Tight Data-Robust Bounds to Mutual Information Combining Shuffling and Model Selection Techniques
نویسندگان
چکیده
منابع مشابه
Tight Data-Robust Bounds to Mutual Information Combining Shuffling and Model Selection Techniques
The estimation of the information carried by spike times is crucial for a quantitative understanding of brain function, but it is difficult because of an upward bias due to limited experimental sampling. We present new progress, based on two basic insights, on reducing the bias problem. First, we show that by means of a careful application of data-shuffling techniques, it is possible to cancel ...
متن کاملBounds on mutual information for simple codes using information combining
For coded transmission over a memoryless channel, two kinds of mutual information are considered: the mutual information between a code symbol and its noisy observation and the overall mutual information between encoder input and decoder output. The overall mutual information is interpreted as a combination of the mutual informations associated with the individual code symbols. Thus, exploiting...
متن کاملRobust Feature Selection by Mutual Information Distributions
Mutual information is widely used in artificial intelligence, in a descriptive way, to measure the stochastic dependence of discrete random variables. In order to address questions such as the reliability of the empirical value, one must consider sample-to-population inferential approaches. This paper deals with the distribution of mutual information, as obtained in a Bayesian framework by a se...
متن کاملData-Robust Tight Lower Bounds to the Information Carried by Spike Times of a Neuronal Population
We develop new data-robust lower-bound methods to quantify the information carried by the timing of spikes emitted by neuronal populations. These methods have better sampling properties and are tighter than previous bounds based on neglecting correlation in the noise entropy. Our new lower bounds are precise also in the presence of strongly correlated firing. They are not precise only if correl...
متن کاملTight RMR Lower Bounds for Mutual Exclusion
We investigate the remote memory references (RMRs) complexity of deterministic processes that communicate by reading and writing shared memory in asynchronous cache-coherent and distributed shared-memory multiprocessors. We define a class of algorithms that we call order encoding. By applying information-theoretic arguments, we prove that every order encoding algorithm, shared by n processes, h...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Neural Computation
سال: 2007
ISSN: 0899-7667,1530-888X
DOI: 10.1162/neco.2007.19.11.2913