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Academy of Mathematics and Systems Science, CAS Colloquia & Seminars：Robust Generalization Requires Exponentially Large Models
鲁棒泛化 指数级大 模型
2023/5/15
It is well-known that modern neural networks are vulnerable to adversarial examples. To mitigate this problem, a series of robust learning algorithms have been proposed. However, although the robust t...
Decomposition Methods for Large Scale LP Decoding
LP Decoding Alternating Direction Method of Multipliers Information Theory
2012/4/18
When binary linear error-correcting codes are used over symmetric channels, a relaxed version of the maximum likelihood decoding problem can be stated as a linear program (LP). This LP decoder can be ...
Efficient variational inference in large-scale Bayesian compressed sensing
large-scale Bayesian variational inference Computer Vision and Pattern Recognition
2011/10/9
Abstract: We study linear models under heavy-tailed priors from a probabilistic viewpoint. Instead of computing a single sparse most probable (MAP) solution as in standard deterministic approaches, th...
Achieving "Massive MIMO" Spectral Efficiency with a Not-so-Large Number of Antennas
Channel training downlink scheduling frequency reuse inter-cell cooperation large-system analysis
2011/9/15
Abstract: The main focus and contribution of this paper is a novel network-MIMO TDD architecture that achieves spectral efficiencies comparable with "Massive MIMO", with one order of magnitude fewer a...
Distributed SIR-Aware Scheduling in Large-Scale Wireless Networks
Distributed SIR-Aware Large-Scale Wireless Networks Information Theory
2011/8/31
Abstract: Opportunistic scheduling and routing can in principle greatly increase the throughput of decentralized wireless networks, but to be practical they must do so with small amounts of timely sid...
Local failure detection and diagnosis in large sensor networks
diagnosis large sensor networks Information Theory
2011/8/29
Abstract: In this article, the joint fluctuations of the extreme eigenvalues and eigenvectors of a large dimensional sample covariance matrix are analyzed when the associated population covariance mat...
Projection-Pursuit Based Principal Component Analysis: a Large Sample Theory
Dispersion matrices eigenvalues and eigenvectors empirical processes principal component analysis projection pursuit (PP)
2007/12/10
摘要 The principal component analysis (PCA) is one of the most celebrated methods in analysing multivariate data. An effort of extending PCA is projection pursuit (PP), a more general class of dimension...
Stability Analysis for the Large-Scale Systems with Time-Delay
Large-scale time-delay system Lyapunov functional partial decomposition method Razumikhin-type theorem
2007/8/7
The stability analysis problems were put forward for the large-scale systems with time-delay by using the partial decomposition method. With the stability of the isolated subsystems without time-delay...
期刊信息
篇名
Double-Local-Symmetric-Integral Iterative Learning Control for Dynamics in Steady-state Optimization of Large-scale Industrial Processes with Delay
语种
英文
撰写或编译
撰写
作者
阮小娥,李换琴,万百五
第一作者单位
西安交通大学
...