NEURON-Request@ti-csl.csc.ti.COM (NEURON-Digest moderator Michael Gately) (04/11/88)
NEURON Digest Mon Apr 11 09:26:40 CDT 1988 Volume 3 / Issue 9 Today's Topics: Query on History of NN's Character font recognition SUN based NN simulator ??? Carver Mead's book request for net software Re: simula Re: Query on History of NN's Re simula Re: display tool for output from neural networks Stanford Adaptive Networks Colloquium Seminar Announcement -- Luis ALmeida at GTE Talk Announcement Complexity Theory and Hopfield Nets ---------------------------------------------------------------------- Date: 10 Mar 88 07:37:47 GMT From: Doug Salot <oliveb!felix!dhw68k!doug@ames.arc.nasa.gov> Subject: Query on History of NN's I'm curious about what those who are familiar with neural-net literature consider to be neural-net epochs. What papers are considered seminal? In a cursory examination of the literature, I'd have to say that the history goes something like Turing (1936), McCulloch & Pitts (1943), Hebb (1949), Rosenblatt (1966), Minsky & Papert (1969), and after that it's not at all clear to me what happens. Grossberg (late '70s)? Wilshaw? Sutton & Barto? Hopfield? Would you say Wiener and Cybernetics was a major influence? What about Leibniz or Shannon? BTW, has anyone considered using Usenet as a large grained neural network to which you throw out a question like "what is the meaning of life?" and watch it converge on a solution? Thanks in advance for helping me complete this partial match, - Doug -- Doug Salot | {trwrb,hplabs}!felix!dhw68k!feedme!doug CSUF School of Computer Thought | doug@dhw86k.cts.com "The cobweb behind the Orange Curtain"| If it needs a :-), it isn't funny. ------------------------------ Date: 18 Mar 88 13:34:12 GMT From: Stan Dembinski <eplrx7!stan@uunet.uu.net> Subject: Character font recognition Has anybody been addressing the problem of character font recognition? I have a vague recollection of a paper having looked at a limited font set (the Scientific American magazine font was part of the set). Does anyone know that ( or other) reference? Neural Net as well as other more classical approaches are welcome. Thank you in advance, -- Stan Dembinski | E.I. Dupont Co. uunet!eplrx7!stan | Engineering Physics Lab | Wilmington, Delaware 19891 (302) 695-7947 | Mail Stop: E357-311 ------------------------------ Date: 23 Feb 88 20:44:00 GMT From: clyde!burl!codas!novavax!hcx1!garyb@rutgers.edu Subject: SUN based NN simulator ??? I have seen mention of a SUN based neural-net simulator developed at Caltech in a recent article from this newsgroup. Could someone in-the-know elaborate on this. I'm specifically interested in its functionality, portability to other UNIX platforms, and its availability status. I'm also looking for other references to work in area of neural-net specification languages and mechanisms. I'll summarize and post if necessary. Thank you for your support. ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++ | Gary Barton | ..from the home of the HCX.. | | Software Development | Harris Computer Systems Division | +-----------------------------------------+----------------------------------+ | garyb@ssd.harris.com | 2101 W. Cypress Creek Rd. | | {uunet,cbosgd,mit-eddie}!hcx1!garyb | Ft. Lauderdale. FL 33309 | | {mtune,gatech}!codas!novavax!hcx1!garyb | (305) 974-1700 | ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++ ------------------------------ Date: Mon, 21 Mar 88 14:00 EDT From: DAVIS@blue.sdr.slb.com Subject: Carver Mead's book X-Vms-To: MRGATE::M_SDR::IN%"neuron@ti-csl" Hi. Somewhere, or via someone, I have heard that Carver Mead, man of optical neural nets, has a book due out called, as I recall, "Analog VLSI and the brain". Has anyone come across this, or does anyone know when its due out ? Carver - if you're out there, please let me know..... with mnay thanks, Paul Davis Schlumberger Cambridge Research, England. davis%m_scrvx2@sdr.slb.com ------------------------------ Date: 21 Mar 88 19:05:58 GMT From: "Wayne D. T. Johnson" <hubcap!ncrcae!ncr-sd!ncrlnk!ncrcce!c10sd3!c10sd1!johnson@gatech.edu> Subject: request for net software