检索结果-内蒙古大学图书馆

您好，读者！请登录

内蒙古大学图书馆

首页
概况
党建
资源
服务
科研支持
- 论文收录引用证明
- 科技查新
知识产权
档案馆
帮助

咨询与建议

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

您的常用邮箱：*

您的手机号码：*

问题描述：

当前已输入0个字，您还可以输入200个字

全部搜索
期刊论文
图书
学位论文
标准
纸本馆藏
外文资源发现
数据库导航
超星发现

高级检索

时间限定

出版年份：

文献类型

图书期刊文献学位论文多媒体

馆藏选择

电子馆藏纸本馆藏

核心期刊

全部期刊 SCI 收录期刊 SSCI 收录期刊 EI 收录期刊 CSCD 收录期刊 CSSCI 收录期刊

语言

中文英文

文献类型

期刊文献图书学位论文标准纸本馆藏

帮助

文字说明：

T=题名（书名、题名），A=作者（责任者），K=主题词，P=出版物名称，PU=出版社名称，O=机构（作者单位、学位授予单位、专利申请人），L=中图分类号，C=学科分类号，U=全部字段，Y=年（出版发行年、学位年度、标准发布年）

检索规则说明：

AND代表“并且”；OR代表“或者”；NOT代表“不包含”；(注意必须大写,运算符两边需空一格)

检索范例：

范例一：(K=图书馆学 OR K=情报学) AND A=范并思 AND Y=1982-2016
范例二：P=计算机应用与软件 AND (U=C++ OR U=Basic) NOT K=Visual AND Y=2011-2016

分类表

所选分类

>> <<

限定检索结果

文献类型

109 篇 会议

馆藏范围

109 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

60 篇 工学
- 57 篇 电气工程
- 57 篇 计算机科学与技术...
- 4 篇 软件工程
- 2 篇 信息与通信工程
- 1 篇 力学（可授工学、理...
- 1 篇 光学工程
- 1 篇 材料科学与工程（可...
- 1 篇 电子科学与技术（可...
- 1 篇 建筑学
- 1 篇 土木工程
5 篇 理学
- 4 篇 物理学
- 2 篇 数学
- 1 篇 统计学（可授理学、...
2 篇 管理学
- 2 篇 图书情报与档案管...
1 篇 法学
- 1 篇 社会学

主题

22 篇 machine learning
20 篇 training
12 篇 deep learning
11 篇 task analysis
9 篇 neural networks
7 篇 feature extracti...
7 篇 image reconstruc...
5 篇 reinforcement le...
5 篇 sparse matrices
5 篇 dictionaries
5 篇 optimization
5 篇 computational mo...
5 篇 array signal pro...
5 篇 data models
4 篇 estimation
4 篇 sensors
4 篇 convolutional ne...
3 篇 support vector m...
3 篇 mimo communicati...
3 篇 generative adver...

机构

2 篇 department of el...
2 篇 nyu dept elect &...
2 篇 univ cent florid...
2 篇 colorado state u...
2 篇 department of el...
1 篇 penn state univ ...
1 篇 university of pi...
1 篇 electrical & com...
1 篇 uppsala univ dep...
1 篇 czech academy of...
1 篇 univ montreal fa...
1 篇 laboratoire mia ...
1 篇 univ mons numedi...
1 篇 tech univ denmar...
1 篇 univ montreal fa...
1 篇 aalto university...
1 篇 univ carlos iii ...
1 篇 univ copenhagen ...
1 篇 uppsala univ sig...
1 篇 department infor...

作者

2 篇 gabbouj moncef
2 篇 sarkka simo
2 篇 nazanin rahnavar...
2 篇 moncef gabbouj
2 篇 goldberger jacob
2 篇 nikolaos passali...
2 篇 quanyan zhu
2 篇 zhu quanyan
2 篇 passalis nikolao...
2 篇 rahnavard nazani...
1 篇 simon godsill
1 篇 yinghui zhao
1 篇 prato m.
1 篇 lee kiwon
1 篇 bouilly delphine
1 篇 dupont stephane
1 篇 bruce a. bassett
1 篇 wiegand thomas
1 篇 ford gabriel
1 篇 chris j. finlay

