Incremental active learning for optimal generalization.

abstract：:A neurocomputational model based on emergent massively overlapping neural cell assemblies (CAs) for resolving prepositional phrase (PP) attachment ambiguity is described. PP attachment ambiguity is a well-studied task in natural language processing and is a case where semantics is used to determine the syntactic struc...

journal_title：Neural computation

authors： Nadh K,Huyck C

更新日期：2012-07-01 00:00:00

abstract：:Lossy compression and clustering fundamentally involve a decision about which features are relevant and which are not. The information bottleneck method (IB) by Tishby, Pereira, and Bialek ( 1999 ) formalized this notion as an information-theoretic optimization problem and proposed an optimal trade-off between throwin...

journal_title：Neural computation

authors： Strouse DJ,Schwab DJ

更新日期：2017-06-01 00:00:00

abstract：:Natural gradient learning is known to be efficient in escaping plateau, which is a main cause of the slow learning speed of neural networks. The adaptive natural gradient learning method for practical implementation also has been developed, and its advantage in real-world problems has been confirmed. In this letter, w...

journal_title：Neural computation

authors： Park H,Murata N,Amari S

更新日期：2004-02-01 00:00:00

abstract：:In this work, we discuss practical methods for the assessment, comparison, and selection of complex hierarchical Bayesian models. A natural way to assess the goodness of the model is to estimate its future predictive capability by estimating expected utilities. Instead of just making a point estimate, it is important ...

journal_title：Neural computation

authors： Vehtari A,Lampinen J

更新日期：2002-10-01 00:00:00

abstract：:Pharmacologically isolated GABAergic irregular spiking and stuttering interneurons in the mouse visual cortex display highly irregular spike times, with high coefficients of variation approximately 0.9-3, in response to a depolarizing, constant current input. This is in marked contrast to cortical pyramidal cells, whi...

journal_title：Neural computation

authors： Englitz B,Stiefel KM,Sejnowski TJ

更新日期：2008-01-01 00:00:00

abstract：:We explicitly analyze the trajectories of learning near singularities in hierarchical networks, such as multilayer perceptrons and radial basis function networks, which include permutation symmetry of hidden nodes, and show their general properties. Such symmetry induces singularities in their parameter space, where t...

journal_title：Neural computation

authors： Wei H,Zhang J,Cousseau F,Ozeki T,Amari S

更新日期：2008-03-01 00:00:00

abstract：:This article presents new procedures for multisite spatiotemporal neuronal data analysis. A new statistical model - the diffusion model - is considered, whose parameters can be estimated from experimental data thanks to mean-field approximations. This work has been applied to optical recording of the guinea pig's audi...

journal_title：Neural computation

authors： François O,Abdallahi LM,Horikawa J,Taniguchi I,Hervé T

更新日期：2000-08-01 00:00:00

abstract：:A single-layered Hough transform network is proposed that accepts image coordinates of each object pixel as input and produces a set of outputs that indicate the belongingness of the pixel to a particular structure (e.g., a straight line). The network is able to learn adaptively the parametric forms of the linear segm...

journal_title：Neural computation

authors： Basak J

更新日期：2001-03-01 00:00:00

abstract：:A modular, recurrent connectionist network is taught to incrementally parse complex sentences. From input presented one word at a time, the network learns to do semantic role assignment, noun phrase attachment, and clause structure recognition, for sentences with both active and passive constructions and center-embedd...

journal_title：Neural computation

authors： Jain AN

更新日期：1991-04-01 00:00:00

abstract：:A study of a general central pattern generator (CPG) is carried out by means of a measure of the gain of information between the number of available topology configurations and the output rhythmic activity. The neurons of the CPG are chaotic Hindmarsh-Rose models that cooperate dynamically to generate either chaotic o...