I have recently read an article on neural nets in the last issue of discovery (I think). As a software Engineer (AKA Programmer) I would be very interested if any one out there could direct me to a source of Public Domain (term used genericly, including such classes as shareware, freeware, etc.) software for UNIX or an IBM PC/Compatible that could be useful to a basement experimentor such as I. I would also like to start a list of basic texts containing information on nets. Not that some of the information in this group isn't useful its just that sometimes it goes so far over my head.... If any one would like to contribute any information, please send it to me via E-mail. If any one would like a copy of what I receive, send me a self addressed stamped E-mail envlope and I will try to send it back. Thanks in advance Wayne Johnson ------------------------------ Date: 10 Mar 88 13:20:29 GMT From: Robert Claeson <mcvax!enea!pvab!robert@uunet.uu.net> Subject: Re: simula In article <464@sbsvax.UUCP>, ks@sbsvax.UUCP (Kurt Schreiner) writes: > we are looking for a simula system (compiler or interpreter), preferably > simula67 which runs under unix (4.3bsd preferred, but others could be hacked) > or siemens bs2000. a PD version would be most exiting, but hints to lowcost > custom versions are also welcome. Sun's Catalyst gives this: Simula General Purpose, object-oriented, high-level programming language. SIMPROG AB P.O. Box 26016 S-100 41 Stockholm Sweden Tel: +46 8 109912 TLX: 16871 There may be versions for a VAX too. ------------------------------ Date: 11 Mar 88 20:11:36 GMT From: Olivier Brousse <olivier@boulder.colorado.edu> Subject: Re: Query on History of NN's In article <5779@dhw68k.cts.com> doug@dhw68k.cts.com (Doug Salot) writes: >I'm curious about what those who are familiar with neural-net literature Roughly speaking, I would say: Late seventies: Kohonen, on associative memories " " : Grossberg, on Adaptive Resonance Theory " " : Barto and Sutton Early eighties: McClelland, Rumelhart and the PDP group: Back-propagation, Boltzmann machines, Harmony theory, distributed representations, cognitive process modeling. " " : Hopfield, on analogy with physical systems. Olivier Brousse | Department of Computer Science | olivier@boulder.colorado.EDU U. of Colorado, Boulder | ------------------------------ Date: 13 Mar 1988 19:20-EST From: Tor Sverre Lande <bassen@ifi.uio.no> Subject: Re simula If your ever think of using SIMULA-67 on UNIX the only usable version is the one from Lund, Sweden. We are using it both on SUN and VAX-en with pretty good performance both on compilation and execution. That portable stuff (S-PORT) is totally unusable. Tor Sverre Lande Institute of Informatics University of Oslo Norway (Simula-land?) ------------------------------ Date: 15 Mar 88 06:36:20 GMT From: Jeanne Rich <agate!saturn!rich@ucbvax.berkeley.edu> Subject: Re: display tool for output from neural networks In article <405@grian.UUCP> liz@grian.UUCP (Liz Allen-Mitchell) writes: >Does anyone have software that take numbers output from a neural >network and display them graphically? For example, something that read >sets of numbers representing the activation levels at a set of nodes >and displayed them as gray levels in boxes would be great. I am >working on a sun 3/60 so software that would run on a sun would be best >though anything would be better than nothing. > Yes, The Rochester Simulation Package provides a graphics package with it, which runs under suntools. You can look at the unit activations, among other things. The package is fairly flexible, allowing you to construct any kind of network. I believe their was a recent posting on who to contact at Rochester. I also believe the cost of the package is $150.00 Jeanne M. Rich rich@saturn.ucsc.edu ucbvax!ucscc!saturn!rich CIS Board UCSC Santa Cruz, CA 95064 (408) 429-4043 ------------------------------ Date: Wed, 23 Mar 88 07:50:37 PST From: Mark Gluck <netlist@psych.stanford.edu> Subject: Stanford Adaptive Networks Colloquium Stanford University Interdisciplinary Colloquium Series: Adaptive Networks and their Applications March 