mraginsky + computation 15
Edsger W. Dijkstra Prize in Distributed Computing
november 2011 by mraginsky
The Edsger W. Dijkstra Prize in Distributed Computing is named for Edsger Wybe Dijkstra (1930-2002), a pioneer in the area of distributed computing. His foundational work on concurrency primitives (such as the semaphore), concurrency problems (such as mutual exclusion and deadlock), reasoning about concurrent systems, and self-stabilization comprises one of the most important supports upon which the field of distributed computing is built. No other individual has had a larger influence on research in principles of distributed computing.
computation
distributed-computing
distributed-systems
reference
november 2011 by mraginsky
Observer Mechanics: A Formal Theory of Perception (Bennett, Hoffman, Prakash)
january 2011 by mraginsky
"Observer Mechanics is an inquiry into the subject of perception. It suggests an approach to the study of perception that attempts to be both rigorous and general. A central thesis of Observer Mechanics is that every perceptual capacity (e.g., stereovision, auditory localization, sentence parsing, haptic recognition, and so on) can be described as an instance of a single formal structure: viz., an "observer.""
books
to-read
complexity
computation
perception
dynamical-systems
probability
multiagent-systems
cognitive-science
cybernetics
january 2011 by mraginsky
Subexponential Lower Bound for Randomized Pivot Rules! | Combinatorics and more
november 2010 by mraginsky
"Oliver Friedman, Thomas Dueholm Hansen, and Uri Zwick have managed to prove subexponential lower bounds of the form for ... two basic randomized pivot rules for the simplex algorithm! This is the first result of its kind and deciding if this is possible was an open problem for several decades." And they do it using MDPs!
papers
to-read
computer-science
computation
optimization
linear-programming
dynamic-programming
Markov-decision-processes
lower-bounds
november 2010 by mraginsky
Algorithmic Thermodynamics « Azimuth
october 2010 by mraginsky
John Baez blogs about his paper with Mike Stay on algorithmic thermodynamics
have-read
blogs
information-theory
complexity
computation
thermodynamics
october 2010 by mraginsky
[1007.5354] Synchronization and Control in Intrinsic and Designed Computation: An Information-Theoretic Analysis of Competing Models of Stochastic Computation
august 2010 by mraginsky
"We adapt tools from information theory to analyze how an observer comes to synchronize with the hidden states of a finitary, stationary stochastic process. We show that synchronization is determined by both the process's internal organization and by an observer's model of it. We analyze these components using the convergence of state-block and block-state entropies, comparing them to the previously known convergence properties of the Shannon block entropy. Along the way, we introduce a hierarchy of information quantifiers as derivatives and integrals of these entropies, which parallels a similar hierarchy introduced for block entropy. We also draw out the duality between synchronization properties and a process's controllability. The tools lead to a new classification of a process's alternative representations in terms of minimality, synchronizability, and unifilarity."
papers
to-read
information-theory
control-theory
complexity
computation
august 2010 by mraginsky
[0901.2735] State Space Realization Theorems For Data Mining
may 2010 by mraginsky
"In this paper, we consider formal series associated with events, profiles derived from events, and statistical models that make predictions about events. We prove theorems about realizations for these formal series using the language and tools of Hopf algebras."
papers
to-read
state-space-models
machine-learning
computation
may 2010 by mraginsky
Computational Aspects of Evolution
january 2010 by mraginsky
A course taught by Christos Papadimitriou
evolution
complexity
computation
computer-science
optimization
lecture-notes
algorithms
january 2010 by mraginsky
Moser’s entropy compression argument
august 2009 by mraginsky
Terry Tao explains the recent paper by Robin Moser.
probability
information-theory
complexity
computer-science
mathematics
computation
august 2009 by mraginsky
Machine Learning (Theory) » Computability in Artificial Intelligence
may 2009 by mraginsky
"Let me show by analogy why limiting research to computational questions is bad for any field. Except in computer science, computational aspects play little role in the development of fundamental theories: Consider e.g. set theory with axiom of choice, foundations of logic, exact/full minimax for zero-sum games, quantum (field) theory, string theory, … Indeed, at least in physics, every new fundamental theory seems to be less computable than previous ones."
blogs
have-read
science
complexity
computer-science
computation
philosophy
epistemology
AI
learning-theory
may 2009 by mraginsky
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