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The problem of estimating causal relationships from purely observational data is studied in this paper. We observe samples from a pair of random variables (X,Y) and wish to estimate whether X causes Y or Y causes X. Any joint distribution can be factored as pX,Y = pX pY|X = pY pX|Y and therefore the “causal” direction cannot be inferred from the joint distribution without further assumptions. In this...
We consider the problem of diluting common randomness from correlated observations by separated agents. This problem creates a new framework to study statistical privacy, in which a legitimate party, Alice, has access to a random variable X, whereas an attacker, Bob, has access to a random variable Y dependent on X drawn from a joint distribution pX,Y. Alice's goal is to produce a non-trivial function...
Speech intelligibility prediction of noisy and processed noisy speech is important in a number of application domains such as hearing instruments and forensics. Most available objective intelligibility measures employ either a signal-to-noise ratio (SNR)-based or correlation-based comparison between frequency bands of the clean and the processed speech. In this paper, we approach the speech intelligibility...
Motivated by questions in lossy data compression and by theoretical considerations, the problem of estimating the rate-distortion function of an unknown (not necessarily discrete-valued) source from empirical data is examined. The focus is the behavior of the so-called ldquoplug-inrdquo estimator, which is simply the rate-distortion function of the empirical distribution of the observed data. Sufficient...
In this paper we present a new method of compensating for complex multipath channel fading in blind multiuser detection for DS-CDMA communication. This compensation allows for the use of different chip pulse shapes. The compensation is based on the incorporation of priors derived from the FFT of the pulse shape. The system employs detectors that incorporate methods of independent component analysis...
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