Unnamed: 0 int64 0 7.24k | id int64 1 7.28k | raw_text stringlengths 9 124k | vw_text stringlengths 12 15k |
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7,200 | 961 | Transformation Invariant Autoassociation
with Application to
Handwritten Character Recognition
Holger Schwenk
Maurice Milgram
PARC
Universite Pierre et Marie Curie
tour 66-56, boite 164
4, place Jussieu, 75252 Paris cedex 05, France.
e-mail: schwenk@robo.jussieu.fr
Abstract
When training neural networks by the clas... | 961 |@word deformed:1 version:4 briefly:1 middle:2 seems:2 simulation:1 propagate:1 reduction:1 moment:1 contains:2 score:2 activation:1 must:5 visible:1 numerical:1 alone:1 intelligence:1 selected:1 realizing:1 short:1 boosting:3 hyperplanes:1 sigmoidal:1 combine:1 introduce:1 expected:1 rapid:1 alspector:1 behavior:3... |
7,201 | 962 | Recognizing Handwritten Digits Using Mixtures of Linear Models
Geoffrey E Hinton
Michael Revow Peter Dayan
Deparbnent of Computer Science, University of Toronto
Toronto, Ontario, Canada M5S lA4
Abstract
We construct a mixture of locally linear generative models of a collection of pixel-based images of digits, and use... | 962 |@word briefly:1 version:9 compression:2 proportion:1 grey:1 r:4 tried:1 covariance:12 decomposition:1 reduction:1 initial:1 united:1 si:1 assigning:1 must:1 generative:8 leaf:1 intelligence:1 selected:1 plane:2 isotropic:4 summarisation:1 dissertation:1 provides:1 coarse:1 toronto:3 along:10 symposium:1 incorrect:... |
7,202 | 963 | An Auditory Localization
and Coordinate Transform Chip
Timothy K. Horiuchi
timmer@cns.caltech.edu
Computation and Neural Systems Program
California Institute of Technology
Pasadena, CA 91125
Abstract
The localization and orientation to various novel or interesting
events in the environment is a critical sensorimotor ... | 963 |@word neurophysiology:1 azimuthal:1 propagate:1 pulse:8 mammal:1 moment:1 electronics:2 contains:2 olded:1 current:6 activation:1 must:2 physiol:1 distant:1 motor:1 asymptote:1 plot:3 v:3 cue:2 plane:1 filtered:2 provides:2 location:6 mathematical:1 constructed:3 consists:6 inter:1 roughly:1 behavior:1 discretized... |
7,203 | 964 | An Input Output HMM Architecture
Yoshua Bengio*
Dept. Informatique et Recherche
Operationnelle
Universite de Montreal, Qc H3C-3J7
bengioyOIRO.UMontreal.CA
Paolo Frasconi
Dipartimento di Sistemi e Informatica
Universita di Firenze (Italy)
paoloOmcculloch.ing.unifi.it
Abstract
We introduce a recurrent architecture havi... | 964 |@word trial:9 cu:1 version:2 open:1 propagate:1 jacob:3 initial:2 series:1 exclusively:1 denoting:2 esj:1 current:7 contextual:1 nt:1 nowlan:4 activation:2 motor:1 remove:1 update:1 discrimination:2 selected:1 discovering:1 smith:2 short:1 recherche:1 quantized:1 node:1 sigmoidal:1 five:1 differential:1 become:1 c... |
7,204 | 965 | Learning from queries for maximum
information gain in imperfectly learnable
problems
Peter Sollich David Saad
Department of Physics, University of Edinburgh
Edinburgh EH9 3JZ, U.K.
