class   - choose one of the topics discussed in class
   - write a very short to-do list and ask the instructor for approval   - write a very short to-do list and ask the instructor for approval
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 Suggested reading: [[http://www.ittc.ku.edu/~jsv/Papers/Vitwritingnotes.pdf|some useful tips for scientific writing in English]] (first two sections) by J.S. Vitter. Suggested reading: [[http://www.ittc.ku.edu/~jsv/Papers/Vitwritingnotes.pdf|some useful tips for scientific writing in English]] (first two sections) by J.S. Vitter.
 +
 +Example of interaction: [[.interaction:|student and instructor]] discussing the report's content and structure.
  
  
-Oral examination: topics discussed in class, please read the references in the notes.+//Oral exam:// topics discussed in class, please read the references in the notes.
 ==== Topics ==== ==== Topics ====
  
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 |26.09.2017| Virus scan and stream analysis with Karp-Rabin fingerprints: randomized checking and pattern matching. Montecarlo and Las Vegas algorithms. | [RM {{:magistraleinformatica:alg2:algo2_15:karp-rabin-1.pdf| par.7.4-7.6}}]  [[https://repl.it/LbWC/3|code]]| |26.09.2017| Virus scan and stream analysis with Karp-Rabin fingerprints: randomized checking and pattern matching. Montecarlo and Las Vegas algorithms. | [RM {{:magistraleinformatica:alg2:algo2_15:karp-rabin-1.pdf| par.7.4-7.6}}]  [[https://repl.it/LbWC/3|code]]|
 |28.09.2017| Dictionary of keywords. Quick review of classical hashing. Universal hashing. Markov's inequality. Perfect hashing.| [CLRS 11.2, 11.3.3, CLRS 11.5 ] [[https://repl.it/Ljuh/8|code]]| |28.09.2017| Dictionary of keywords. Quick review of classical hashing. Universal hashing. Markov's inequality. Perfect hashing.| [CLRS 11.2, 11.3.3, CLRS 11.5 ] [[https://repl.it/Ljuh/8|code]]|
-|02.10.2017| Case study: rsync and file synchronization using hash functions | {{ :magistraleinformatica:ad:ad_17:rsync.pdf |slides}} [[https://en.wikipedia.org/wiki/Rsync|wikipedia]] |+|02.10.2017| Case study on hashing: rsync and file synchronization using hash functions | {{ :magistraleinformatica:ad:ad_17:rsync.pdf |slides}} [[https://en.wikipedia.org/wiki/Rsync|wikipedia]] |
 |02.10.2017| Data Streaming algorithms. Motivations and examples. Count-Min Sketches | {{https://7797b024-a-62cb3a1a-s-sites.googlegroups.com/site/countminsketch/cm-latin.pdf| sects.1-3}} [[https://sites.google.com/site/countminsketch/|Site]] {{:magistraleinformatica:alg2:algo2_12:count-min-sketch.pdf|Notes}} [[https://repl.it/Lvob/3|code]]| |02.10.2017| Data Streaming algorithms. Motivations and examples. Count-Min Sketches | {{https://7797b024-a-62cb3a1a-s-sites.googlegroups.com/site/countminsketch/cm-latin.pdf| sects.1-3}} [[https://sites.google.com/site/countminsketch/|Site]] {{:magistraleinformatica:alg2:algo2_12:count-min-sketch.pdf|Notes}} [[https://repl.it/Lvob/3|code]]|
 |03.10.2017| Queries with Count-Min Sketches: implementation and analysis. | {{https://7797b024-a-62cb3a1a-s-sites.googlegroups.com/site/countminsketch/cm-latin.pdf| sects.3-4}} {{:magistraleinformatica:ad:ad_17:20171003.pdf|Notes}} {{:magistraleinformatica:alg2:algo2_12:count-min-sketch-median.pdf|Notes (optional)}} | |03.10.2017| Queries with Count-Min Sketches: implementation and analysis. | {{https://7797b024-a-62cb3a1a-s-sites.googlegroups.com/site/countminsketch/cm-latin.pdf| sects.3-4}} {{:magistraleinformatica:ad:ad_17:20171003.pdf|Notes}} {{:magistraleinformatica:alg2:algo2_12:count-min-sketch-median.pdf|Notes (optional)}} |
