“Most people don’t follow these issues for a living and have a hard time distinguishing legitimate arguments from garbage. I don’t mean this patronizingly: I certainly would have trouble distinguishing valid arguments from nonsense in a technical field I didn’t study professionally. But that’s why there’s a value in signaling that some arguments aren’t merely expressing a difference in values or interpretation, but are made by an unqualified hack peddling demonstrable nonsense. Being so mean is a labor of love, I confess, but also one with a purpose.”
“The massive work by New Zealand scholar Sally-Ann Lambert is extraordinarily detailed, and the product of years of effort.
The problem is: The language in the book is not recognizable by contemporary scholars, or Native Tlingit speakers.”
We consider the problem of building detectors for high-level concepts using only unsupervised feature learning. For example, we would like to understand if it is possible to learn a face detector using only unlabeled images downloaded from the internet. To answer this question, we trained a simple feature learning algorithm on a large dataset of images (10 million images, each image is 200×200). The simulation is performed on a cluster of 1000 machines with fast network hardware for one week. Extensive experimental results reveal surprising evidence that such high-level concepts can indeed be learned using only unlabeled data and a simple learning algorithm.
Many natural processes occur over characteristic spatial and temporal scales. This paper presents tools for (i) flexibly and scalably coarse-graining cellular automata and (ii) identifying which coarse-grainings express an automaton’s dynamics well, and which express its dynamics badly. We apply the tools to investigate a range of examples in Conway’s Game of Life and Hopfield networks and demonstrate that they capture some basic intuitions about emergent processes. Finally, we formalize the notion that a process is emergent if it is better expressed at a coarser granularity.
We propose a nonlinear voter model to study the emergence of global consensus in opinion dynamics. In our model, agent $i$ agrees with one of binary opinions with the probability that is a power function of the number of agents holding this opinion among agent $i$ and its nearest neighbors, where an adjustable parameter $alpha$ controls the effect of herd behavior on consensus. We find that there exists an optimal value of $alpha$ leading to the fastest consensus for lattices, random graphs, small-world networks and scale-free networks. Qualitative insights are obtained by examining the spatiotemporal evolution of the opinion clusters.
REBOUND is a new multi-purpose N-body code which is freely available under an open-source license. It was designed for collisional dynamics such as planetary rings but can also solve the classical N-body problem. It is highly modular and can be customized easily to work on a wide variety of different problems in astrophysics and beyond.
Matching dependencies (MDs) have been recently introduced as declarative rules for entity resolution (ER), i.e. for identifying and resolving duplicates in relational instance $D$. A set of MDs can be used as the basis for a possibly non-deterministic mechanism that computes a duplicate-free instance from $D$. The possible results of this process are the clean, “minimally resolved instances” (MRIs). There might be several MRIs for $D$, and the “resolved answers” to a query are those that are shared by all the MRIs. We investigate the problem of computing resolved answers. We look at various sets of MDs, developing syntactic criteria for determining (in)tractability of the resolved answer problem, including a dichotomy result. For some tractable classes of MDs and conjunctive queries, we present a query rewriting methodology that can be used to retrieve the resolved answers. We also investigate connections with “consistent query answering”, deriving further tractability results for MD-based ER.
This article analyses a game where players sequentially choose either to become insiders and pick one of finitely many locations or to remain outsiders. They will only become insiders if a minimum distance to the next player can be assured; their secondary objective is to maximize the minimal distance to other players. This is illustrated by considering the strategic behavior of men choosing from a set of urinals in a public lavatory. However, besides very similar situations (e.g. settling of residents in a newly developed area, the selection of food patches by foraging animals, choosing seats in waiting rooms or lines in a swimming pool), the game might also relevant to the problem of placing billboards attempting to catch the attention of passers-by or similar economic situations. In the non-cooperative equilibrium, all insiders behave as if they cooperated with each other and minimized the total number of insiders. It is shown that strategic behavior leads to an equilibrium with substantial under utilization of available locations. Increasing the number of locations tends to decrease utilization. The removal of some locations which leads to gaps can not only increase relative utilization but even absolute maximum capacity.
Stencil computations, involving operations over the elements of an array, are a common programming pattern in scientific computing, games, and image processing. As a programming pattern, stencil computations are highly regular and amenable to optimisation and parallelisation. However, general-purpose languages obscure this regular pattern from the compiler, and even the programmer, preventing optimisation and obfuscating (in)correctness. This paper furthers our work on the Ypnos domain-specific language for stencil computations embedded in Haskell. Ypnos allows declarative, abstract specification of stencil computations, exposing the structure of a problem to the compiler and to the programmer via specialised syntax. In this paper we show the decidable safety guarantee that well-formed, well-typed Ypnos programs cannot index outside of array boundaries. Thus indexing in Ypnos is safe and run-time bounds checking can be eliminated. Program information is encoded as types, using the advanced type-system features of the Glasgow Haskell Compiler, with the safe-indexing invariant enforced at compile time via type checking.
It’s wrong to think of Ron Paul’s racism and his libertarianism as two distinct parts of his political persona, when in fact they are deeply tied together. White supremacists understand what Glenn, apparently, does not; the absence of Federal authority makes it easier for private actors and local governments to repress the civil and political rights of minorities. Paul’s libertarianism emerged in a regional and cultural context that was deeply hostile to Federal efforts at integration. The newsletters give strong indication that none of this is lost on Ron Paul. A notional President Paul is just as likely to use the powers of the office to gut Federal enforcement of a wide range of civil liberties protections as he is to do any of the things that Glenn would like him to do.