P.Sollich~ed.ac.uk. D.Saad~ed.ac.uk
Abstract
In supervised learning, learning from queries rather than from
random examples can improve g... | 965 |@word version:15 achievable:5 covariance:1 tr:1 reduction:3 contains:1 efficacy:3 selecting:1 existing:6 comparing:1 readily:1 additive:2 happen:1 plot:1 progressively:1 half:1 selected:2 hypersphere:1 provides:1 ron:1 firstly:1 simpler:4 along:4 become:2 expected:2 themselves:1 frequently:1 wallace:2 spherical:1 ... |
7,205 | 966 | Boltzmann Chains and Hidden
Markov Models
Lawrence K. Saul and Michael I. Jordan
lksaulOpsyche.mit.edu, jordanOpsyche.mit.edu
Center for Biological and Computational Learning
Massachusetts Institute of Technology
79 Amherst Street, E10-243
Cambridge, MA 02139
Abstract
We propose a statistical mechanical framework for ... | 966 |@word middle:3 polynomial:1 simulation:1 ajj:2 idl:1 initial:1 configuration:2 series:12 disparity:2 comparing:1 must:3 visible:11 partition:3 enables:1 mstep:1 designed:1 update:3 fewer:1 compo:1 constructed:1 combine:1 idr:1 baldi:2 notably:1 indeed:1 themselves:1 nor:1 mechanic:3 unfolded:1 provided:1 moreover:... |
7,206 | 967 | An Integrated Architecture of Adaptive Neural Network
Control for Dynamic Systems
Robert L. Tokar2
Brian D.McVey 2
'Center for Nonlinear Studies, 2Applied Theoretical Physics Division
Los Alamos National Laboratory, Los Alamos, NM, 87545
Abstract
In this study, an integrated neural network control architecture for n... | 967 |@word hyperstates:1 solid:6 liu:4 series:1 yet:12 john:1 realize:2 plot:1 designed:1 update:1 alone:1 plane:1 provides:1 node:3 become:1 supply:1 persistent:1 combine:2 becomes:1 kind:5 control:86 producing:1 t1:1 engineering:1 sutton:1 id:1 emphasis:1 au:2 hunt:2 palmer:1 testing:2 implement:2 differs:1 backpropa... |
7,207 | 968 | Capacity and Information Efficiency of a
Brain-like Associative Net
Bruce Graham and David Willshaw
Centre for Cognitive Science, University of Edinburgh
2 Buccleuch Place, Edinburgh, EH8 9LW, UK
Email: bruce@cns.ed.ac.uk&david@cns.ed.ac.uk
Abstract
We have determined the capacity and information efficiency of an
asso... | 968 |@word soc:1 effect:1 contain:1 maz:1 version:1 come:1 proportion:1 analytically:1 occurs:1 strategy:23 simulation:5 deal:1 heteroassociative:1 pg:1 during:3 amongst:1 incompletely:1 behaviour:1 capacity:39 oa:1 configuration:2 recollection:1 presenting:1 recognised:1 dendritic:18 theoretic:1 trivial:1 delivers:1 c... |
7,208 | 969 | Adaptive Elastic Input Field for
Recognition Improvement
Minoru Asogawa
C&C Research Laboratories, NEe
Miyamae, Miyazaki, Kawasaki Kanagawa 213 Japan
asogawa~csl.cl.nec.co.jp
Abstract
For machines to perform classification tasks, such as speech and
character recognition, appropriately handling deformed patterns
is a ... | 969 |@word deformed:2 initial:1 configuration:1 contains:1 score:8 current:1 comparing:1 blank:1 activation:5 si:1 written:1 numerical:1 selected:1 guess:5 yamada:3 location:13 simpler:1 become:1 comb:1 forgetting:1 presumed:1 compensating:2 csl:1 little:1 totally:1 becomes:1 classifies:1 moreover:1 lowest:1 miyazaki:1... |
7,209 | 97 | 289
NEURAL ANALOG DIFFUSION-ENHANCEMENT
LAYER AND SPATIO-TEMPORAL GROUPING
IN EARLY VISION
Allen M. Waxman?,t, Michael Seibert?,t,RobertCunninghamt and I ian Wu?
