Robust boosting algorithm against mislabeling in multiclass problems.

Abstract:

:We discuss robustness against mislabeling in multiclass labels for classification problems and propose two algorithms of boosting, the normalized Eta-Boost.M and Eta-Boost.M, based on the Eta-divergence. Those two boosting algorithms are closely related to models of mislabeling in which the label is erroneously exchanged for others. For the two boosting algorithms, theoretical aspects supporting the robustness for mislabeling are explored. We apply the proposed two boosting methods for synthetic and real data sets to investigate the performance of these methods, focusing on robustness, and confirm the validity of the proposed methods.

journal_name

Neural Comput

journal_title

Neural computation

authors

Takenouchi T,Eguchi S,Murata N,Kanamori T

doi

10.1162/neco.2007.11-06-400

subject

Has Abstract

pub_date

2008-06-01 00:00:00

pages

1596-630

issue

6

eissn

0899-7667

issn

1530-888X

journal_volume

20

pub_type

信件
  • Why Does Large Batch Training Result in Poor Generalization? A Comprehensive Explanation and a Better Strategy from the Viewpoint of Stochastic Optimization.

    abstract::We present a comprehensive framework of search methods, such as simulated annealing and batch training, for solving nonconvex optimization problems. These methods search a wider range by gradually decreasing the randomness added to the standard gradient descent method. The formulation that we define on the basis of th...

    journal_title:Neural computation

    pub_type: 杂志文章

    doi:10.1162/neco_a_01089

    authors: Takase T,Oyama S,Kurihara M

    更新日期:2018-07-01 00:00:00

  • Pattern generation by two coupled time-discrete neural networks with synaptic depression.

    abstract::Numerous animal behaviors, such as locomotion in vertebrates, are produced by rhythmic contractions that alternate between two muscle groups. The neuronal networks generating such alternate rhythmic activity are generally thought to rely on pacemaker cells or well-designed circuits consisting of inhibitory and excitat...

    journal_title:Neural computation

    pub_type: 杂志文章

    doi:10.1162/089976698300017449

    authors: Senn W,Wannier T,Kleinle J,Lüscher HR,Müller L,Streit J,Wyler K

    更新日期:1998-07-01 00:00:00

  • Higher-order statistics of input ensembles and the response of simple model neurons.

    abstract::Pairwise correlations among spike trains recorded in vivo have been frequently reported. It has been argued that correlated activity could play an important role in the brain, because it efficiently modulates the response of a postsynaptic neuron. We show here that a neuron's output firing rate critically depends on t...

    journal_title:Neural computation

    pub_type: 杂志文章

    doi:10.1162/089976603321043702

    authors: Kuhn A,Aertsen A,Rotter S

    更新日期:2003-01-01 00:00:00

  • Distributed control of uncertain systems using superpositions of linear operators.

    abstract::Control in the natural environment is difficult in part because of uncertainty in the effect of actions. Uncertainty can be due to added motor or sensory noise, unmodeled dynamics, or quantization of sensory feedback. Biological systems are faced with further difficulties, since control must be performed by networks o...

    journal_title:Neural computation

    pub_type: 杂志文章

    doi:10.1162/NECO_a_00151

    authors: Sanger TD

    更新日期:2011-08-01 00:00:00

  • How precise is neuronal synchronization?

    abstract::Recent work suggests that synchronization of neuronal activity could serve to define functionally relevant relationships between spatially distributed cortical neurons. At present, it is not known to what extent this hypothesis is compatible with the widely supported notion of coarse coding, which assumes that feature...

    journal_title:Neural computation

    pub_type: 杂志文章

    doi:10.1162/neco.1995.7.3.469

    authors: König P,Engel AK,Roelfsema PR,Singer W

    更新日期:1995-05-01 00:00:00

  • The Deterministic Information Bottleneck.

    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

    pub_type: 杂志文章

    doi:10.1162/NECO_a_00961

    authors: Strouse DJ,Schwab DJ

    更新日期:2017-06-01 00:00:00

  • Changes in GABAB modulation during a theta cycle may be analogous to the fall of temperature during annealing.

