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Academy of Mathematics and Systems Science, CAS Colloquia & Seminars：Estimating Factor-Based Spot Volatility Matrices with Noisy and Asynchronous High-Frequency Data
噪声 异步高频 数据估算 因子 现货波动率 矩阵
2023/5/4
With noisy and asynchronous high-frequency data collected for an ultra-large number of assets, we estimate high-dimensional spot volatility matrices satisfying a low-rank plus sparse structure. A loca...
GENERALIZED SPARSE SIGNAL MIXING MODEL AND APPLICATION TO NOISY BLIND SOURCE SEPARATION
GENERALIZED SPARSE SIGNAL MIXING MODEL NOISY BLIND SOURCE SEPARATION
2015/9/29
Sparse constraints on signal decompositions are justified bytypical sensor data used in a variety of signal processing fields such as acoustics, medical imaging, or wireless, but moreover can lead to ...
Matrix Completion from Noisy Entries
matrix completion low-rank matrices spectral methods manifold optimization
2015/8/21
Given a matrix M of low-rank, we consider the problem of reconstructing it from noisy observations of a small, random subset of its entries. The problem arises in a variety of applications, from colla...
Localization from Incomplete Noisy Distance Measurements
Noise the measurement the sensor network localization nuclear magnetic resonance protein conformation
2015/8/20
We consider the problem of positioning a cloud of points in the Euclidean space R d, using noisy measurements of a subset of pairwise distances. This task has applications in various areas, such as se...
Orthogonal Matching Pursuit with Noisy and Missing Data: Low and High Dimensional Results
Orthogonal Matching Pursuit Noisy and Missing Data High Dimensional Results Statistics Theory
2012/6/21
Many models for sparse regression typically assume that the covariates are known completely, and without noise. Particularly in high-dimensional applications, this is often not the case. This paper de...
Laplace deconvolution with noisy observations
adaptivity kernel estimation minimax rates Volterra equation Laplace convolution
2011/9/6
Abstract: In the present paper we consider Laplace deconvolution on the basis of discrete noisy data observed on the interval which length may increase with a sample size. Although this problem arises...
Noisy channel coding via privacy amplification and information reconciliation
Noisy channel coding privacy amplification information reconciliation
2011/3/3
We show that optimal protocols for noisy channel coding of public or private information over either classical or quantum channels can be directly constructed from two more primitive information-theor...
On the Stability of Swarm Consensus Under Noisy Control
Adaptation and Self-Organizing Systems (nlin.AO) Multiagent Systems (cs.MA)
2010/11/10
Representation of a swarm of independent robotic agents under graph-theoretic constructs allows for more formal analysis of convergence properties. We consider the local and global convergence behavio...
On Reliability Function of BSC with Noisy Feedback
Reliability Function BSC with Noisy Feedback
2010/11/15
For information transmission a binary symmetric channel is used. There is also another noisy binary symmetric channel (feedback channel), and the transmitter observes without delay all the outputs of...
We consider the effect of Gaussian white noise on fast-slow dynamical systems with one fast and two slow variables, containing a folded-node singularity. In the absence of noise, these systems are kn...
Near-Oracle Performance of Greedy Block-Sparse Estimation Techniques from Noisy Measurements
Near-Oracle Performance Greedy Block-Sparse Estimation Techniques Noisy Measurements
2010/11/30
This paper examines the ability of greedy algorithms to estimate a block sparse parameter vector from noisy measurements.In particular, block sparse versions of the orthogonal
matching pursuit and th...
Uniqueness transition in noisy phase retrieval
Uniqueness transition noisy phase retrieval
2010/12/16
Previous criteria for the feasibility of reconstructing phase information from intensity measurements, both in x-ray crystallography and more recently in coherent x-ray imaging, have been based on the...
Fast detection of nonlinearity in short and noisy time series
nonlinearity nonstationarity time series
2010/4/1
We introduce a statistical method to detect nonlinearity and nonstationarity in time series, that works even for short sequences and in presence of noise. We test speed and discrimination power of the...