 |04.10.2017| Document resemblance with MinHash, k-sketches and the Jaccard similarity index. Azuma-Hoeffding bound. | [[http://gatekeeper.dec.com/ftp/pub/dec/SRC/publications/broder/positano-final-wpnums.pdf|paper]] [[http://cs.brown.edu/courses/cs253/papers/nearduplicate.pdf|paper]] [[http://homes.cs.washington.edu/~jrl/cs525/scribes08/lec10.pdf|Azuma-Hoeffding]] [[https://repl.it/MDNO/3|code]]| |04.10.2017| Document resemblance with MinHash, k-sketches and the Jaccard similarity index. Azuma-Hoeffding bound. | [[http://gatekeeper.dec.com/ftp/pub/dec/SRC/publications/broder/positano-final-wpnums.pdf|paper]] [[http://cs.brown.edu/courses/cs253/papers/nearduplicate.pdf|paper]] [[http://homes.cs.washington.edu/~jrl/cs525/scribes08/lec10.pdf|Azuma-Hoeffding]] [[https://repl.it/MDNO/3|code]]|
-|19.10.2017| Case study: document tagging and perfect hashing.| {{ :magistraleinformatica:ad:ad_17:tagger.tgz | code }} |+|19.10.2017| Case study on hashing: document tagging and perfect hashing.| {{ :magistraleinformatica:ad:ad_17:tagger.tgz | code }} |
 |23.10.2017| Networked data and randomized min-cut algorithm for graphs. | {{:magistraleinformatica:alg2:algo2_15:mincut1.pdf| par.1.1}} | |23.10.2017| Networked data and randomized min-cut algorithm for graphs. | {{:magistraleinformatica:alg2:algo2_15:mincut1.pdf| par.1.1}} |
 |23.10.2017| Proxy caches and dictionaries with errors: Bloom filters. | {{:magistraleinformatica:alg2:bloomfiltersurvey.pdf|Survey: except par.2.5-2.6 (optional: par.2.2)}} | |23.10.2017| Proxy caches and dictionaries with errors: Bloom filters. | {{:magistraleinformatica:alg2:bloomfiltersurvey.pdf|Survey: except par.2.5-2.6 (optional: par.2.2)}} |
 |24.10.2017| Randomness in data. Kolmogorov complexity. Generating random sequences and permutations (exercise: subsets). | [[http://www.eecs.berkeley.edu/~luca/cs172/notek.pdf|Notes]] [[http://www.1stworks.com/ref/ruskeycombgen.pdf|Sect. 5.4]] | |24.10.2017| Randomness in data. Kolmogorov complexity. Generating random sequences and permutations (exercise: subsets). | [[http://www.eecs.berkeley.edu/~luca/cs172/notek.pdf|Notes]] [[http://www.1stworks.com/ref/ruskeycombgen.pdf|Sect. 5.4]] |
 |26.10.2017| Generating random trees. Models for generating random graphs: Erdős-Rényi-Gilbert G(n,p), Barabási–Albert preferential attachment, Watts–Strogatz small world, configuration model. | [[http://www.1stworks.com/ref/ruskeycombgen.pdf|Sect. 5.5]] [[http://www.win.tue.nl/~rhofstad/NotesRGCN.pdf| Sect. 1.1-1.3 (optional 1.5-1.6), 4,1 (till pag.126), 7.1-7.2, 8.1]] | |26.10.2017| Generating random trees. Models for generating random graphs: Erdős-Rényi-Gilbert G(n,p), Barabási–Albert preferential attachment, Watts–Strogatz small world, configuration model. | [[http://www.1stworks.com/ref/ruskeycombgen.pdf|Sect. 5.5]] [[http://www.win.tue.nl/~rhofstad/NotesRGCN.pdf| Sect. 1.1-1.3 (optional 1.5-1.6), 4,1 (till pag.126), 7.1-7.2, 8.1]] |
-|06.11.2017| Case studydata stream analytics (part 1). | {{ :magistraleinformatica:ad:ad_17:data-stream-stats.pdf |notes}} |+|06.11.2017| Case study on data stream: statistics and analytics (part 1). | {{ :magistraleinformatica:ad:ad_17:data-stream-stats.pdf |notes}} |