29th (Tuesday, 3:15pm) "Casting Neural Networks into Silicon: there's good news, and there's bad news. DAN HAMMERSTROM Computer Science&Engineering The Oregon Graduate Center Abstract -------- Researchers are developing neural-like network models that exhi- bit a broad range of cognitive behavior. Unfortunately, existing computer systems are limited in their ability to emulate such networks efficiently. Consequently, the OGC Cognitive Architec- ture Project is studying the implementation of massively parallel architectures for the emulation of a range of very large connectionist/neural networks. The goal of our project is to build ultra-large-scale-integrated, silicon-based computing structures that will be able to emulate connectionist/neural net- works with thousands of nodes and millions of connections at rates exceeding that of their biological counterparts. The manufacturing costs for these systems will be a few thousand dol- lars. Such ultra-large die size (larger than the traditional 1 square centimeter) is made possible by the inherent fault- tolerance of the computational model. This talk will explore some of the problems and potential solutions in developing such architectures. . . . . Format: Tea will be served 15 minutes prior to the talk, outside the lecture hall. The talks (including discussion) last about one hour. Following the talk, there will be a reception in the fourth floor lounge of the Psychology Dept. Location: Room 380-380W, which can be reached through the lower level between the Psychology and Mathematical Sciences buildings. Technical Level: These talks will be technically oriented and are intended for persons actively working in related areas. They are not intended for the newcomer seeking general introductory material. Information: For additional information, contact Mark Gluck (gluck@psych.stanford.edu) 415-725-2434. * * * Co-Sponsored by: Departments of Electrical Engineering (B. Widrow) and Psychology (D. Rumelhart, M. Gluck), Stanford Univ. ------------------------------ Date: Fri, 25 Mar 88 11:06:53 EST From: Rich Sutton <rich@gte-labs.csnet> Subject: Seminar Announcement -- Luis ALmeida at GTE BACKPROPAGATION IN NONFEEDFORWARD NETWORKS Luis B. Almeida INESC, Portugal 10 AM, April 8th, in the GTE Labs Auditorium The subject of this talk will be the extension of the backpropagation learning rule to nonfeedforward networks. The classical backpropagation rule for feedforward networks will first be reviewed, in terms of operations on networks (linearization and transposition), in order to better visualize what the solution for nonfeedforward networks might be. The proof of the validity of this solution will then be given. Next, stability issues will be addressed. Finally, some experimental results will be presented. ----------------------------------------------------------------------- In my opinion, Almeida has done some of the best work on generalizing the back-propagation learning algorithm to recurrent (cycle containing) networks (see his paper in the ICNN-87 proceedings). He will be spending the day at GTE, so there should be ample opportunity for discussions. Visitors should arrive early and ask for Mary Anne Fox. GTE Labs is off Rt. 128 at Waltham, west off the Winter St. exit. For questions contact me (466-4133) or Mary Anne Fox (466-4207). -Rich Sutton ------------------------------ Date: 11 Mar 88 17:05:35 GMT From: Kangsuk Lee <siemens!demon!kslee@princeton.edu> Subject: Talk Announcement \fBSome Perspectives on Analog Computation\fR \fIBradley W. Dickinson\fR Dept. of Electrical Engineering Princeton University Princeton, NJ 08544 \fBDate: March 23 (Wed) 10:00 \fR \fBPlace: Siemens RTL, Princeton NJ \fR \fBContact: Tom Petsche (609) 734-3392\fR The term \fIanalog computation\fR evokes numerous associations; the planimeter, the slide rule, the differential analyzer, and other physical computing systems are modeled by mathematical equations with diverse applications. By drawing a careful distinction between analog and digital computation, it becomes possible to compare the use of analog computation in the solution of various