语言

109 篇 英文

检索条件"任意字段=29th IEEE International Workshop on Machine Learning for Signal Processing, MLSP 2019"

共 109 条记录，以下是1-10 订阅

全选清除本页清除全部题录导出标记到"检索档案"

详细简洁

排序：

2019 ieee 29th international workshop on machine learning for signal processing, mlsp 2019

2019 IEEE 29th International Workshop on Machine Learning fo...

引用

29th ieee international workshop on machine learning for signal processing, mlsp 2019

ISBN: (纸本)9781728108247

the proceedings contain 98 papers. the topics discussed include: optimal pricing in black box producer-consumer Stackelberg games using revealed preference feedback;learning warm-start points for AC optimal power flow;minimax active learning via minimal model capacity;multi-step chord sequence prediction based on aggregated multi-scale encoder-decoder networks;robust hybrid beamforming with quantized deep neural networks;a machine learning approach for classifying faults in microgrids using wavelet decomposition;robust importance-weighted cross-validation under sample selection bias;interpretable online banking fraud detection based on hierarchical attention mechanism;and a benchmark study of backdoor data poisoning defenses for deep neural network classifiers and a novel defense.

关键词：

来源：评论

学校读者我要写书评

暂无评论

A NEW APPROACH TO ONLINE REGRESSION BASED ON MAXIMUM CORRENTROPY CRITERION 29

A NEW APPROACH TO ONLINE REGRESSION BASED ON MAXIMUM CORRENT...

引用

ieee 29th international workshop on machine learning for signal processing (mlsp)

作者： Bahraini, Sajjad Tuncel, Ertern Univ Calif Riverside Dept Elect & Comp Engn Riverside CA 92521 USA

ISBN: (纸本)9781728108247

the problem of linear adaptive filtering (or equivalently, online regression) in the presence of non-Gaussian noise is addressed. One efficient way in face of environments with non-Gaussian noise is to employ information theoretic criteria such as correntropy. In this study, a new algorithm based on correntropy is proposed, and demonstrated to outperform previous works in terms of both convergence speed and steady-state misalignment. At the same time, the proposed algorithm benefits from lower computational complexity compared to some of these algorithms.

关键词： Information theoretic learning maximum correntropy criterion adaptive filtering online regression non-Gaussian noise

来源：评论

学校读者我要写书评

暂无评论

LARGE-SCALE SPARSE SUBSPACE CLUSTERING USING LANDMARKS 29

LARGE-SCALE SPARSE SUBSPACE CLUSTERING USING LANDMARKS

引用

ieee 29th international workshop on machine learning for signal processing (mlsp)

作者： Pourkarnali-Anaraki, Farhad Univ Massachusetts Lowell Dept Comp Sci Lowell MA 01854 USA

ISBN: (纸本)9781728108247

Subspace clustering methods based on expressing each data point as a linear combination of all other points in a dataset are popular unsupervised learning techniques. However, existing methods incur high computational complexity on large-scale datasets as they require solving an expensive optimization problem and performing spectral clustering on large affinity matrices. this paper presents an efficient approach to sub-space clustering by selecting a small subset of the input data called landmarks. the resulting subspace clustering method in the reduced domain runs in linear time with respect to the size of the original data. Numerical experiments on synthetic and real data demonstrate the effectiveness of our method.

关键词： Unsupervised learning subspace clustering large-scale data landmark selection computational cost

来源：评论

学校读者我要写书评

暂无评论

REJECTION-SAMPLING-BASED ANCESTOR SAMPLING FOR PARTICLE GIBBS 29

REJECTION-SAMPLING-BASED ANCESTOR SAMPLING FOR PARTICLE GIBB...

引用

ieee 29th international workshop on machine learning for signal processing (mlsp)

作者： Hostettler, Roland Sarkka, Simo Uppsala Univ Dept Engn Sci Uppsala Finland Aalto Univ Dept Elect Engn & Automat Espoo Finland

ISBN: (纸本)9781728108247

Particle Gibbs with ancestor sampling is an efficient and statistically principled algorithm for learning of dynamic systems. However, the ancestor sampling step used to improve mixing of the Markov chain requires the possibly expensive calculation of a set of ancestor weights for the complete particle system. In this paper, we propose a rejection-sampling-based algorithm for ancestor sampling in particle Gibbs that mitigates this problem. Additionally, performance guarantees and a fallback strategy to prevent suffering from high rejection rates are discussed. the performance of the method is illustrated in two numerical examples.

