Improving Random Projections Using Marginal Information
نویسندگان
چکیده
We present an improved version of random projections that takes advantage of marginal norms. Using a maximum likelihood estimator (MLE), marginconstrained random projections can improve estimation accuracy considerably. Theoretical properties of this estimator are analyzed in detail.
منابع مشابه
RANDOM PROJECTIONS Margin-constrained Random Projections And Very Sparse Random Projections
Abstract We1 propose methods for improving both the accuracy and efficiency of random projections, the popular dimension reduction technique in machine learning and data mining, particularly useful for estimating pairwise distances. Let A ∈ Rn×D be our n points in D dimensions. This method multiplies A by a random matrix R ∈ RD×k, reducing the D dimensions down to just k . R typically consists ...
متن کاملRandom Projections with Bayesian Priors
The technique of random projection is one of dimension reduction, where high dimensional vectors in RD are projected down to a smaller subspace in Rk. Certain forms of distances or distance kernels such as Euclidean distances, inner products [10], and lp distances [12] between high dimensional vectors are approximately preserved in this smaller dimensional subspace. Word vectors which are repre...
متن کاملTight Variational Bounds via Random Projections and I-Projections
Information projections are the key building block of variational inference algorithms and are used to approximate a target probabilistic model by projecting it onto a family of tractable distributions. In general, there is no guarantee on the quality of the approximation obtained. To overcome this issue, we introduce a new class of random projections to reduce the dimensionality and hence the ...
متن کاملImproving security of double random phase encoding with chaos theory using fractal images
This study presents a new method based on the combination of cryptography and information hiding methods. Firstly, the image is encoded by the Double Random Phase Encoding (DRPE) technique. The real and imaginary parts of the encoded image are subsequently embedded into an enlarged normalized host image. DRPE demands two random phase mask keys to decode the decrypted image at the destination. T...
متن کاملNew Outer Bounds on the Marginal Polytope
We give a new class of outer bounds on the marginal polytope, and propose a cutting-plane algorithm for efficiently optimizing over these constraints. When combined with a concave upper bound on the entropy, this gives a new variational inference algorithm for probabilistic inference in discrete Markov Random Fields (MRFs). Valid constraints on the marginal polytope are derived through a series...
متن کامل