378 Result(s)
within
**ze Shen
English
Machine Learning
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Article
Discovery as autonomous learning from the environment
Discovery involves collaboration among many intelligent activities. However, little is known about how and in what form such collaboration occurs. In this article, a framework is proposed for autonomous system...
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Article
Discovery as Autonomous Learning from the Environment
Discovery involves collaboration among many intelligent activities. However, little is known about how and in what form such collaboration occurs. In this article, a framework is proposed for autonomous system...
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Article
Sampling With Prolate Spheroidal Wave Functions
The prolate spheroidal wave functions (PSWFs) are used in sampling of bandlimited signals. Several formulae based on integer values of these PSWFs are derived and used to replace the sinc function in sampling ...
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Article
Mining Skewed and Sparse Transaction Data for Personalized Shop** Recommendation
A good shop** recommender system can boost sales in a retailer store. To provide accurate recommendation, the recommender needs to accurately predict a customer's preference, an ability difficult to acquire....
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Article
Structural Extension to Logistic Regression: Discriminative Parameter Learning of Belief Net Classifiers
Bayesian belief nets (BNs) are often used for classification tasks—typically to return the most likely class label for each specified instance. Many BN-learners, however, attempt to find the BN that maximizes a d...
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Article
Ranking and Reranking with Perceptron
This work is inspired by the so-called reranking tasks in natural language processing. In this paper, we first study the ranking, reranking, and ordinal regression algorithms proposed recently in the context o...
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Article
Feature selection via sensitivity analysis of SVM probabilistic outputs
Feature selection is an important aspect of solving data-mining and machine-learning problems. This paper proposes a feature-selection method for the Support Vector Machine (SVM) learning. Like most feature-s...
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Article
A collaborative filtering framework based on both local user similarity and global user similarity
Collaborative filtering as a classical method of information retrieval has been widely used in hel** people to deal with information overload. In this paper, we introduce the concept of local user similarity...
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Article
Periodic step-size adaptation in second-order gradient descent for single-pass on-line structured learning
It has been established that the second-order stochastic gradient descent (SGD) method can potentially achieve generalization performance as well as empirical optimum in a single pass through the training exam...
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Article
An empirical study on image bag generators for multi-instance learning
Multi-instance learning (MIL) has been widely used on diverse applications involving complicated data objects such as images, where people use a bag generator to represent an original data object as a bag of inst...
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Article
Online optimization for max-norm regularization
The max-norm regularizer has been extensively studied in the last decade as it promotes an effective low-rank estimation for the underlying data. However, such max-norm regularized problems are typically formu...
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Chapter and Conference Paper
Intrusion Detection Using Temporal Convolutional Networks
Intrusion detection system is an important network security facility. With the fast development of information technology, the information security is getting more serious. On the other side, making the IT equ...
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Chapter and Conference Paper
Adversarial Domain Adaptation for Chinese Semantic Dependency Graph Parsing
The Chinese Semantic Dependency Graph (CSDG) Parsing reveals the deep and fine-grained semantic relationship of Chinese sentences, and the parsing results have a great help to the downstream NLP tasks. However...
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Chapter and Conference Paper
Learnable Gabor Convolutional Networks
Commonly used convolutional operation does not have the ability to learn invariant information of images. However, some handcrafted image feature extractors, like Gabor wavelets, are robust to object’s scale ...
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Chapter and Conference Paper
Massive-Scale Models of Urban Infrastructure and Populations
As the world becomes more dense, connected, and complex, it is increasingly difficult to answer “what-if” questions about our cities and populations. Most modeling and simulation tools struggle with scale and ...
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Chapter and Conference Paper
Robust Segmentation of Nucleus in Histopathology Images via Mask R-CNN
Nuclei segmentation plays an import role in histopathology images analysis. Deep learning approaches have shown its strength for histopathology images processing in various studies. In this paper, we proposed ...
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Chapter and Conference Paper
Automatic Brain Tumor Segmentation with Domain Adaptation
Deep convolution neural networks, in particular, the encoder-decoder networks, have been extensively used in image segmentation. We develop a deep learning approach for tumor segmentation by combining a modifi...
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Chapter and Conference Paper
An Expert Validation Framework for Improving the Quality of Crowdsourced Clustering
Crowdclustering is a cost-effective mechanism that learns a cluster structure from data and crowdsourced human pairwise labels. Though some initial efforts have shown some effectiveness of crowdclustering, per...
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Chapter and Conference Paper
Dynamic Placement Algorithm for Multiple Classes of Mobile Base Stations in Public Safety Networks
As new mobile base stations (mBSs) have been constantly developed with various capacities, mobile coverage, and mobility models, the level of heterogeneity in public safety networks (PSNs) has been increasing
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Chapter and Conference Paper
A Hybrid Chain Based Incentive Mechanism for Resource Leasing in NDN
Since the main feature of Named Data Network (NDN) is in-net caching, it is crucial to motivate users to offer resource such as bandwidth and storage. However, few research works on incentive mechanism design ...
