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- Alexey Radul
- DLS
- 2007

Reasoning with probabilistic models is a widespread and successful technique in areas ranging from computer vision, to natural language processing, to bioinformatics. Currently, these reasoning systems are either coded from scratch in general-purpose languages or use formalisms such as Bayesian networks that have limited expressive power. In both cases, the… (More)

The TREC Definition and Relationship questions are evaluated on the basis of information nuggets that may be contained in system responses. Human evalua-tors provide informal descriptions of each nugget, and judgements (assignments of nuggets to responses) for each response submitted by participants. While human evaluation is the most accurate way to… (More)

Derivatives, mostly in the form of gradients and Hessians, are ubiquitous in machine learning. Automatic differentiation (AD) is a technique for calculating derivatives of numeric functions expressed as computer programs efficiently and accurately, used in fields such as computational fluid dynamics , nuclear engineering, and atmospheric sciences. Despite… (More)

- Alexey Radul, Gerald Jay Sussman, Gerald, Jay Sussman
- 2008

We develop a programming model built on the idea that the basic computational elements are autonomous machines interconnected by shared cells through which they communicate. Each machine continuously examines the cells it is interested in, and adds information to some based on deductions it can make from information from the others. This model makes it easy… (More)

In this dissertation I propose a shift in the foundations of computation. Modern programming systems are not expressive enough. The traditional image of a single computer that has global effects on a large memory is too restrictive. The propagation paradigm replaces this with computing by networks of local, independent, stateless machines interconnected… (More)

We investigate a coin-weighing puzzle that appeared in the all-Russian Mathematics Olympiad in 2000. The methods of analysis differ from classical coin-weighing puzzles. We generalize the puzzle by varying the number of participating coins, and deduce a complete solution. Perhaps surprisingly, the objective can be achieved in no more than two weighings… (More)

We propose extensions to FORTRAN which integrate forward and reverse Automatic Differentiation (AD) directly into the programming model. Irrespective of implementation technology, embedding AD constructs directly into the language extends the reach and convenience of AD while allowing abstraction of concepts of interest to scientific-computing practice,… (More)

- Boris Katz, Gregory Marton, Sue Felshin, Daniel Loreto, Ben Lu, Federico Mora +7 others
- TREC
- 2006

Traditionally, distributed computing problems have been solved by partitioning data into chunks small enough to be handled by commodity hardware. However, such partitioning is not possible in cases where there are a high number of dependencies or high dimensionality, such as in reasoning and expert systems, rendering such problems less tractable for… (More)

We describe an implementation of the FARFEL FORTRAN AD extensions (Radul et al., 2012). These extensions integrate forward and reverse AD directly into the programming model, with attendant benefits to flexibility, modularity, and ease of use. The implementation we describe is a " prepreprocessor " that generates input to existing FORTRAN-based AD tools. In… (More)