? Laboratory for Sensory Robotics
Boston University
Boston, MA 02215
t Machine Intelligence Group
MIT Lincoln Laboratory
Lexington, MA 02173
ABSTRACT
A new... | 97 |@word simulation:1 kent:2 thereby:2 solid:2 initial:6 configuration:2 activation:2 yet:1 realize:1 distant:2 periodically:2 shape:3 plot:2 v:1 stationary:1 intelligence:3 cue:3 plane:1 inspection:1 feedfoward:1 short:3 farther:1 detecting:1 provides:1 location:2 successive:1 yarbus:2 five:3 along:1 become:1 differe... |
7,210 | 970 | Sample Size Requirements For
Feedforward Neural Networks
Michael J. Turmon
Cornell Univ. Electrical Engineering
Ithaca, NY 14853
mjt@ee.comell.edu
Terrence L. Fine
Cornell Univ. Electrical Engineering
Ithaca, NY 14853
tlfine@ee.comell.edu
Abstract
We estimate the number of training samples required to ensure that
the... | 970 |@word determinant:1 blu:3 ona:1 seek:1 simulation:2 covariance:4 accounting:1 initial:1 chervonenkis:2 existing:1 z2:1 comell:2 activation:3 must:2 realistic:1 informative:1 shape:1 drop:1 clumping:6 alone:1 item:1 warmuth:1 farther:1 compo:1 provides:1 math:1 contribute:1 shatter:1 c2:1 along:1 sustained:1 indeed... |
7,211 | 971 | Combining Estimators Using
Non-Constant Weighting Functions
Volker Tresp*and Michiaki Taniguchi
Siemens AG, Central Research
Otto-Hahn-Ring 6
81730 Miinchen, Germany
Abstract
This paper discusses the linearly weighted combination of estimators in which the weighting functions are dependent on the input .
We show that ... | 971 |@word version:1 advantageous:1 seems:1 retraining:2 tried:1 jacob:2 decomposition:4 covariance:2 tr:4 reduction:1 neuneier:2 current:1 nt:2 nowlan:3 location:1 toronto:1 miinchen:1 simpler:3 combine:1 introduce:2 manner:1 acquired:1 forgetting:1 expected:1 indeed:1 alspector:1 multi:1 brain:1 considering:2 becomes... |
7,212 | 972 | A model of the hippocampus combining selforganization and associative memory function.
Michael E. Hasselmo, Eric Schnell
Joshua Berke and Edi Barkai
Dept. of Psychology, Harvard University
33 Kirkland St., Cambridge, MA 02138
hasselmo@katla.harvard.edu
Abstract
A model of the hippocampus is presented which forms rapi... | 972 |@word h:1 illustrating:1 version:5 selforganization:1 hippocampus:9 simulation:13 r:1 heteroassociative:1 thereby:1 ld:3 series:1 zurada:1 longitudinal:1 current:8 activation:8 buckingham:3 subsequent:1 j1:1 interspike:1 medial:3 tenn:1 intelligence:1 nervous:1 reciprocal:1 compo:1 provides:1 rgm:2 org:2 behaviora... |
7,213 | 973 | Catastrophic Interference in Human
Motor Learning
Tom Brashers-Krug, Reza Shadmehr t , and Emanuel Todorov
Dept. of Brain and Cognitive Sciences, M. I. T., Cambridge, MA 02139
tCurrently at Dept. of Biomedical Eng., Johns Hopkins Univ., Baltimore, MD 21205
Email: tbk@ai.mit.edu, reza@bme.jhu.edu, emo@aLmit.edu
Abstra... | 973 |@word seems:2 open:1 eng:1 jacob:4 fifteen:1 ld:1 moment:3 initial:4 ivaldi:5 series:2 practiced:3 current:6 yet:1 must:2 john:1 subsequent:1 plasticity:1 motor:16 displace:1 wanted:1 plot:1 medial:1 half:1 cue:1 manipulandum:4 nervous:1 positron:1 short:1 location:1 successive:2 five:1 mathematical:1 along:1 dire... |
7,214 | 974 | Model of a Biological Neuron as a Temporal
Neural Network
Sean D. Murphy and Edward W. Kairiss
Interdepartmental Neuroscience Program, Department of Psychology,
and The Center for Theoretical and Applied Neuroscience,
Yale University,
Box 208205, New Haven, CT 06520
Abstract
A biological neuron can be viewed as a devi... | 974 |@word trial:3 middle:1 hippocampus:1 simulation:4 versatile:1 series:1 contains:1 past:3 comparing:1 activation:3 yet:1 numerical:1 realistic:4 plasticity:1 designed:2 v:1 device:2 ith:1 short:1 oneto:1 filtered:1 characterization:1 node:24 location:1 simpler:1 nodal:1 along:1 differential:1 consists:2 compose:1 b... |
7,215 | 975 | Dynamic Cell Structures
Jorg Bruske and Gerald Sommer
Department of Cognitive Systems
Christian Albrechts University at Kiel
24105 Kiel- Germany
Abstract
Dynamic Cell Structures (DCS) represent a family of artificial neural
architectures suited both for unsupervised and supervised learning.