    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

    pub_type: 杂志文章

    doi:10.1162/089976698300017539

    authors: Sohal VS,Hasselmo ME

    更新日期:1998-05-15 00:00:00

  • Physiological gain leads to high ISI variability in a simple model of a cortical regular spiking cell.

    abstract::To understand the interspike interval (ISI) variability displayed by visual cortical neurons (Softky & Koch, 1993), it is critical to examine the dynamics of their neuronal integration, as well as the variability in their synaptic input current. Most previous models have focused on the latter factor. We match a simple...

    journal_title:Neural computation

    pub_type: 杂志文章

    doi:10.1162/neco.1997.9.5.971

    authors: Troyer TW,Miller KD

    更新日期:1997-07-01 00:00:00

  • Machine Learning: Deepest Learning as Statistical Data Assimilation Problems.

    abstract::We formulate an equivalence between machine learning and the formulation of statistical data assimilation as used widely in physical and biological sciences. The correspondence is that layer number in a feedforward artificial network setting is the analog of time in the data assimilation setting. This connection has b...

    journal_title:Neural computation

    pub_type: 杂志文章

    doi:10.1162/neco_a_01094

    authors: Abarbanel HDI,Rozdeba PJ,Shirman S

    更新日期:2018-08-01 00:00:00

  • Computing sparse representations of multidimensional signals using Kronecker bases.

    abstract::Recently there has been great interest in sparse representations of signals under the assumption that signals (data sets) can be well approximated by a linear combination of few elements of a known basis (dictionary). Many algorithms have been developed to find such representations for one-dimensional signals (vectors...

    journal_title:Neural computation

    pub_type: 杂志文章

    doi:10.1162/NECO_a_00385

    authors: Caiafa CF,Cichocki A

    更新日期:2013-01-01 00:00:00

  • Robust Closed-Loop Control of a Cursor in a Person with Tetraplegia using Gaussian Process Regression.

    abstract::Intracortical brain computer interfaces can enable individuals with paralysis to control external devices through voluntarily modulated brain activity. Decoding quality has been previously shown to degrade with signal nonstationarities-specifically, the changes in the statistics of the data between training and testin...

    journal_title:Neural computation

    pub_type: 杂志文章

    doi:10.1162/neco_a_01129

    authors: Brandman DM,Burkhart MC,Kelemen J,Franco B,Harrison MT,Hochberg LR

    更新日期:2018-11-01 00:00:00

  • Synchrony of neuronal oscillations controlled by GABAergic reversal potentials.

    abstract::GABAergic synapse reversal potential is controlled by the concentration of chloride. This concentration can change significantly during development and as a function of neuronal activity. Thus, GABA inhibition can be hyperpolarizing, shunting, or partially depolarizing. Previous results pinpointed the conditions under...

    journal_title:Neural computation

    pub_type: 杂志文章

    doi:10.1162/neco.2007.19.3.706

    authors: Jeong HY,Gutkin B

    更新日期:2007-03-01 00:00:00

  • Multispike interactions in a stochastic model of spike-timing-dependent plasticity.

    abstract::Recently we presented a stochastic, ensemble-based model of spike-timing-dependent plasticity. In this model, single synapses do not exhibit plasticity depending on the exact timing of pre- and postsynaptic spikes, but spike-timing-dependent plasticity emerges only at the temporal or synaptic ensemble level. We showed...

    journal_title:Neural computation

    pub_type: 杂志文章

    doi:10.1162/neco.2007.19.5.1362

    authors: Appleby PA,Elliott T

    更新日期:2007-05-01 00:00:00

  • Neutral stability, rate propagation, and critical branching in feedforward networks.

    abstract::Recent experimental and computational evidence suggests that several dynamical properties may characterize the operating point of functioning neural networks: critical branching, neutral stability, and production of a wide range of firing patterns. We seek the simplest setting in which these properties emerge, clarify...

    journal_title:Neural computation

    pub_type: 杂志文章

    doi:10.1162/NECO_a_00461

    authors: Cayco-Gajic NA,Shea-Brown E

    更新日期:2013-07-01 00:00:00

  • On the slow convergence of EM and VBEM in low-noise linear models.