journal_title：Neural computation

authors： Stiesberg GR,Reyes MB,Varona P,Pinto RD,Huerta R

更新日期：2007-04-01 00:00:00

abstract：:This letter proposes a multichannel source separation technique, the multichannel variational autoencoder (MVAE) method, which uses a conditional VAE (CVAE) to model and estimate the power spectrograms of the sources in a mixture. By training the CVAE using the spectrograms of training examples with source-class label...

journal_title：Neural computation

authors： Kameoka H,Li L,Inoue S,Makino S

更新日期：2019-09-01 00:00:00

abstract：:Changes in GABA modulation may underlie experimentally observed changes in the strength of synaptic transmission at different phases of the theta rhythm (Wyble, Linster, & Hasselmo, 1997). Analysis demonstrates that these changes improve sequence disambiguation by a neural network model of CA3. We show that in the fra...

journal_title：Neural computation

authors： Sohal VS,Hasselmo ME

更新日期：1998-05-15 00:00:00

abstract：:Knowledge of synaptic input is crucial for understanding synaptic integration and ultimately neural function. However, in vivo, the rates at which synaptic inputs arrive are high, so that it is typically impossible to detect single events. We show here that it is nevertheless possible to extract the properties of the ...

journal_title：Neural computation

authors： Puggioni P,Jelitai M,Duguid I,van Rossum MCW

更新日期：2017-07-01 00:00:00

abstract：:The past decade has seen a rise of interest in Laplacian eigenmaps (LEMs) for nonlinear dimensionality reduction. LEMs have been used in spectral clustering, in semisupervised learning, and for providing efficient state representations for reinforcement learning. Here, we show that LEMs are closely related to slow fea...

journal_title：Neural computation

authors： Sprekeler H

更新日期：2011-12-01 00:00:00

abstract：:A minimal model is presented to explain changes in frequency, shape, and amplitude of Ca2+ oscillations in the neuroendocrine melanotrope cell of Xenopus Laevis. It describes the cell as a plasma membrane oscillator with influx of extracellular Ca2+ via voltage-gated Ca2+ channels in the plasma membrane. The Ca2+ osci...

journal_title：Neural computation

authors： Cornelisse LN,Scheenen WJ,Koopman WJ,Roubos EW,Gielen SC

更新日期：2001-01-01 00:00:00

abstract：:A general method is presented to classify temporal patterns generated by rhythmic biological networks when synaptic connections and cellular properties are known. The method is discrete in nature and relies on algebraic properties of state transitions and graph theory. Elements of the set of rhythms generated by a net...

journal_title：Neural computation

authors： Roberts PD

更新日期：1998-10-01 00:00:00

abstract：:The Hebbian paradigm is perhaps the best-known unsupervised learning theory in connectionism. It has inspired wide research activity in the artificial neural network field because it embodies some interesting properties such as locality and the capability of being applicable to the basic weight-and-sum structure of ne...

journal_title：Neural computation

authors： Fiori S

更新日期：2005-04-01 00:00:00

abstract：:We consider learning a causal ordering of variables in a linear nongaussian acyclic model called LiNGAM. Several methods have been shown to consistently estimate a causal ordering assuming that all the model assumptions are correct. But the estimation results could be distorted if some assumptions are violated. In thi...

journal_title：Neural computation

authors： Tashiro T,Shimizu S,Hyvärinen A,Washio T

更新日期：2014-01-01 00:00:00

abstract：:This article studies a general theory of estimating functions of independent component analysis when the independent source signals are temporarily correlated. Estimating functions are used for deriving both batch and on-line learning algorithms, and they are applicable to blind cases where spatial and temporal probab...

journal_title：Neural computation

authors： Amari S

更新日期：2000-09-01 00:00:00

abstract：:The statistical dependencies that independent component analysis (ICA) cannot remove often provide rich information beyond the linear independent components. It would thus be very useful to estimate the dependency structure from data. While such models have been proposed, they have usually concentrated on higher-order...