 |07.11.2017| Distributed server and load balancing through hashing: revisited | [[https://www.cs.cmu.edu/afs/cs/project/pscico-guyb/realworld/www/slidesF15/hashing.pdf|Sect.7 and 8.1]] | |07.11.2017| Distributed server and load balancing through hashing: revisited | [[https://www.cs.cmu.edu/afs/cs/project/pscico-guyb/realworld/www/slidesF15/hashing.pdf|Sect.7 and 8.1]] |
 |09.11.2017| The power of two random choices: Cuckoo hashing.| {{:magistraleinformatica:alg2:algo2_10:cuckoo-undergrad.pdf|Notes}} {{:magistraleinformatica:alg2:algo2_16:cuckoohashinsertion.pdf|Notes}}  [[https://repl.it/NzGN/3|code]]| |09.11.2017| The power of two random choices: Cuckoo hashing.| {{:magistraleinformatica:alg2:algo2_10:cuckoo-undergrad.pdf|Notes}} {{:magistraleinformatica:alg2:algo2_16:cuckoohashinsertion.pdf|Notes}}  [[https://repl.it/NzGN/3|code]]|
-|13.11.2017| Case studydata stream analytics (part 2). | {{ :magistraleinformatica:ad:ad_17:data-stream-stats2.pdf |notes}}  [[https://repl.it/@geraci/Min-Hash-estimate|code]]|+|13.11.2017| Case study on data stream: statistics and analytics (part 2). | {{ :magistraleinformatica:ad:ad_17:data-stream-stats2.pdf |notes}}  [[https://repl.it/@geraci/Min-Hash-estimate|code]]|
  
 === Enumeration, hardness and approximation of some combinatorial problems === === Enumeration, hardness and approximation of some combinatorial problems ===
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 |14.11.2017| 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]]  | |14.11.2017| 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]]  |
 |16.11.2017| NP-hard problems: branch and bound algorithms; fully polynomial-time approximation schemes (FPTASs). Case study: knapsack problem. | {{ :magistraleinformatica:ad:ad_17:vazirani_knapsack.pdf |ch.8}} {{ :magistraleinformatica:ad:ad_17:NotesKnapsack1.pdf | notes}} [[https://repl.it/@grossiroberto/approxKnapsack|code]] | |16.11.2017| NP-hard problems: branch and bound algorithms; fully polynomial-time approximation schemes (FPTASs). Case study: knapsack problem. | {{ :magistraleinformatica:ad:ad_17:vazirani_knapsack.pdf |ch.8}} {{ :magistraleinformatica:ad:ad_17:NotesKnapsack1.pdf | notes}} [[https://repl.it/@grossiroberto/approxKnapsack|code]] |
-|20.11.2017| TBD TBA|+|20.11.2017| Case study on bottom-k sketches: approximate similarity searching of large collections of images [[http://image.diku.dk/igel/paper/NNCUBkS.pdf|paper]]|
 |21.11.2017| NP-hard problems: counting version (#P) based on dynamic programming, uniform random sampling of the feasible solutions; fully polynomial-time randomized approximation schemes (FPRASs). Case study: #knapsack problem. | {{ :magistraleinformatica:ad:ad_17:notesknapsack2.pdf |notes}} [[https://repl.it/@grossiroberto/ApproxKnapsack|code]] | |21.11.2017| NP-hard problems: counting version (#P) based on dynamic programming, uniform random sampling of the feasible solutions; fully polynomial-time randomized approximation schemes (FPRASs). Case study: #knapsack problem. | {{ :magistraleinformatica:ad:ad_17:notesknapsack2.pdf |notes}} [[https://repl.it/@grossiroberto/ApproxKnapsack|code]] |
 |23.11.2017| General inapproximability results. Case study: travel salesman problem (TSP).  2-approximation algorithm . | [CLRS 35.2] | |23.11.2017| General inapproximability results. Case study: travel salesman problem (TSP).  2-approximation algorithm . | [CLRS 35.2] |
-|27.11.2017| Case study on approximation for metric k-center: Clustering and video summarization. | TBD +|27.11.2017| Case study on approximation for metric k-center: Clustering and video summarization. | [[https://www.dropbox.com/s/mvomtclqs97vx26/27-11.pdf?dl=0|slides]] [[https://www.dropbox.com/s/aeowxkt6p8iximx/chapter2.pdf?dl=0|notes]] 