They belong to the recently... | 975 |@word repository:1 version:1 compression:1 retraining:1 simulation:10 u11:1 tr:3 initial:2 contains:2 tuned:1 existing:2 current:1 nt:1 activation:2 lang:2 readily:2 distant:1 shape:1 christian:1 update:2 fewer:1 plane:1 directory:1 dissertation:1 record:1 num:1 math:1 node:2 location:2 kiel:4 albrechts:1 become:1... |
7,216 | 976 | On-line Learning of Dichotomies
N. Barkai
H. S. Seung
AT&T Bell Laboratories
Murray Hill, NJ 07974
seungCphysics.att.com
Racah Institute of Physics
The Hebrew University
Jerusalem, Israel 91904
naamaCfiz.huji.ac.il
H. Sompolinsky
Racah Institute of Physics
The Hebrew University
Jerusalem, Israel 91904
and AT&T Be... | 976 |@word h:1 polynomial:1 simulation:4 solid:2 kappen:2 initial:2 att:1 com:1 yet:1 dx:2 written:1 realistic:1 numerical:2 asymptote:1 fund:1 alone:1 half:3 stationary:2 implying:1 plane:2 isotropic:3 provides:1 ron:7 differential:3 become:1 indeed:1 roughly:1 behavior:1 tje:1 mechanic:1 v1t:1 adiabatically:2 decreas... |
7,217 | 977 | New Algorithms for
2D and 3D Point Matching:
Pose Estimation and Correspondence
Steven Gold l , Chien Ping LuI, Anand Rangarajan l ,
Suguna Pappu l and Eric Mjolsness 2
Department of Computer Science
Yale University
New Haven, CT 06520-8285
Abstract
A fundamental open problem in computer vision-determining
pose and c... | 977 |@word trial:2 open:1 tried:1 decomposition:3 current:1 written:1 shape:1 enables:1 update:2 alone:1 selected:2 plane:1 beginning:1 sys:1 oblique:2 provides:1 location:1 c2:1 vjk:1 introduce:1 p8:3 expected:1 multi:1 ctan:1 discretized:1 decomposed:1 actual:1 window:1 becomes:2 estimating:1 bounded:1 moreover:1 nul... |
7,218 | 978 | Pattern Playback in the '90s
Malcolm Slaney
Interval Research Corporation
180 l-C Page Mill Road,
Palo Alto, CA 94304
malcolm@interval.com
Abstract
Deciding the appropriate representation to use for modeling human
auditory processing is a critical issue in auditory science. While engineers have successfully performed ... | 978 |@word middle:1 version:1 compression:3 inversion:45 agc:9 duda:1 cochleagram:14 instrumental:1 pulse:1 pick:1 papoulis:1 initial:5 contains:2 transfonn:2 daniel:2 interestingly:1 existing:2 recovered:3 com:1 comparing:1 yet:2 readily:1 numerical:1 designed:1 half:6 guess:2 sys:1 short:5 provides:1 mathematical:2 a... |
7,219 | 979 | Learning in large linear perceptrons and
why the thermodynamic limit is relevant
to the real world
Peter Sollich
Department of Physics, University of Edinburgh
Edinburgh EH9 3JZ, U.K.
