**acm**3097

Why Logical Clocks are Easy - ACM Queue

14 days ago by mechazoidal

"The mechanisms for tracking causality and the rules used in these mechanisms are often seen as complex,6,15 and their presentation is not always intuitive. The most commonly used mechanisms for tracking causality—vector clocks and version vectors—are simply optimized representations of causal histories, which are easy to understand.

By building on the notion of causal histories, you can begin to see the logic behind these mechanisms, to identify how they differ, and even consider possible optimizations. When confronted with an unfamiliar causality-tracking mechanism, or when trying to design a new system that requires it, readers should ask two simple questions: (a) Which events need tracking? (b) How does the mechanism translate back to a simple causal history?

Without a simple mental image for guidance, errors and misconceptions become more common. Sometimes, all you need is the right language."

From 2016, noting "vector versions" and "dotted vector versions". This might also be a good way to understand the ordt/cvrdt data structure.

distributed
clock
acm
piperesearch
logic
By building on the notion of causal histories, you can begin to see the logic behind these mechanisms, to identify how they differ, and even consider possible optimizations. When confronted with an unfamiliar causality-tracking mechanism, or when trying to design a new system that requires it, readers should ask two simple questions: (a) Which events need tracking? (b) How does the mechanism translate back to a simple causal history?

Without a simple mental image for guidance, errors and misconceptions become more common. Sometimes, all you need is the right language."

From 2016, noting "vector versions" and "dotted vector versions". This might also be a good way to understand the ordt/cvrdt data structure.

14 days ago by mechazoidal

Solution concept - Wikipedia

28 days ago by nhaliday

In game theory, a solution concept is a formal rule for predicting how a game will be played. These predictions are called "solutions", and describe which strategies will be adopted by players and, therefore, the result of the game. The most commonly used solution concepts are equilibrium concepts, most famously Nash equilibrium.

Many solution concepts, for many games, will result in more than one solution. This puts any one of the solutions in doubt, so a game theorist may apply a refinement to narrow down the solutions. Each successive solution concept presented in the following improves on its predecessor by eliminating implausible equilibria in richer games.

nice diagram

concept
conceptual-vocab
list
wiki
reference
acm
game-theory
inference
equilibrium
extrema
reduction
sub-super
Many solution concepts, for many games, will result in more than one solution. This puts any one of the solutions in doubt, so a game theorist may apply a refinement to narrow down the solutions. Each successive solution concept presented in the following improves on its predecessor by eliminating implausible equilibria in richer games.

nice diagram

28 days ago by nhaliday

ON THE GEOMETRY OF NASH EQUILIBRIA AND CORRELATED EQUILIBRIA

7 weeks ago by nhaliday

Abstract: It is well known that the set of correlated equilibrium distributions of an n-player noncooperative game is a convex polytope that includes all the Nash equilibrium distributions. We demonstrate an elementary yet surprising result: the Nash equilibria all lie on the boundary of the polytope.

pdf
nibble
papers
ORFE
game-theory
optimization
geometry
dimensionality
linear-algebra
equilibrium
structure
differential
correlation
iidness
acm
linear-programming
spatial
characterization
levers
7 weeks ago by nhaliday

Workshop Abstract | Identifying and Understanding Deep Learning Phenomena

8 weeks ago by nhaliday

ICML 2019 workshop, June 15th 2019, Long Beach, CA

We solicit contributions that view the behavior of deep nets as natural phenomena, to be investigated with methods inspired from the natural sciences like physics, astronomy, and biology.

unit
workshop
acm
machine-learning
science
empirical
nitty-gritty
atoms
deep-learning
model-class
icml
data-science
rigor
replication
examples
ben-recht
physics
We solicit contributions that view the behavior of deep nets as natural phenomena, to be investigated with methods inspired from the natural sciences like physics, astronomy, and biology.

8 weeks ago by nhaliday

RISKS-LIST: RISKS-FORUM Digest

12 weeks ago by bigpicbruh

via uni of toronto course page. This website lists the risks in software field

security
risks
software
ACM
news
12 weeks ago by bigpicbruh