-|28.11.2017| Non-existence of PTAS. Local search. Greedy. Case study: max-cut for graphs. | TBD +|28.11.2017| Non-existence of PTAS. Local search. Greedy. Case study: max cut for graphs. | {{:magistraleinformatica:alg2:algo2_14:lec02.pdf|Notes}} 
-|30.11.2017| Randomized approximation. Derandomization: universal hash functions; conditional expectations. Case study: max-cut for graphs. | TBD |+|30.11.2017| Randomized approximation. Derandomization: universal hash functions; conditional expectations. Case study: max-cut for graphs. | [[http://pages.cs.wisc.edu/~jyc/02-810notes/lecture19.pdf|sect. 3-4]] [[http://web.cs.iastate.edu/~pavan/633/lec14.pdf|sect. 1.1]] |
 |04.12.2017| Case study on approximation for graphs (max cut): single individual haplotypes reconstruction problem (hapcut) |[[https://tinyurl.com/yak7p2w7|paper]] | |04.12.2017| Case study on approximation for graphs (max cut): single individual haplotypes reconstruction problem (hapcut) |[[https://tinyurl.com/yak7p2w7|paper]] |
-|05.12.2017| Parameterized algorithms. Kernelization. Bounded search tree. Case study: min-vertex cover in graphs. TBD +|05.12.2017| Fixed-parameter tractable (FPT) algorithms. Kernelization. Bounded search tree. Case study: min-vertex cover in graphs. [[https://www.mimuw.edu.pl/~malcin/book/parameterized-algorithms.pdf|sect. 2.2.1, 3.1]] 
-|07.12.2017| Fixed-parameter tractable (FPT) algorithms. Randomized FPT algorithms: color coding and randomized separation. Case study: longest path in graphs and subgraph isomorphism. | TBD +|07.12.2017| Randomized FPT algorithms: color coding and randomized separation. Case study: longest path in graphs and subgraph isomorphism. | [[https://www.mimuw.edu.pl/~malcin/book/parameterized-algorithms.pdf|sect. 5.2, 5.3]] | 
-|12.12.2017| Fine-grained algorithms. SETH conjecture and conditional lower bounds. Guaranteed heuristics. Case study: diameter in undirected unweighted graphs. | TBD +|11.12.2017| Class canceled for weather alert. | - |  
-|14.12.2017| Approximation in fine-grained algorithms and limitations. Case study: diameter in undirected unweighted graphs. Communities detection in large graphs.| {{ :magistraleinformatica:ad:ad_17:diameterapprox.pdf | notes }} [[https://www.nature.com/articles/nature03607.pdf|paper]] [[https://images.nature.com/original/nature-assets/nature/journal/v435/n7043/extref/nature03607-s1.pdf|supplement]] |+|12.12.2017| Fine-grained algorithms. SETH conjecture and conditional lower bounds. Guaranteed heuristics. Case study: diameter in undirected unweighted graphs. | [[https://www.dropbox.com/s/zq0dklabkjyd302/20171212.pdf?dl=0|notes]] [[https://people.csail.mit.edu/virgi/ipec-survey.pdf|sect. 2.3, 2.4, 3, 4]]
 +|14.12.2017| Approximation in fine-grained algorithms and limitations. Case study: diameter in undirected unweighted graphs. Case study: communities detection in large graphs.| {{ :magistraleinformatica:ad:ad_17:diameterapprox.pdf | notes }} [[https://www.nature.com/articles/nature03607.pdf|paper]] [[https://images.nature.com/original/nature-assets/nature/journal/v435/n7043/extref/nature03607-s1.pdf|supplement]] |
  
 == Activity in class == == Activity in class ==
magistraleinformatica/ad/ad_17/start.1514386677.txt.gz · Ultima modifica: 27/12/2017 alle 14:57 (7 anni fa) da Roberto Grossi

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