P.Sollich~ed.ac.uk
Abstract
We present a new method for obtaining the response function 9
and its average G from which most of the pro... | 979 |@word simulation:1 tr:10 initial:2 series:4 recovered:1 readily:2 john:2 additive:1 plot:2 leaf:1 slowing:1 plane:1 isotropic:2 location:1 ron:2 simpler:1 height:2 become:2 differential:3 fitting:1 expected:1 ra:1 examine:1 ol:2 precursor:1 becomes:1 begin:1 xx:2 bounded:1 lowest:1 what:2 interpreted:2 q2:1 ag:3 f... |
7,220 | 98 | 553
SPREADING ACTIVATION OVER
DISTRIBUTED MICROFEATURES
James Hendler *
Depart.ment, of Computer Science
University of Maryland
College Park, MD 20742
ABSTRACT
One att?empt at explaining human inferencing is that of spreading activat,ion, particularly in the st.ructured connectionist paradigm. This has resulted in t.... | 98 |@word joh:1 underst:2 llsed:1 nd:5 r:1 tr:1 fif:1 ld:1 configuration:1 cru:1 att:1 charniak:2 current:1 nt:3 activation:16 import:1 must:2 john:7 cottrell:4 wellbehaved:1 hypothesize:1 designed:1 heir:1 alone:1 item:1 scienc:1 ial:2 tjw:1 cognit:1 node:14 acti:1 idr:1 cot:1 dist:5 examine:2 ry:1 simulator:1 provide... |
7,221 | 980 | Interior Point Implementations of
Alternating Minimization Training
Michael Lemmon
Dept . of Electrical Engineering
University of Notre Dame
Notre Dame, IN 46556
lemmon@maddog.ee.nd.edu
Peter T. Szymanski
Dept. of Electrical Engineering
University of Notre Dame
Notre Dame, IN 46556
pszymans@maddog.ee.nd.edu
Abstract... | 980 |@word inversion:1 nd:2 km:1 simulation:2 simplifying:1 contraction:1 jacob:2 thereby:1 solid:1 series:2 current:4 z2:2 nowlan:2 assigning:1 must:3 j1:3 update:28 pursued:2 parameterization:3 steepest:1 lr:4 nearness:1 provides:1 codebook:1 successive:8 consists:1 manner:4 examine:1 decreasing:2 solver:4 increasing... |
7,222 | 981 | Reinforcement Learning with Soft State
Aggregation
Satinder P. Singh
singh@psyche.mit.edu
Tommi Jaakkola
tommi@psyche.mit.edu
Michael I. Jordan
jordan@psyche.mit.edu
Dept. of Brain & Cognitive Sciences (E-lO)
M.I.T.
Cambridge, MA 02139
Abstract
It is widely accepted that the use of more compact representations
tha... | 981 |@word version:3 proportion:2 advantageous:1 km:3 contraction:1 pg:1 thereby:1 current:3 plot:1 update:1 stationary:1 ith:1 dissertation:1 provides:2 lx:1 ipi:1 constructed:5 prove:2 specialize:1 combine:1 eleventh:1 theoretically:1 expected:2 ra:4 planning:1 brain:1 bellman:15 discounted:1 td:11 resolve:1 increasi... |
7,223 | 982 | Coarse-to-Fine Image Search Using Neural
Networks
Clay D. Spence, John C. Pearson, and Jim Bergen
Nationallnfonnation Display Laboratory
P.O. Box 8619
Princeton, NJ 08543-8619
cspence@sarnoff.com
John_Pearson@maca.sarnoff.com
jbergen@sarnoff.com
Abstract
The efficiency of image search can be greatly improved by using ... | 982 |@word version:8 simulation:1 decomposition:1 carry:1 contains:1 tuned:1 com:4 surprising:1 must:1 finest:2 john:4 realistic:1 visible:2 blur:3 v:1 half:1 fewer:1 selected:1 discovering:1 coarse:14 location:3 sigmoidal:1 five:3 height:1 constructed:5 direct:1 become:1 lowresolution:1 qualitative:1 combine:2 burr:3 ... |
7,224 | 983 | On the Computational Utility of
Consciousness
Donald W. Mathis and Michael C. Mozer
mathis@cs.colorado.edu, mozer@cs.colorado.edu
Department of Computer Science and Institute of Cognitive Science
University of Colorado, Boulder
Boulder, CO 80309-0430
Abstract
We propose a computational framework for understanding and
... | 983 |@word illustrating:1 faculty:1 simulation:8 carry:5 moment:1 initial:1 rightmost:2 subjective:2 existing:2 current:3 contextual:1 activation:7 yet:2 must:4 subsequent:1 motor:2 interpretable:1 update:1 mental:2 coarse:1 plaut:2 provides:1 five:2 become:1 symposium:1 persistent:16 consists:3 acquired:1 roughly:1 be... |
7,225 | 984 | A Convolutional Neural Network
Hand Tracker
Steven J. Nowlan
Synaptics, Inc.
2698 Orchard Parkway
San Jose, CA 95134
nowlan@synaptics .com
John C. Platt
Synaptics, Inc.