optimization problems with the use of digital computation. Can analog computation be used to solve intractable combinatorial optimization problems, circumventing the apparent limitations of digital computation? We will argue that this is unlikely, based on a simulation paradigm. Differential equation models associated with $bold { NP }$-complete problems have been proposed in the literature. These provide an opportunity to explore and develop interesting complexity issues related to dynamic systems. A common shortcoming is the failure of the model to admit a scaling that constrains the solutions to evolve in a polynomially-bounded hypercube in ``configuration-space'', for a fixed level of precision of the computation. Analog sorting schemes provide a simple illustration of this inherent obstacle to solution of ``numerical'' problems by analog means. The differential equation models for ``nonnumerical'' problems can also suffer from this drawback. One topic to be discussed is the ``neural network'' formulation proposed by Hopfield and Tank for the solution of the $bold { NP }$-complete Traveling Salesman Problem with systems described by differential equations. The scaling problem in this model arises from the use of highly nonlinear amplifier characteristics. Time permitting, some possible connections with ergodic theory and complex dynamics (chaos) will be mentioned. It appears that even in dynamic systems where scaling problems do not arise, the ability to do computation may be severely limited. Kangsuk Lee, Siemens RTL Learning Systems Lab 105 College Road, Princeton, NJ 08540 e-mail: kslee@siemens.com or princeton!siemens!kslee ------------------------------ Date: Sun, 13 Mar 88 12:41:54 EST From: John Lipscomb <lipscomb@ai.toronto.edu> Subject: Complexity Theory and Hopfield Nets Two M.Sc. theses are available by writing or e-mailing me. They are The Computational Complexity of the Stable Configuration Problem for Connectionist Models Gail H. Godbeer September 1987 (latex typesetting) \begin {abstract} Connectionist models (CM's) are typically used to perform constraint-satisfaction searches. We know that the problem of finding the configuration that least violates the constraints in a CM is $NP$-hard. We thus look at the complexity of finding {\em stable} configurations, or configurations in which all the local constraints are satisfied. The complexity of finding a stable configuration varies greatly depending on the type of weights in a CM. We thus classify CM's according to their weights and examine the parallel and sequential complexity of this problem for the various classes. \end {abstract} AND On the Computational Complexity of Finding a Connectionist Model's Stable State Vectors John Lipscomb October 1987 \newcommand{\cm}{{\sc cm}} \newcommand{\ssv}{stable state vector} \begin{abstract} Our {\em Connectionist Models\/} (\cm's) are fixed weighted simple graphs where each node can be in one of two states: {\em on}\/ or {\em off}. A {\em \ssv\/} for a \cm\ is an assignment of states to the nodes such that each node is stable. The stability of a node depends on its state, its weight, incident edge weights, and neighboring nodes' states. Our principle results are \begin{itemize} \item The decision problem ``Given a directed \cm, does it have a \ssv?'' is NP-complete. \item The search problem ``Given an undirected \cm, find a \ssv\ for it.'' is P-hard under \NC{1} reductions. \item The decision problem ``Given an undirected \cm, does it have at least two different \ssv s?'' is NP-complete. \item The decision problem ``Given an undirected \cm, a node $x$, and a state $s$, does the \cm\ have a \ssv\ with node $x$ in state $s$?'' is NP-complete. \end{itemize} We consider the complexity of these problems on more restricted classes of \cm's, and prove that the problem of finding a \ssv\ can be solved in O($m$) sequential time, where $m$ is the number of edges, for \cm's with only positive edges or for bipartite \cm's with only negative edges. The obvious major question is still open: ``Is there a poly-time algorithm for finding a \ssv\ for an undirected \cm?'' Also of interest is whether any interesting restricted class of \cm's has a fast parallel algorithm for finding a \ssv. \end{abstract} The theses overlap in parts, but the different perspective is worthwhile. John Lipscomb Dept. of Computer Sc. University of Toronto Toronto, Canada M5S 1A4 (416) 978-4837 home ph: 928-3310 electronic mail: lipscomb@ai.toronto.edu (CSnet,UUCP,Bitnet) {uunet,watmath}!ai.toronto.edu!lipscomb ------------------------------ End of NEURON-Digest ********************