    abstract::We analyze convergence of the expectation maximization (EM) and variational Bayes EM (VBEM) schemes for parameter estimation in noisy linear models. The analysis shows that both schemes are inefficient in the low-noise limit. The linear model with additive noise includes as special cases independent component analysis...

    journal_title:Neural computation

    pub_type: 杂志文章

    doi:10.1162/0899766054322991

    authors: Petersen KB,Winther O,Hansen LK

    更新日期:2005-09-01 00:00:00

  • Design of charge-balanced time-optimal stimuli for spiking neuron oscillators.

    abstract::In this letter, we investigate the fundamental limits on how the interspike time of a neuron oscillator can be perturbed by the application of a bounded external control input (a current stimulus) with zero net electric charge accumulation. We use phase models to study the dynamics of neurons and derive charge-balance...

    journal_title:Neural computation

    pub_type: 杂志文章

    doi:10.1162/NECO_a_00643

    authors: Dasanayake IS,Li JS

    更新日期:2014-10-01 00:00:00

  • Parsing Complex Sentences with Structured Connectionist Networks.

    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

    pub_type: 杂志文章

    doi:10.1162/neco.1991.3.1.110

    authors: Jain AN

    更新日期:1991-04-01 00:00:00

  • An oscillatory Hebbian network model of short-term memory.

    abstract::Recurrent neural architectures having oscillatory dynamics use rhythmic network activity to represent patterns stored in short-term memory. Multiple stored patterns can be retained in memory over the same neural substrate because the network's state persistently switches between them. Here we present a simple oscillat...

    journal_title:Neural computation

    pub_type: 杂志文章

    doi:10.1162/neco.2008.02-08-715

    authors: Winder RK,Reggia JA,Weems SA,Bunting MF

    更新日期:2009-03-01 00:00:00

  • On the performance of voltage stepping for the simulation of adaptive, nonlinear integrate-and-fire neuronal networks.

    abstract::In traditional event-driven strategies, spike timings are analytically given or calculated with arbitrary precision (up to machine precision). Exact computation is possible only for simplified neuron models, mainly the leaky integrate-and-fire model. In a recent paper, Zheng, Tonnelier, and Martinez (2009) introduced ...

    journal_title:Neural computation

    pub_type: 杂志文章

    doi:10.1162/NECO_a_00112

    authors: Kaabi MG,Tonnelier A,Martinez D

    更新日期:2011-05-01 00:00:00

  • Universal approximation depth and errors of narrow belief networks with discrete units.

    abstract::We generalize recent theoretical work on the minimal number of layers of narrow deep belief networks that can approximate any probability distribution on the states of their visible units arbitrarily well. We relax the setting of binary units (Sutskever & Hinton, 2008 ; Le Roux & Bengio, 2008 , 2010 ; Montúfar & Ay, 2...

    journal_title:Neural computation

    pub_type: 信件

    doi:10.1162/NECO_a_00601

    authors: Montúfar GF

    更新日期:2014-07-01 00:00:00

  • Locality of global stochastic interaction in directed acyclic networks.

    abstract::The hypothesis of invariant maximization of interaction (IMI) is formulated within the setting of random fields. According to this hypothesis, learning processes maximize the stochastic interaction of the neurons subject to constraints. We consider the extrinsic constraint in terms of a fixed input distribution on the...

    journal_title:Neural computation

    pub_type: 杂志文章

    doi:10.1162/089976602760805368

    authors: Ay N

    更新日期:2002-12-01 00:00:00

  • Spiking neural P systems with weights.

    abstract::A variant of spiking neural P systems with positive or negative weights on synapses is introduced, where the rules of a neuron fire when the potential of that neuron equals a given value. The involved values-weights, firing thresholds, potential consumed by each rule-can be real (computable) numbers, rational numbers,...