journal_title：Neural computation

authors： Sasaki H,Gutmann MU,Shouno H,Hyvärinen A

更新日期：2017-11-01 00:00:00

abstract：:Characterizing neural spiking activity as a function of intrinsic and extrinsic factors is important in neuroscience. Point process models are valuable for capturing such information; however, the process of fully applying these models is not always obvious. A complete model application has four broad steps: specifica...

journal_title：Neural computation

authors： Sarma SV,Nguyen DP,Czanner G,Wirth S,Wilson MA,Suzuki W,Brown EN

更新日期：2011-11-01 00:00:00

abstract：:As neural activity is transmitted through the nervous system, neuronal noise degrades the encoded information and limits performance. It is therefore important to know how information loss can be prevented. We study this question in the context of neural population codes. Using Fisher information, we show how informat...

journal_title：Neural computation

authors： Renart A,van Rossum MC

更新日期：2012-02-01 00:00:00

abstract：:Recent experiments indicate that the calcium store (e.g., endoplasmic reticulum) is involved in electrical bursting and [Ca2+]i oscillation in bursting neuronal cells. In this paper, we formulate a mathematical model for bursting neurons, which includes Ca2+ in the intracellular Ca2+ stores and a voltage-independent c...

journal_title：Neural computation

authors： Chay TR

更新日期：1996-07-01 00:00:00

abstract：:Many neurons that initially respond to a stimulus stop responding if the stimulus is presented repeatedly but recover their response if a different stimulus is presented. This phenomenon is referred to as stimulus-specific adaptation (SSA). SSA has been investigated extensively using oddball experiments, which measure...

journal_title：Neural computation

authors： Mill R,Coath M,Wennekers T,Denham SL

更新日期：2011-02-01 00:00:00

abstract：:In the past decade the importance of synchronized dynamics in the brain has emerged from both empirical and theoretical perspectives. Fast dynamic synchronous interactions of an oscillatory or nonoscillatory nature may constitute a form of temporal coding that underlies feature binding and perceptual synthesis. The re...

journal_title：Neural computation

authors： Chawla D,Lumer ED,Friston KJ

更新日期：1999-08-15 00:00:00

abstract：:In this letter, we examine a general method of approximation, known as the Kikuchi approximation method, for finding the marginals of a product distribution, as well as the corresponding partition function. The Kikuchi approximation method defines a certain constrained optimization problem, called the Kikuchi problem,...

journal_title：Neural computation

authors： Pakzad P,Anantharam V

更新日期：2005-08-01 00:00:00

abstract：:We study a model of the cortical macrocolumn consisting of a collection of inhibitorily coupled minicolumns. The proposed system overcomes several severe deficits of systems based on single neurons as cerebral functional units, notably limited robustness to damage and unrealistically large computation time. Motivated ...

journal_title：Neural computation

authors： Lücke J,von der Malsburg C

更新日期：2004-03-01 00:00:00

abstract：:The visual systems of many mammals, including humans, are able to integrate the geometric information of visual stimuli and perform cognitive tasks at the first stages of the cortical processing. This is thought to be the result of a combination of mechanisms, which include feature extraction at the single cell level ...

journal_title：Neural computation

authors： Cocci G,Barbieri D,Citti G,Sarti A

更新日期：2015-06-01 00:00:00

abstract：:Humans learn categories of complex objects quickly and from a few examples. Random projection has been suggested as a means to learn and categorize efficiently. We investigate how random projection affects categorization by humans and by very simple neural networks on the same stimuli and categorization tasks, and how...

journal_title：Neural computation

authors： Arriaga RI,Rutter D,Cakmak M,Vempala SS

更新日期：2015-10-01 00:00:00

abstract：:In a previous article, we considered game trees as graphical models. Adopting an evaluation function that returned a probability distribution over values likely to be taken at a given position, we described how to build a model of uncertainty and use it for utility-directed growth of the search tree and for deciding o...

journal_title：Neural computation

authors： Baum EB,Smith WD

更新日期：1999-01-01 00:00:00