Goto

Collaborating Authors

 Law


Predictive Coding with Neural Nets: Application to Text Compression

Neural Information Processing Systems

To compress text files, a neural predictor network P is used to approximate theconditional probability distribution of possible "next characters", given n previous characters. P's outputs are fed into standard coding algorithms that generate short codes for characters with high predicted probability and long codes for highly unpredictable characters.Tested on short German newspaper articles, our method outperforms widely used Lempel-Ziv algorithms (used in UNIX functions such as "compress" and "gzip").


The Workshop on Computational Dialectics

AI Magazine

Surely, scientific arguments Still, a full literature search of citations They are trivial, that is, when compared have their own special logic. of Rescher's 1977 monograph, to the defeasibility of open-textured Cavalli-Sforza has for a while been Dialectics, reveals no useful formal concepts, the logic of which interested in Toulmin's own attempts extension or clarification of the logical remains unanalyzed (says McCarty, to apply his work on argument to system prior to Brewka.


History-Dependent Attractor Neural Networks

Neural Information Processing Systems

We present a methodological framework enabling a detailed description of the performance of Hopfield-like attractor neural networks (ANN) in the first two iterations. Using the Bayesian approach, we find that performance is improved when a history-based term is included in the neuron's dynamics. A further enhancement of the network's performance is achieved by judiciously choosing the censored neurons (those which become active in a given iteration) on the basis of the magnitude of their post-synaptic potentials. The contribution of biologically plausible, censored, historydependent dynamics is especially marked in conditions of low firing activity and sparse connectivity, two important characteristics of the mammalian cortex. In such networks, the performance attained is higher than the performance of two'independent' iterations, which represents an upper bound on the performance of history-independent networks.


History-Dependent Attractor Neural Networks

Neural Information Processing Systems

We present a methodological framework enabling a detailed description of the performance of Hopfield-like attractor neural networks (ANN) in the first two iterations. Using the Bayesian approach, we find that performance is improved when a history-based term is included in the neuron's dynamics. A further enhancement of the network's performance is achieved by judiciously choosing the censored neurons (those which become active in a given iteration) on the basis of the magnitude of their post-synaptic potentials. The contribution of biologically plausible, censored, historydependent dynamics is especially marked in conditions of low firing activity and sparse connectivity, two important characteristics of the mammalian cortex. In such networks, the performance attained is higher than the performance of two'independent' iterations, which represents an upper bound on the performance of history-independent networks.


History-Dependent Attractor Neural Networks

Neural Information Processing Systems

We present a methodological framework enabling a detailed description ofthe performance of Hopfield-like attractor neural networks (ANN) in the first two iterations. Using the Bayesian approach, wefind that performance is improved when a history-based term is included in the neuron's dynamics. A further enhancement of the network's performance is achieved by judiciously choosing the censored neurons (those which become active in a given iteration) onthe basis of the magnitude of their post-synaptic potentials. Thecontribution of biologically plausible, censored, historydependent dynamicsis especially marked in conditions of low firing activity and sparse connectivity, two important characteristics of the mammalian cortex. In such networks, the performance attained ishigher than the performance of two'independent' iterations, whichrepresents an upper bound on the performance of history-independent networks.


Green Engineering AI Tools Benefit the Environment

AI Magazine

Although the economic results of PDEC's green engineering techniques are only beginning to come in, they are nonetheless compelling. In addition, as green engineering grows in practice, the outset for the entire life cycle of new jobs in remanufacturing have been applied to a product, designing for component and recycling will be created. The consortium is currently Common Lisp. It plots a cost curve A pioneering consortium at engaged in two major development that represents the effort put into Carnegie Mellon University (CMU) is activities: (1) green indicators that are disassembly, testing, repair and using AI, combined with operations measures of environmental compatibility remanufacturing, quality assurance, research, environmental science, and (2) tools that use the green and product design changes that public policy, and other disciplines, indicators to help designers make allow for recovery. It also plots a to build tools for green engineering.


Tennessee Offender Management Information System

AI Magazine

Parole board date order received three different parole dates. On the changes, probation judgments, and new laws earliest of these parole dates, he would be eligible and sentencing guidelines enacted each year for release from prison to serve the remainder by the state legislature also affect sentence calculations. of his sentence in the community. Finally, Because offenders are often sentenced because of overcrowding in the prison, Doe under multiple laws, these changes can received a safety valve date, which is a fraction create a complex equation for judges and of his time to serve until parole.


Knowledge Discovery in Databases: An Overview

AI Magazine

After a decade of fundamental interdisciplinary research in machine learning, the spadework in this field has been done; the 1990s should see the widespread exploitation of knowledge discovery as an aid to assembling knowledge bases. The contributors to the AAAI Press book Knowledge Discovery in Databases were excited at the potential benefits of this research. The editors hope that some of this excitement will communicate itself to "AI Magazine readers of this article.


Bylaws of the American Association for Artificial Intelligence

AI Magazine

The Executive Council may change the principal office in California The name of this corporation shall be the American Association from one location to another. The corporation may have such other offices, either within or without the State of California, ARTICLE II. This corporation is a nonprofit public benefit corporation and is not organized for the private gain of any person. MEMBERS is organized under the California Nonprofit Corporation Law for scientific and educational purposes in the field of Section 1. Classes and Privileges. Student members have all the rights and privileges of Regular ARTICLE III. The Executive Council shall determine (a) This corporation is organized and operated exclusively the qualifications for membership in the corporation.


AAAI News

AI Magazine

All inquiries should include your travel support for students who are registration area. Now Exempt from applicants must have fulfilled your lab's research efforts to be the volunteer and reporting requirements California Sales Tax shown to a large portion of the AI for previous awards. This year, Recent California legislation required community. California that can be run in parallel on several who submit a letter of recommendation Senate Bill 89 (Chapter 461, screens. Please do not send tapes of a from a faculty supervisor in lieu Statutes of 1991)-signed by the governor particular project or lecture but, of a paper, student authors from foreign at press time-provides AAAI rather, tapes that present broad institutions, and foreign scholars.