2698 Orchard Parkway
San Jose, CA 95134
platt@synaptics.com
Abstract
We describe a system that can track a hand in a sequence of video
frames and rec... | 984 |@word hence:1 print:2 open:9 correct:1 illustrated:1 white:1 separate:2 existing:1 current:2 com:2 tracker:2 nowlan:3 image:3 differencing:1 john:2 difficult:2 tracked:1 designed:2 implementation:1 perform:2 currently:1 upper:1 ai:2 largest:1 successfully:1 rashid:1 coarse:1 variability:1 location:3 frame:24 locat... |
7,226 | 985 | Efficient Methods for Dealing with
Missing Data in Supervised Learning
Volker '!'resp?
Siemens AG
Central Research
Otto-Hahn-Ring 6
81730 Miinchen
Germany
Ralph Neuneier
Siemens AG
Central Research
Otto-Hahn-Ring 6
81730 Miinchen
Germany
Subutai Ahmad
Interval Research Corporation
1801-C Page Mill R<;l.
Palo Alto, C... | 985 |@word duda:2 seems:1 substitution:1 score:1 interestingly:1 neuneier:12 elliptical:1 dx:1 must:1 written:1 john:1 numerical:1 remove:1 treating:1 update:1 xk:6 miinchen:2 five:1 become:1 consists:4 alspector:2 tomaso:1 multi:1 window:5 increasing:1 becomes:1 alto:1 mass:1 kaufman:2 ag:2 finding:1 corporation:1 mul... |
7,227 | 986 | Grammar Learning by a Self-Organizing
Network
Michiro Negishi
Dept. of Cognitive and Neural Systems, Boston University
111 Cummington Street
Boston, MA 02215 email: negishi@cns.bu.edu
Abstract
This paper presents the design and simulation results of a selforganizing neural network which induces a grammar from example ... | 986 |@word cnn:1 version:1 selforganization:1 f32:1 bigram:1 simulation:5 reduction:2 initial:1 score:1 hereafter:1 subjective:1 current:5 contextual:2 activation:1 parsing:2 john:3 motor:1 selected:2 iso:1 record:2 accepting:1 node:6 evaluator:1 rc:10 scholtes:4 direct:2 consists:1 dan:1 acquired:5 forgetting:1 elman:... |
7,228 | 987 | Recurrent Networks:
Second Order Properties and Pruning
Morten With Pedersen and Lars Kai Hansen
CONNECT, Electronics Institute
Technical University of Denmark B349
DK-2800 Lyngby, DENMARK
emails:with.lkhansen@ei.dtu.dk
Abstract
Second order properties of cost functions for recurrent networks
are investigated. We ana... | 987 |@word manageable:1 retraining:2 orf:1 simplifying:1 invoking:2 thereby:3 electronics:1 series:8 contains:2 past:1 current:1 activation:2 si:6 visible:1 remove:1 update:2 pursued:1 keu:3 firstly:1 five:1 fitting:1 roughly:1 brain:6 inspired:1 provided:1 wki:1 panel:12 ooi:1 growth:1 unit:34 uo:1 appear:1 continuall... |
7,229 | 988 | Comparing the prediction accuracy of
artificial neural networks and other
statistical models for breast cancer
survival
Harry B. Burke
Department of Medicine
New York Medical College
Valhalla, NY 10595
David B. Rosen
Department of Medicine
New York Medical College
Valhalla, NY 10595
Philip H. Goodman
Department of M... | 988 |@word neurophysiology:1 prognostic:11 accommodate:1 reduction:1 contains:1 united:1 comparing:2 distant:1 discrimination:2 intelligence:1 selected:2 coleman:1 institution:1 math:1 node:7 seyal:2 five:5 weinstein:2 manner:1 ra:1 expected:1 proliferation:1 linearity:1 what:1 minimizes:1 psych:1 fuzzy:4 assoc:1 medic... |
7,230 | 989 | Convergence Properties of the K-Means
Algorithms
Leon Bottou
Neuristique,
28 rue des Petites Ecuries,
75010 Paris, France
leonCneuristique.fr
Yoshua Bengio"
Dept. LR.O.
