ER04: Computational Geometry and Topology for Data Analysis (11-15 January)

Dates: 11-15 January 2016

Location: Sophia-Antipolis

Teachers: Jean-Daniel Boissonnat, Frédéric Chazal et Alfredo Hubard (Sophia-Antipolis)

For more information about this school: https://team.inria.fr/geometrica/winter-school-2016/

ER05: Advanced Techniques Software Specification and Computer Proof (18-22 January)

Date: 18-22 January 2016

Teachers: Cyril Cohen, Laurence Rideau, and Laurent Théry Local contact: Enrico Tassi

https://team.inria.fr/marelle/en/advanced-coq-winter-school-2016/

ER01: Randomized Algorithms (7-11 December)

Dates : 7-11 December

Teachers: Joel Ouaknine, Ben Worrell et Stefan Kiefel (Oxford). Local contact: Pascal Koiran

Title: Probabilistic Techniques and Models in Computer Science

The schedule: Monday: 9:30 – 11:30 am and 1:30 – 3:30 pm Tuesday: 9 – 11:30 am, 1:30-3:30 pm and 4-6 pm. Wednesday: 9-11:30 am and 1:30-3:30 pm. Thursday: 9 am – 12:30 pm Friday: 9 am – 12:30 pm and afternoon exam: 2 pm – 4 pm

Synopsis (more information here):

— Decision Problems

* Space-bounded interactive protocols

* Reachability and threshold problems for Markov chains

* Connections with number theory

— Stochastic [Lire la suite…]

ER02: Data Mining : Statistical Modeling and Learning from Data (11-15 January)

Dates: 11-15 January 2016

Teachers: Ciro Cattuto, Laetitia Gauvin et André Panisson (ISI Torino)

Local contact: Márton Karsai (marton.karsai@ens-lyon.fr)

Venue: ENS Lyon, site Monod, Amphi B (entrance from the 4th floor)

Time: 9:30 – 16:45

External participants who has no access to the building should contact Marton Karsai (marton.karsai@ens-lyon.fr) in advance.

The main page of the course can be found here.

The course aims to provide basic skills for analysis and statistical modeling of data, with special attention to machine learning both supervised and unsupervised. An important objective of the course is the operational knowledge of [Lire la suite…]

ER03: Combinatorics/Sage (18-22 January)

Dates: 18 – 22 January 2016

Organizer : Nicolas Thiéry and Thierry Monteil.

ER01: Data Structures for Big Data

Dates: January 12-16, 2015.

Teachers: Michael Bender (Stony Brook University), Martín Farach-Colton (Rutgers and Tokutek), Samuel McCauley (Stony Brook University)

Description of the school

Course Hours

Monday-Thursday:

  • morning lecture: 9:30am-11:30am

  • afternoon lecture: 1:30pm-3:30pm.

  • recitation/homework practice: 4pm-5pm.

Friday:

  • morning lecture: 9:30am-11:30am

  • afternoon exam:  2pm-5pm

Local contact :  Frédéric Vivien.

Registration

Registration is free, but the number of participants is limited. Registration includes neither housing nor meals (though for lunch the attendees will be granted access to the student [Lire la suite…]

ER02: Algorithms and Heuristics for Large-scale Data Sets

Dates: January 19-23, 2015.

Dedicated webpage

Teachers: Nicolas Schabanel (Université Paris-Diderot), Alain Barrat et Bruno Gonçalves (Université Aix-Marseille)

Local contact : Marton Karsai

Registration

Registration is free, but the number of participants is limited. Registration includes neither housing nor meals (though for lunch the attendees will be granted access to the student cafeteria). Registration should be made before … (to be decided later) by Lire la suite…]

ER03: Static Analysis and Compilation

Dates: January 26-30, 2015.

Dedicated webpage

Teacher: Fernando Magno Pereira (Univ Mineas Gerais, Brazil)

Local contact :  Laure Gonnord

Registration

Registration is free, but the number of participants is limited. Registration includes neither housing nor meals (though for lunch the attendees will be granted access to the student cafeteria). Registration should be made before … (to be decided later) by Lire la suite…]

ER04: Verification and Computer Proof (SOPHIA-ANTIPOLIS)

Date: January 19-23 2015

Teacher: Yves Berthot (INRIA Sophia-Antipolis)

School Webpage

Registration

Please contact Yves Bertot (Yves.Bertot@sophia.inria.fr) to know the registration instructions.