关键词： Particle Markov chain Monte Carlo particle filters statistical learning

来源：评论

学校读者我要写书评

暂无评论

GENERIC BOUNDS ON thE MAXIMUM DEVIATIONS IN SEQUENTIAL PREDICTION: AN INFORMATION-thEORETIC ANALYSIS 29

GENERIC BOUNDS ON THE MAXIMUM DEVIATIONS IN SEQUENTIAL PREDI...

引用

ieee 29th international workshop on machine learning for signal processing (mlsp)

作者： Fang, Song Zhu, Quanyan NYU Dept Elect & Comp Engn New York NY 10003 USA

ISBN: (纸本)9781728108247

In this paper, we derive generic bounds on the maximum deviations in prediction errors for sequential prediction via an information-theoretic approach. the fundamental bounds are shown to depend only on the conditional entropy of the data point to be predicted given the previous data points. In the asymptotic case, the bounds are achieved if and only if the prediction error is white and uniformly distributed.

关键词： Information-theoretic learning sequential learning sequential prediction bounds on performance sequence prediction

来源：评论

学校读者我要写书评

暂无评论

REGULARIZED STATE ESTIMATION AND PARAMETER learning VIA AUGMENTED LAGRANGIAN KALMAN SMOOthER MEthOD 29

REGULARIZED STATE ESTIMATION AND PARAMETER LEARNING VIA AUGM...

引用

ieee 29th international workshop on machine learning for signal processing (mlsp)

作者： Gao, Rui Tronarp, Filip Zhao, Zheng Sarkka, Simo Aalto Univ Dept Elect Engn & Automat Rakentajanaukio 2C Espoo Finland

ISBN: (纸本)9781728108247

In this article, we address the problem of estimating the state and learning of the parameters in a linear dynamic system with generalized L-1-regularization. Assuming a sparsity prior on the state, the joint state estimation and parameter learning problem is cast as an unconstrained optimization problem. However, when the dimensionality of state or parameters is large, memory requirements and computation of learning algorithms are generally prohibitive. Here, we develop a new augmented Lagrangian Kalman smoother method for solving this problem, where the primal variable update is reformulated as Kalman smoother. the effectiveness of the proposed method for state estimation and parameter learning is demonstrated in spectro-temporal estimation tasks using both synthetic and real data.

关键词： state estimation parameter learning sparsity Kalman smoother augmented Lagrangian method

来源：评论

学校读者我要写书评

暂无评论

learning WARM-START POINTS FOR AC OPTIMAL POWER FLOW 29

LEARNING WARM-START POINTS FOR AC OPTIMAL POWER FLOW

引用

ieee 29th international workshop on machine learning for signal processing (mlsp)

作者： Baker, Kyri Univ Colorado Boulder CO 80309 USA

ISBN: (纸本)9781728108247

A large amount of data has been generated by grid operators solving AC optimal power flow (ACOPF) throughout the years, and we explore how leveraging this data can be used to help solve future ACOPF problems. We use this data to train a Random Forest to predict solutions of future ACOPF problems. To preserve correlations and relationships between predicted variables, we utilize a multi-target approach to learn approximate voltage and generation solutions to ACOPF problems directly by only using network loads, without the knowledge of other network parameters or the system topology. We explore the benefits of using the learned solution as an intelligent warm start point for solving the ACOPF, and the proposed framework is evaluated numerically using multiple ieee test networks. the benefit of using learned ACOPF solutions is shown to be solver and network dependent, but shows promise for quickly finding approximate solutions to the ACOPF problem.

关键词： Electric load flow

来源：评论

学校读者我要写书评

暂无评论

INTERPRETABLE ONLINE BANKING FRAUD DETECTION BASED ON HIERARCHICAL ATTENTION MECHANISM 29

INTERPRETABLE ONLINE BANKING FRAUD DETECTION BASED ON HIERAR...