Universite de Montreal
Montreal, Qc H3C-3J7, Canada
bengioyCiro.umontreal.ca
Abstract
This paper studies the convergence properties of the well know... | 989 |@word trial:1 version:4 open:2 uon:1 initial:2 contains:1 score:1 selecting:1 outperforms:2 current:1 comparing:1 nowlan:2 si:8 must:1 remove:1 update:6 une:1 lr:1 indefinitely:1 provides:1 five:2 symposium:1 prove:4 consists:3 fitting:1 fld:1 introduce:2 indeed:2 expected:1 behavior:3 ol:1 insist:1 decreasing:1 d... |
7,231 | 99 | 695
ANALOG IMPLEMENTATION OF SHUNTING
NEURAL NETWORKS
Bahram Nabet, Robert B. Darling, and Robert B. Pinter
Department of Electrical Engineering, FT-lO
University of Washington
Seattle, WA 98195
ABSTRACT
An extremely compact, all analog and fully parallel implementation of a class of shunting recurrent neural network... | 99 |@word version:1 compression:1 hippocampus:1 instruction:1 thereby:1 solid:1 electronics:1 tuned:1 suppressing:1 current:4 si:1 dx:1 readily:1 additive:2 nonsaturated:1 v:2 device:7 nervous:1 liapunov:2 iso:1 dover:1 short:4 core:1 provides:1 quantized:1 preference:2 mathematical:1 constructed:1 consists:1 overhead:... |
7,232 | 990 | Comparing the prediction accuracy of
artificial neural networks and other
statistical models for breast cancer
survival
Harry B. Burke
Department of Medicine
New York Medical College
Valhalla, NY 10595
David B. Rosen
Department of Medicine
New York Medical College
Valhalla, NY 10595
Philip H. Goodman
Department of M... | 990 |@word neurophysiology:1 version:3 polynomial:1 seems:1 prognostic:11 simulation:12 quickprop:1 jacob:2 nsw:2 accommodate:1 reduction:1 initial:1 contains:3 united:1 selecting:3 lapedes:2 imaginary:1 existing:2 comparing:2 com:2 activation:1 yet:1 assigning:1 distant:1 additive:1 numerical:1 predetermined:1 enables... |
7,233 | 991 | Stochastic Dynamics of Three-State
Neural Networks
Toru Ohira
Sony Computer Science Laboratory
3-14-13 Higashi-gotanda,
Tokyo 141, Japan
ohira@csl.sony.co.jp
Jack D. Cowan
Depts. of Mathematics and Neurology
University of Chicago
Chicago, IL 60637
cowan@synapse.uchicago.edu
Abstract
We present here an analysis of the... | 991 |@word normalized:1 briefly:1 classical:3 australian:1 evolution:1 liouville:1 ril:4 physik:1 tokyo:1 laboratory:1 simulation:9 stochastic:11 dependence:1 interacts:1 kth:1 mann:1 solid:1 moment:21 outer:5 configuration:1 transparent:1 investigation:1 past:1 reaction:1 extension:3 current:3 comparing:1 motion:1 lio... |
7,234 | 992 | Grouping Components of
?
Three-Dimensional Moving Objects In
Area MST of Visual Cortex
Richard S. Zemel
Carnegie Mellon University
Department of Psychology
Pittsburgh, PA 15213
zemel?lcmu. edu
Terrence J. Sejnowski
CNL, The Salk Institute
P.O. Box 85800
San Diego, CA 92186-5800
terry?lsalk.edu
Abstract
Many cells in ... | 992 |@word effect:1 implies:1 subpattern:2 direction:9 move:2 receptive:3 simulation:1 primary:1 contraction:1 responds:3 during:1 self:1 width:1 gradient:1 simulated:1 initial:1 evenly:1 stone:1 selecting:2 tuned:2 demonstrate:1 singularity:1 performs:1 motion:39 interpreting:1 modeled:1 considered:1 image:9 recently:... |
7,235 | 993 | Visual Speech Recognition with
Stochastic Networks
Javier R. Movellan
Department of Cognitive Science
University of California San Diego
La Jolla, Ca 92093-0515
Abstract
This paper presents ongoing work on a speaker independent visual
speech recognition system. The work presented here builds on previous