    journal_title:Neural computation

    pub_type: 杂志文章

    doi:10.1162/NECO_a_00022

    authors: Wang J,Hoogeboom HJ,Pan L,Păun G,Pérez-Jiménez MJ

    更新日期:2010-10-01 00:00:00

  • Discrete states of synaptic strength in a stochastic model of spike-timing-dependent plasticity.

    abstract::A stochastic model of spike-timing-dependent plasticity (STDP) postulates that single synapses presented with a single spike pair exhibit all-or-none quantal jumps in synaptic strength. The amplitudes of the jumps are independent of spiking timing, but their probabilities do depend on spiking timing. By making the amp...

    journal_title:Neural computation

    pub_type: 杂志文章

    doi:10.1162/neco.2009.07-08-814

    authors: Elliott T

    更新日期:2010-01-01 00:00:00

  • Kernels for longitudinal data with variable sequence length and sampling intervals.

    abstract::We develop several kernel methods for classification of longitudinal data and apply them to detect cognitive decline in the elderly. We first develop mixed-effects models, a type of hierarchical empirical Bayes generative models, for the time series. After demonstrating their utility in likelihood ratio classifiers (a...

    journal_title:Neural computation

    pub_type: 杂志文章

    doi:10.1162/NECO_a_00164

    authors: Lu Z,Leen TK,Kaye J

    更新日期:2011-09-01 00:00:00

  • Parameter Identifiability in Statistical Machine Learning: A Review.

    abstract::This review examines the relevance of parameter identifiability for statistical models used in machine learning. In addition to defining main concepts, we address several issues of identifiability closely related to machine learning, showing the advantages and disadvantages of state-of-the-art research and demonstrati...

    journal_title:Neural computation

    pub_type: 杂志文章

    doi:10.1162/NECO_a_00947

    authors: Ran ZY,Hu BG

    更新日期:2017-05-01 00:00:00

  • Similarity, connectionism, and the problem of representation in vision.

    abstract::A representational scheme under which the ranking between represented similarities is isomorphic to the ranking between the corresponding shape similarities can support perfectly correct shape classification because it preserves the clustering of shapes according to the natural kinds prevailing in the external world. ...

    journal_title:Neural computation

    pub_type: 杂志文章,评审

    doi:10.1162/neco.1997.9.4.701

    authors: Edelman S,Duvdevani-Bar S

    更新日期:1997-05-15 00:00:00

  • State-Space Representations of Deep Neural Networks.

    abstract::This letter deals with neural networks as dynamical systems governed by finite difference equations. It shows that the introduction of k -many skip connections into network architectures, such as residual networks and additive dense n...

    journal_title:Neural computation

    pub_type: 杂志文章

    doi:10.1162/neco_a_01165

    authors: Hauser M,Gunn S,Saab S Jr,Ray A

    更新日期:2019-03-01 00:00:00

  • A Mathematical Analysis of Memory Lifetime in a Simple Network Model of Memory.

    abstract::We study the learning of an external signal by a neural network and the time to forget it when this network is submitted to noise. The presentation of an external stimulus to the recurrent network of binary neurons may change the state of the synapses. Multiple presentations of a unique signal lead to its learning. Th...

    journal_title:Neural computation

    pub_type: 杂志文章

    doi:10.1162/neco_a_01286

    authors: Helson P

    更新日期:2020-07-01 00:00:00

  • A bio-inspired, computational model suggests velocity gradients of optic flow locally encode ordinal depth at surface borders and globally they encode self-motion.

    abstract::Visual navigation requires the estimation of self-motion as well as the segmentation of objects from the background. We suggest a definition of local velocity gradients to compute types of self-motion, segment objects, and compute local properties of optical flow fields, such as divergence, curl, and shear. Such veloc...

    journal_title:Neural computation

    pub_type: 杂志文章

    doi:10.1162/NECO_a_00479

    authors: Raudies F,Ringbauer S,Neumann H

    更新日期:2013-09-01 00:00:00

  • Modeling slowly bursting neurons via calcium store and voltage-independent calcium current.

    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

    pub_type: 杂志文章

    doi:10.1162/neco.1996.8.5.951

    authors: Chay TR

    更新日期:1996-07-01 00:00:00