mejia@laidbak.UUCP (Galo Mejia) (04/14/88)
I want to pose my ideas as questions. Does anyone knows if programs like Conway's "game of life" have been implemented in neural-net computers like The Connection machine. The pattern recognition potential of such algorithms can be fully explored in fine-grained networks with strong neighbor connectivity. Visual recognition, in my view, can be modeled by convolutional cyclical process in search for patterns (stored in local memory) that represent knowledge. This knowledge is transferred either to another net-subsystem or to an output device. Galo ..ihnp4!laibak!mejia (614) 864-3418 ---
berryh@udel.EDU (John Berryhill) (04/15/88)
DAVIS@blue.sdr.slb.com (Paul Davis) writes: > Hi. Somewhere, or via someone, I have heard that Carver Mead, > man of optical neural nets, has a book due out called, as I Carver Mead may be many things. However, she is not a "man" of anything. John Berryhill berryh@udel.huey.edu
chi@tybalt.caltech.edu (Curt Hagenlocher) (04/15/88)
In article <2071@louie.udel.EDU> berryh@udel.EDU (John Berryhill) writes: > > DAVIS@blue.sdr.slb.com (Paul Davis) writes: >> Hi. Somewhere, or via someone, I have heard that Carver Mead, >> man of optical neural nets, has a book due out called, as I > >Carver Mead may be many things. However, she is not a "man" Carver Mead is most certainly a male. He teaches at least one class here at Caltech, which I plan on taking sometime in the near future. cit-vax!tybalt!chi chi@tybalt.caltech.edu "Education? Who needs one? I came here to make big bucks!"
odea@tybalt.caltech.edu (J. Andrew ODea) (04/15/88)
In article <2071@louie.udel.EDU> berryh@udel.EDU (John Berryhill) writes: > > DAVIS@blue.sdr.slb.com (Paul Davis) writes: >> Hi. Somewhere, or via someone, I have heard that Carver Mead, >> man of optical neural nets, has a book due out called, as I > >Carver Mead may be many things. However, she is not a "man" >of anything. > >John Berryhill berryh@udel.huey.edu When I was taking Carver Mead's course earlier this year, I was pretty sure he was a man. Something about the beard... Andrew O'Dea ODEA@TYBALT.CALTECH.EDU
floyd@brl-smoke.ARPA (Floyd C. Wofford) (04/15/88)
In article <2071@louie.udel.EDU> berryh@udel.EDU (John Berryhill) writes: > >Carver Mead may be many things. However, she is not a "man" >of anything. > >John Berryhill berryh@udel.huey.edu Perhaps you are reminded of Lynn Conway (of Mead & Conway fame). She, most definitely, is a woman. There is an interesting article about her in a recent SPECTRUM. (Say hello to Dr. Warter for me.) Floyd Wofford floyd@brl.arpa
berryh@udel.EDU (John Berryhill) (04/16/88)
In article <7694@brl-smoke.ARPA> floyd@brl.arpa (Floyd C. Wofford) writes: >Perhaps you are reminded of Lynn Conway (of Mead & Conway fame). She, >most definitely, is a woman. There is an interesting article about her >in a recent SPECTRUM. (Say hello to Dr. Warter for me.) I stand corrected. Or rather, I will stand corrected as soon as I get my foot out of my mouth. Having used a Mead & Conway book for so long, I get them confused. John Berryhill
bjpt@maui.cs.ucla.edu (Benjamin Thompson) (04/16/88)
>>Carver Mead may be many things. However, she is not a "man" >>of anything. > >When I was taking Carver Mead's course earlier this year, I was pretty sure he >was a man. Something about the beard... Perhaps he's swapped with Lynn Conway since then ...
shafto@eos.UUCP (Michael Shafto) (04/19/88)
Let me add my vote for the masculinity of Carver Mead. I was present at his [?] talk at the ONR 40th Anniversary Research Symposium. He appeared to (admittedly casual) inspection to be a man. Mike