12321641
Locally Balanced Incremental Hierarchical Discriminant Regression
Incremental hierarchical discriminant regression faces several challenging issues: (a) a large input space with a small output space and (b) nonstationary statistics of data sequences. In the first case (a), there maybe few distinct labels in the output space while the input data distribute in a high dimensional space. In the second case (b), a tree has to be grown when only a limited data sequence has been observed. In this paper, we present the Locally Balanced Incremental Hierarchical Discriminant Regression (LBIHDR) algorithm. A novel node self-organization and spawning strategy is proposed to generate a more discriminant subspace by forming multiple clusters for one class. The algorithm was successfully applied to different kinds of data set.
27213248
Multiresolution recognition of offline handwritten Chinese characters with wavelet transform
The authors propose a novel multiresolution recognition scheme for handwritten Chinese character recognition in which an input pattern is recognized by adopting the coefficients of the wavelet transforms. It is known that wavelet representation provides a coarse-to-fine strategy. The recognition starts from the coarse scale and moves to the finer scales. After preprocessing, the wavelet transform is applied to the kanji image. Then, we make use of the coefficients with the lowest resolution to select 50 candidates from 3755 categories. In order to enhance the statistical feature of a character, we used statistical methods to reconstruct features in fine classification. With the proposed recognition system, experiments are performed on the 863 Testing System. The correct rate reaches 80.56%, which is a promising result.
30724966
Motivational System for Human-Robot Interaction
Human-Robot Interaction (HRI) has recently drawn increased attention. Robots can not only passively receive information but also actively emit actions. We present a motivational system for human-robot interaction. The motivational system signals the occurrence of salient sensory inputs, modulates the mapping from sensory inputs to action outputs, and evaluates candidate actions. No salient feature is predefined in the motivational system but instead novelty based on experience, which is applicable to any task. Novelty is defined as an innate drive. Reinforcer is integrated with novelty. Thus, the motivational system of a robot can be developed through interactions with trainers. We treat vision-based neck action selection as a behavior guided by the motivational system. The experimental results are consistent with the attention mechanism in human infants.
16444798
Finding Similar Patterns in Microarray Data
In this paper we propose a clustering algorithm called s-Cluster for analysis of gene expression data based on pattern-similarity. The algorithm captures the tight clusters exhibiting strong similar expression patterns in Microarray data,and allows a high level of overlap among discovered clusters without completely grouping all genes like other algorithms. This reflects the biological fact that not all functions are turned on in an experiment, and that many genes are co-expressed in multiple groups in response to different stimuli. The experiments have demonstrated that the proposed algorithm successfully groups the genes with strong similar expression patterns and that the found clusters are interpretable.
16107199
Fast Rectangular Matrix Multiplication and Applications
First we study asymptotically fast algorithms for rectangular matrix multiplication. We begin with new algorithms for multiplication of ann?nmatrix by ann?n2matrix in arithmetic timeO(n?),?=3.333953?, which is less by 0.041 than the previous record 3.375477?. Then we present fast multiplication algorithms for matrix pairs of arbitrary dimensions, estimate the asymptotic running time as a function of the dimensions, and optimize the exponents of the complexity estimates. For a large class of input matrix pairs, we improve the known exponents. Finally we show three applications of our results: (a)we decrease from 2.851 to 2.837 the known exponent of the work bounds for fast deterministic (NC) parallel evaluation of the determinant, the characteristic polynomial, and the inverse of ann?nmatrix, as well as for the solution to a nonsingular linear system ofnequations, (b)we asymptotically accelerate the known sequential algorithms for the univariate polynomial composition modxn, yielding the complexity boundO(n1.667) versus the old record ofO(n1.688), and for the univariate polynomial factorization over a finite field, and (c)we improve slightly the known complexity estimates for computing basic solutions to the linear programming problem withmconstraints andnvariables.
2832131
Applying Data Mining to Pseudo-Relevance Feedback for High Performance Text Retrieval
In this paper, we investigate the use of data mining, in particular the text classification and co-training techniques, to identify more relevant passages based on a small set of labeled passages obtained from the blind feedback of a retrieval system. The data mining results are used to expand query terms and to re-estimate some of the parameters used in a probabilistic weighting function. We evaluate the data mining based feedback method on the TREC HARD data set. The results show that data mining can be successfully applied to improve the text retrieval performance. We report our experimental findings in detail.
17235430
A generalized global alignment algorithm
MOTIVATION
Homologous sequences are sometimes similar over some regions but different over other regions. Homologous sequences have a much lower global similarity if the different regions are much longer than the similar regions.


RESULTS
We present a generalized global alignment algorithm for comparing sequences with intermittent similarities, an ordered list of similar regions separated by different regions. A generalized global alignment model is defined to handle sequences with intermittent similarities. A dynamic programming algorithm is designed to compute an optimal general alignment in time proportional to the product of sequence lengths and in space proportional to the sum of sequence lengths. The algorithm is implemented as a computer program named GAP3 (Global Alignment Program Version 3). The generalized global alignment model is validated by experimental results produced with GAP3 on both DNA and protein sequences. The GAP3 program extends the ability of standard global alignment programs to recognize homologous sequences of lower similarity.


AVAILABILITY
The GAP3 program is freely available for academic use at http://bioinformatics.iastate.edu/aat/align/align.html.
37047287
A SoPC Architecture of MIMO Sphere Decoder for Mobile Communications