AFLB

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'''Current top choices (at least two votes)'''
'''Current top choices (at least two votes)'''
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* (Avishek, Chris) algorithmic game theory (from [http://www.cambridge.org/journals/nisan/downloads/Nisan_Non-printable.pdf this book])
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* (Avishek, Chris, Piyush) algorithmic game theory (from [http://www.cambridge.org/journals/nisan/downloads/Nisan_Non-printable.pdf this book])
* (Suresh, Jeff, Chris, Parasaran, Josh) Lattice theory (from [http://www.amazon.com/Lattice-Theory-Colloquium-Publications-Mathematical/dp/0821810251 Birkhoff]) and its applications in complexity, clustering, social choice theory, and more.  
* (Suresh, Jeff, Chris, Parasaran, Josh) Lattice theory (from [http://www.amazon.com/Lattice-Theory-Colloquium-Publications-Mathematical/dp/0821810251 Birkhoff]) and its applications in complexity, clustering, social choice theory, and more.  
** [http://www.math.hawaii.edu/~jb/books.html Here is an online collection] of lecture notes.  
** [http://www.math.hawaii.edu/~jb/books.html Here is an online collection] of lecture notes.  
** [http://users.ece.utexas.edu/~garg/f03-lat.html Lattice theory course] with a focus on CS applications
** [http://users.ece.utexas.edu/~garg/f03-lat.html Lattice theory course] with a focus on CS applications
* (Piyush, Avishek, Jeff, Josh) [http://www.amazon.com/Concentration-Measure-Analysis-Randomized-Algorithms/dp/0521884276 concentration inequalities for random variables]
* (Piyush, Avishek, Jeff, Josh) [http://www.amazon.com/Concentration-Measure-Analysis-Randomized-Algorithms/dp/0521884276 concentration inequalities for random variables]
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* (Jeff, Chris, Josh) uncertainty in spatial data (We would follow a series of (mainly) recent papers spanning areas from Computational Geometry, databases, machine learning, to statistics.  We would start with models and then move on to specific applications where they are used.  We will encounter many interesting open questions.  If I get more votes or upon request, I will sketch a paper list in more detail)
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* (Jeff, Chris, Josh, Piyush) uncertainty in spatial data (We would follow a series of (mainly) recent papers spanning areas from Computational Geometry, databases, machine learning, to statistics.  We would start with models and then move on to specific applications where they are used.  We will encounter many interesting open questions.  If I get more votes or upon request, I will sketch a paper list in more detail)

Revision as of 14:12, 20 May 2010

The Algorithms For Lunch Bunch

Thursdays at 12:30 (during the semester)

Contents

Summer 2010

Tentative time: Tue/Thu @ 1pm (starting May 20) Venue: TBA (probably the graphics annex)

Potential topics: (add your name to vote (as many topics as you like))

Current top choices (at least two votes)

  • (Avishek, Chris, Piyush) algorithmic game theory (from this book)
  • (Suresh, Jeff, Chris, Parasaran, Josh) Lattice theory (from Birkhoff) and its applications in complexity, clustering, social choice theory, and more.
  • (Piyush, Avishek, Jeff, Josh) concentration inequalities for random variables
  • (Jeff, Chris, Josh, Piyush) uncertainty in spatial data (We would follow a series of (mainly) recent papers spanning areas from Computational Geometry, databases, machine learning, to statistics. We would start with models and then move on to specific applications where they are used. We will encounter many interesting open questions. If I get more votes or upon request, I will sketch a paper list in more detail)


General topics

  • (Chris) quantum computing (possibly from these notes)

Complexity Theory

Analysis Tools

Geometry

Miscellaneous

Papers for discussion

Recently Seen on Arxiv

STOC 2010

Add papers here that you found interesting (and link to full version if available)

  • Efficiently Learning Mixtures of Two Gaussians. Adam Tauman Kalai (Microsoft), Ankur Moitra (MIT), and Gregory Valiant (UC Berkeley)
  • Measuring Independence of Datasets. Vladimir Braverman and Rafail Ostrovsky (UCLA)
  • On the Geometry of Differential Privacy. Moritz Hardt (Princeton University) and Kunal Talwar (Microsoft Research)
  • Weighted Geometric Set Cover via Quasi-Uniform Sampling. Kasturi Varadarajan (University of Iowa)
  • A Sparse Johnson-Lindenstrauss Transform. Anirban Dasgupta and Ravi Kumar and Tamas Sarlos (Yahoo! Research)

Other Papers

Previous Semesters

Contact

If you are interested in giving a talk at AFLB or have questions, please feel free to send a mail to moeller@cs.utah.edu, praman@cs.utah.edu or avishek@cs.utah.edu. If you are planning to give a talk, we would really appreciate if you have an abstract ready a week before the talk is scheduled.

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