research effo... | 993 |@word trial:1 compression:1 simulation:1 tried:2 dialing:2 reduction:1 initial:1 selecting:1 past:1 current:1 si:1 numerical:3 alone:1 infant:2 half:2 beginning:1 filtered:2 provides:1 wrinkling:1 height:1 profound:1 fps:1 yuhas:2 alspector:1 themselves:1 roughly:2 audiovisual:2 automatically:1 window:1 considerin... |
7,236 | 994 | Single Transistor Learning Synapses
Paul Hasler, Chris Diorio, Bradley A. Minch, Carver Mead
California Institute of Technology
Pasadena, CA 91125
(818) 395 - 2812
paul@hobiecat.pcmp.caltech.edu
Abstract
We describe single-transistor silicon synapses that compute, learn,
and provide non-volatile memory retention. The... | 994 |@word pulse:1 thereby:3 past:1 vg2:3 bradley:5 current:41 must:6 refresh:1 analytic:1 remove:3 designed:1 drop:1 update:9 v:6 selected:1 device:7 trapping:2 iso:4 characterization:1 five:2 along:7 roughly:1 examine:2 terminal:5 decreasing:1 vfg:2 increasing:3 project:1 matched:1 underlying:1 circuit:3 substantiall... |
7,237 | 996 | Bias, Variance and the Combination of
Least Squares Estimators
Ronny Meir
Faculty of Electrical Engineering
Technion, Haifa 32000
Israel
rmeirGee.technion.ac.il
Abstract
We consider the effect of combining several least squares estimators
on the expected performance of a regression problem. Computing
the exact bias a... | 996 |@word briefly:1 faculty:1 advantageous:1 seems:2 norm:3 covariance:5 reduction:1 series:1 denoting:2 written:1 must:1 analytic:1 remove:1 implying:1 el1:1 manfred:1 along:1 direct:2 become:2 fitting:1 manner:1 indeed:1 expected:15 behavior:1 mechanic:1 multi:1 decreasing:2 considering:2 increasing:4 becomes:3 more... |
7,238 | 997 | A Real Time Clustering CMOS
Neural Engine
T. Serrano-Gotarredona, B. Linares-Barranco, and J. L. Huertas
Dept. of Analog Design, National Microelectronics Center (CNM), Ed. CICA, Av. Reina
Mercedes sIn, 41012 Sevilla, SPAIN. Phone: (34)-5-4239923, Fax: (34)-5-4624506,
E-mail: bernabe@cnm.us.es
Abstract
We describe an ... | 997 |@word version:2 arti:12 solid:2 electronics:1 configuration:1 zij:4 current:35 z2:1 must:1 zll:1 designed:1 update:3 short:1 node:5 differential:6 consists:2 microchip:1 symp:1 inside:1 expected:1 behavior:2 z13:1 spain:1 stm:10 matched:1 provided:1 circuit:13 alto:1 z:1 fabricated:2 ti:1 control:2 internally:2 or... |
7,239 | 998 | Learning direction in global motion: two
classes of psychophysically-motivated
models
V. Sundareswaran
Lucia M. Vaina*
Intelligent Systems Laboratory, College of Engineering,
Boston University
44 Cummington Street, Boston, MA 02215
Abstract
Perceptual learning is defined as fast improvement in performance and
retentio... | 998 |@word neurophysiology:1 trial:11 middle:2 judgement:4 wiesel:2 nd:4 open:1 simulation:6 dramatic:1 accommodate:6 contains:1 series:1 foveal:1 tuned:5 interestingly:1 imaginary:1 existing:1 current:6 od:1 yet:1 subsequent:2 plasticity:4 girosi:1 designed:1 selfsupervised:1 progressively:1 fund:1 discrimination:10 v... |
7,240 | 999 | Correlation and Interpolation Networks for
Real-time Expression Analysis/Synthesis.
Trevor Darrell, Irfan Essa, Alex Pentland
Perceptual Computing Group
MIT Media Lab
Abstract
We describe a framework for real-time tracking of facial expressions
that uses neurally-inspired correlation and interpolation methods. A
dist... | 999 |@word open:1 sensed:1 tr:3 shot:2 reduction:2 initial:1 score:9 animated:6 current:1 activation:8 yet:1 must:1 mesh:3 realistic:2 girosi:1 shape:2 motor:13 half:1 selected:2 core:1 provides:1 location:2 simpler:1 five:2 constructed:2 direct:1 consists:1 combine:1 polyhedral:1 indeed:1 multi:1 inspired:2 relying:1 ... |
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