Sentences with phrase «inference algorithms»
The company has already developed proof - of - deep - learning - training and proof - of - inference algorithms.
http://www.cryptomorrow.com/
In particular, I look to develop fast deterministic / stochastic inference algorithms for large - scale and / or high dimensional problems.
I obtained my PhD degree in 2008 under the supervision of Prof. Bert Kappen in the SNN / Machine Learning group on the subject of approximate inference algorithms and Bayesian graphical models for genetic linkage analysis (Radboud University).
Next, he borrowed an inference algorithm from IBM's Tokyo research lab and set about fine - tuning it to work in Nairobi.
Sudderth and his team devised an efficient inference algorithm that can scan incoming data to find events that likely represent an actual seismic signal.
Not exact matches
Expertise is necessary to make sense of all the data: no computer algorithm can substitute for a deep understanding of the subject matter, nor can it replace sound causal inference.
Nowadays everyone in this field is pushing some kind of logical deduction system, genetic algorithm system, statistical inference system, or a neural network — none of which are making much progress because they're fairly simple.
The inference results then trigger a planning algorithm that attempts to solve the task.
It performed about as well as its competing AI algorithms on most types of questions, but it really shined on so - called inference questions: «Lily is a Swan.
His research interests include brain decoding, learning algorithms for diffusion MRI data, joint analysis of multiple neuroimaging data sources, active learning and Bayesian inference.
Using the maximum and minimum inference of each variable's linguistic definition (A1 (n),..., n (n)-RRB-, the fuzzy rule - based algorithms were constructed so that each variable was expressed in terms of the number of species (B1 (n),..., n (n)-RRB- of each geographic location (E1 (n..., n),..., E7 (n,..., n)-RRB-.
I've recently been reading David MacKay's 2003 book, Information Theory, Inference, and Learning Algorithms.
And as I wrote, seemingly minor changes in the details of the statistical algorithm (long memory model of natural variation vs short memory model; p = 0.01 instead of p = 0.10 [with its well - known high type 1 error rate in settings of multiple testing]-RRB- produce dramatically different inferences based on the time series of summary statistics.
The tweet made me buy the book «Information Theory, Inference, and Learning Algorithm's» that David MacKay wrote a few years back.
As to how ROSS has the capacity to draw inferences and formulate hypotheses, the answer, says Arruda, «is a very complicated process that uses hundreds of different algorithms».
Once enough data has built up in the browser, Google's algorithm can make inferences on what you might be looking for based on the other websites you've visited.
Algorithms also can't engage in what Marcus calls «open - ended inference,» which entails bringing background knowledge to bear on a question.
Applied LRP algorithm on wafer images to draw useful inferences on what the network learnt and the training data.