February 2017 S M T W T F S « Sep 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 Pages
 1bit measurements Bregman iteration classification clustering compressed sensing computer vision conical hull problem convex optimization dimension reduction DivideandConquer elastic net fast algorithm fast SVD feature selection fixed point continuation game greedy search group sparsity Hamming Compressed Sensing iterative thresholding Kmeans latent variable model lowrank manifold learning matrix completion matrix factorization multilabel learning Ncut Nesterov's method NIPS 2011 Nonnegative Matrix Factorization optimization Quantization recovery randomized optimization robust principal component analysis SDP Separable assumption sparse learning Spectral clustering structured learning SVM
ClustrMaps

What’s new
 List of Submodular Optimization on Streaming Data (In Update)
 DivideandConquer Learning by Anchoring a Conical Hull
 Multitask Copula – A semiparametric joint prediction model for multiple outputs with sparse graph structure
 NeSVM (Nesterov’s method for SVM) code for our ICDM 2010 paper
 AISTATS 2013 GreBsmo code is released
Articles
Tag Archives: Quantization recovery
Compressed Labeling: An important extension of Hamming Compressed Sensing; at NIPS now
We are just informed that our submission “Compressed Labeling (CL) on Distilled Labelsets (DL) for Multilabel Learning” is accepted by Machine Learning Journal (Springer). Online first PDF can be downloaded here. CL is an important application and extension of Hamming … Continue reading
Hamming Compressed Sensingrecovering kbit quantization from 1bit measurements with linear noniterative algorithm
We developed a new compressed sensing type signal acquisition paradigm called “Hamming Compressed Sensing (HCS)” to recover signal’s kbit quantization rather than itself. Directly recovering quantization is much more preferred in practical digital systems. HCS provides a linear, noniterative quantization … Continue reading
Posted in Tianyi's work
Tagged 1bit measurements, compressed sensing, fast algorithm, Quantization recovery
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