ER05: Algorithmic Geometry of Triangulations (SOPHIA-ANTIPOLIS)

Date: January 26-30 2015

Dedicated webpage (to be updated)

Teachers: Jean-Daniel Boissonat, Clément Maria, Mariette Yvinec (INRIA Sophia-Antipolis)

Registration

Please contact Jean-Daniel Boissonat (Jean-Daniel.Boissonnat@inria.fr) to know the registration instructions.

ER01: Algorithmic Game Theory

Dates: December 9-13, 2013.

School outline and timetable .

Local contact :Natacha Portier.

Registration

Registration is free, but the number of participants is limited. Registration includes neither housing nor meals (though for lunch the attendees will be granted access to the student cafeteria). Registration should be made before November 29, 2013 by clicking on this link, [Lire la suite…]

ER02: Synchronous Approaches for Embedded Systems

Dates: January 13-17, 2014.

Web site.

Local contact : Laure Gonnord.

Registration

Registration is free, but the number of participants is limited. Registration includes neither housing nor meals (though for lunch the attendees will be granted access to the student cafeteria). Registration should be made before January 3, 2014 by clicking on this link, filling [Lire la suite…]

ER03: Logic of Dynamical Systems

Speakers: André Platzer and Sarah Loos.

Dates: January 20-24, 2014.

Web page.

Local contact: Filippo Bonchi

Registration

Registration is free, but the number of participants is limited. Registration includes neither housing nor meals (though for lunch the attendees will be granted access to the student cafeteria). Registration should be made before January 10, 2014 by Lire la suite…]

ER03: Constraint satisfaction problems

January 21-25, 2013, ENS Lyon. Speakers: Manuel Bodirsky, Michael Pinsker.

A Constraint Satisfaction Problem (CSP) is a computational problem where the task is to decide for a given finite set of variables and constraints whether there is an assignment to the variables that satisfies all constraints. Many computational problems in various areas of theoretical computer science can be modeled in this way.

If the variables take their values in some finite domain, there is a rich universal-algebraic theory that describes those constraint languages whose CSP is NP-hard, and those whose CSP is in P. In this course, we [Lire la suite…]

ER02: Semantics and tools for low-level concurrent programming

January 14-18, 2013, ENS Lyon. Speakers

Francesco Zappa Nardelli (INRIA), Mark Batty (University of Cambridge), Alastair Donaldson(Imperial College London), and Martin Vechev (ETH Zurich)

Slides

Available from here

Abstract

Optimisations performed by the hardware or by high-level language compilers can reorder memory accesses in various subtle ways. These reorderings can sometimes be observed by concurrent programs, exacerbating the usual problems of concurrent programming. The situation is even worse when we abandon traditional shared memory concurrency in favor of graphics processing units (GPUs) or exotic hardware. In these lectures we will cover recent progress in understanding [Lire la suite…]

ER01: Fault tolerance for high performance computing

George Bosilca et Thomas Hérault,

University of Tennessee Knoxville

December 10-14, 2012, ENS Lyon.

During this course, we will discuss fault tolerance techniques for high performance computing systems.

Motivation.

In June 2008, the LANL’s Road Runner computing system was the first to  cross the hallmark of one Petaflop based on the Linpack benchmark (reaching $1.026 \cdot 10^{15}$ double precision floating point operation per second). Today, only 4 years later, the fastest computing system, the Sequoia BlueGene/Q at LLNL, sustains 16.324 Petaflops. Continuing on the same path, it is expected that as early as 2022, computing systems will [Lire la suite…]

ER01 : verifying and certifying software

 

ER02 : Compressive Sensing

Lecturer : Justin Romberg (Georgia Institute of Technology, Atlanta)

Outline of the school : “The dogma of signal processing maintains that a signal must be sampled at a rate at least twice its highest frequency in order to be represented without error. However, in practice, we often compress the data soon after sensing, trading off signal representation complexity (bits) for some error (consider JPEG image compression in digital cameras, for example). Clearly, this is wasteful of valuable sensing resources. Over the past few years, a new theory of “compressive sensing” has begun to emerge, in which the signal is sampled [Lire la suite…]

ER03 : Calculabilité sur les entiers et les réels : de l’œuvre de Turing à la recherche actuelle

 

ER04 : linear programming and combinatorics