| MonMonday | TueTuesday | WedWednesday | ThuThursday | FriFriday | SatSaturday | SunSunday |
|---|---|---|---|---|---|---|
Mar 2, '20March 2, 2020
|
Mar 3, '20March 3, 2020
|
Mar 4, '20March 4, 2020
|
Mar 5, '20March 5, 2020●(1 event)
|
Mar 6, '20March 6, 2020
|
Mar 7, '20March 7, 2020
|
Mar 8, '20March 8, 2020
|
| MMonday | TTuesday | WWednesday | TThursday | FFriday | SSaturday | SSunday |
|---|---|---|---|---|---|---|
24February 24, 2020
|
25February 25, 2020
|
26February 26, 2020
|
Strategic information transmission with receiver's type-dependent decision sets, by Stephan Sémirat (GAEL, Grenoble) – Strategic information transmission with receiver's type-dependent decision sets. Abstract: We consider a sender-receiver game, in which the sender has finitely many types and the receiver makes decisions in a bounded real interval. We assume that utility functions are concave, single-peaked and supermodular. After the cheap talk phase, the receiver makes a decision, which must fulfill a constraint (e.g., a participation constraint) that depends on the sender's type. Hence a necessary equilibrium condition is that the receiver maximizes his expected utility subject to the constraints of all positive probability types. This necessary condition may not hold at the receiver's prior belief, so that a non-revealing equilibrium may fail to exist. We propose a constructive algorithm that always achieves a partitional perfect Bayesian equilibrium Bâtiment IMAG (442) |
28February 28, 2020
|
29February 29, 2020
|
March1March 1, 2020 |
2March 2, 2020
|
3March 3, 2020
|
4March 4, 2020
|
keynote LIG – |
6March 6, 2020
|
7March 7, 2020
|
8March 8, 2020
|
9March 9, 2020
|
10March 10, 2020
|
11March 11, 2020
|
Seminar Anastasios Giovanidis – Title : Ranking Online Social Users by their Influence Abstract: In this talk I will introduce an original mathematical model to analyse the diffusion of posts within a generic online social platform. As a main result, using the developed model, we derive in closed form the probabilities that posts originating from a given user are found on the Wall and Newsfeed of any other inside the platform. By combining these probabilities we get a measure of per user influence on the entire network. This constitutes a new centrality measure which is more expressive than existing ones, in the sense that it combines the user position on the graph with the user posting activity. Comparisons with simulations show the accuracy of this model and its robustness with respect to the modelling assumptions. Furthermore, its application on large data traces from real platforms asserts its validity for real world applications, and the possibilities it opens for explaining real diffusion phenomena and predicting actual user influence.
Bio: |
F. Falniowski: "Robust routes to chaos in congestion games: The effects of scale on learning dynamics" – We study the effects of increasing the population size/scale of costs in congestion games and generalize recent results for the well known Multiplicative Weights Update dynamic to a large class of Follow-the-Regularized Leader dynamics (FoReL). We prove that even in simple linear congestion games with two parallel links as the population/scale increases, learning becomes unstable and (unless the game is fully symmetric) eventually Li-Yorke chaotic. Despite their chaotic instability, the dynamics provably converge in a time-average sense to an exact equilibrium for any choice of learning rate and any scale of costs. |
14March 14, 2020
|
15March 15, 2020
|
16March 16, 2020
|
17March 17, 2020
|
18March 18, 2020
|
Seminar CERAI Alexandre Termier – |
20March 20, 2020
|
21March 21, 2020
|
22March 22, 2020
|
23March 23, 2020
|
24March 24, 2020
|
25March 25, 2020
|
PhD defense of Stephan Plassart (Postponed due to COVID lockdown) |
27March 27, 2020
|
28March 28, 2020
|
29March 29, 2020
|
30March 30, 2020
|
31March 31, 2020
|
April1April 1, 2020 |
3April 3, 2020
|
4April 4, 2020
|
5April 5, 2020
|
|
6April 6, 2020
|
7April 7, 2020
|
8April 8, 2020
|
9April 9, 2020
|
10April 10, 2020
|
11April 11, 2020
|
12April 12, 2020
|
13April 13, 2020
|
14April 14, 2020
|
15April 15, 2020
|
16April 16, 2020
|
17April 17, 2020
|
18April 18, 2020
|
19April 19, 2020
|
20April 20, 2020
|
21April 21, 2020
|
22April 22, 2020
|
23April 23, 2020
|
24April 24, 2020
|
25April 25, 2020
|
26April 26, 2020
|
27April 27, 2020
|
28April 28, 2020
|
29April 29, 2020
|
30April 30, 2020
|
May1May 1, 2020 |
2May 2, 2020
|
3May 3, 2020
|
This website uses cookies so that we can provide you with the best user experience possible. Cookie information is stored in your browser and performs functions such as recognising you when you return to our website and helping our team to understand which sections of the website you find most interesting and useful.
Strictly Necessary Cookie should be enabled at all times so that we can save your preferences for cookie settings.
If you disable this cookie, we will not be able to save your preferences. This means that every time you visit this website you will need to enable or disable cookies again.