引用

ieee 29th international workshop on machine learning for signal processing (mlsp)

作者： Achituve, Idan Kraus, Sarit Goldberger, Jacob Bar Ilan Univ IL-52100 Ramat Gan Israel

ISBN: (纸本)9781728108247

Online banking activities are constantly growing and are likely to become even more common as digital banking platforms evolve. One side effect of this trend is the rise in attempted fraud. However, there is very little work in the literature on online banking fraud detection. We propose an attention based architecture for classifying online banking transactions as either fraudulent or genuine. the proposed method allows transparency to its decision by identifying the most important transactions in the sequence and the most informative features in each transaction. Experiments conducted on a large dataset of real online banking data demonstrate the effectiveness of the method in terms of both classification accuracy and interpretability of the results.

关键词： deep learning attention interpretability Online banking fraud detection

来源：评论

学校读者我要写书评

暂无评论

A DEEP NETWORK FOR SINGLE-SNAPSHOT DIRECTION OF ARRIVAL ESTIMATION 29

A DEEP NETWORK FOR SINGLE-SNAPSHOT DIRECTION OF ARRIVAL ESTI...

引用

ieee 29th international workshop on machine learning for signal processing (mlsp)

作者： Ozanich, Emma Gerstoft, Peter Niu, Haiqiang Univ Calif San Diego Scripps Inst Oceanog La Jolla CA 92093 USA Chinese Acad Sci Inst Acoust Beijing 100190 Peoples R China

ISBN: (纸本)9781728108247

this paper examines a deep feedforward network for beamforming with the single-snapshot sample covariance matrix (SCM). the conventional beamforming formulation, typically quadratic in the complex weight space, is reformulated as real and linear in the weight covariance and SCM. the reformulated SCMs are used as input to a deep feed-forward neural network (FNN) for two source localization. Simlations demonstrate the effect of source incoherence and performance in a noisy tracking example. the FNN beamformer is experimentally tested on the Swellex96 experiment S95 source tow with a loud interferer.

关键词： feedforward network deep learning beamforming array processing

来源：评论

学校读者我要写书评

暂无评论

EFFICIENT PRE-DESIGNED CONVOLUTIONAL FRONT-END FOR DEEP learning 29

EFFICIENT PRE-DESIGNED CONVOLUTIONAL FRONT-END FOR DEEP LEAR...

引用

ieee 29th international workshop on machine learning for signal processing (mlsp)

作者： Baali, Hamza Bouzerdoum, Abdesselam Hamad Bin Khalifs Univ Coll Sci & Engn Div Informat & Comp Technol Doha Qatar Univ Wollongong Sch Elect Comp & Telecommun Engn Wollongong NSW Australia

ISBN: (纸本)9781728108247

this paper introduces a hierarchical learning paradigm based on a predesigned directional filter bank front-end analogous to the energy model for complex cells. the filter bank front-end is designed to extract common primitive features such as orientations and edges. Each energy response is subjected to a shunting inhibition operator to enhance contrast and reduce the effects of illumination variations. this is followed by a divisive-normalization, which bounds the responses of the feature maps. the normalized responses are then propagated through a two-layer convolutional neural network (CNN) back-end for classification. the efficiency of the proposed approach is demonstrated using the CIFAR-10 dataset, and its performance is compared against that of the DTCWT ScaterNet front-end.

关键词： Convolutional neural network directional filters Energy model

来源：评论

学校读者我要写书评

暂无评论

没有更多数据了...

全选清除本页清除全部题录导出标记到“检索档案”

共11页 << < 1 2 3 4 5 6 7 8 9 10 > >>

检索报告对象比较合并检索0

隐藏清空

合并搜索

回到顶部

执行限定条件

内容：

评分：

请选择保存的检索档案：

请选择收藏分类：

订阅名称：

通借通还

温馨提示：

图书名称：

借书校区：

取书校区：

手机号码：

邮箱地址：

一卡通帐号：

电话和邮箱必须正确填写，我们会与您联系确认。

联系人：

所在院系：

联系邮箱：

联系电话：

内蒙古自治区呼和浩特市赛罕区大学西街235号邮编: 010021

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：