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» Universal Sparse Modeling
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CORR
2007
Springer
111views Education» more  CORR 2007»
15 years 23 days ago
Capacity of Sparse Multipath Channels in the Ultra-Wideband Regime
—This paper studies the ergodic capacity of time- and frequency-selective multipath fading channels in the ultrawideband (UWB) regime when training signals are used for channel e...
Vasanthan Raghavan, Gautham Hariharan, Akbar M. Sa...
106
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ICCV
2011
IEEE
14 years 24 days ago
Informative Feature Selection for Object Recognition via Sparse PCA
Bag-of-words (BoW) methods are a popular class of object recognition methods that use image features (e.g., SIFT) to form visual dictionaries and subsequent histogram vectors to r...
Nikhil Naikal, Allen Y. Yang, S. Shankar Sastry
97
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HVC
2007
Springer
108views Hardware» more  HVC 2007»
15 years 7 months ago
How Fast and Fat Is Your Probabilistic Model Checker? An Experimental Performance Comparison
Abstract. This paper studies the efficiency of several probabilistic model checkers by comparing verification times and peak memory usage for a set of standard case studies. The s...
David N. Jansen, Joost-Pieter Katoen, Marcel Olden...
83
Voted
NIPS
2007
15 years 2 months ago
Predictive Matrix-Variate t Models
It is becoming increasingly important to learn from a partially-observed random matrix and predict its missing elements. We assume that the entire matrix is a single sample drawn ...
Shenghuo Zhu, Kai Yu, Yihong Gong
KDD
2008
ACM
259views Data Mining» more  KDD 2008»
16 years 1 months ago
Using ghost edges for classification in sparsely labeled networks
We address the problem of classification in partially labeled networks (a.k.a. within-network classification) where observed class labels are sparse. Techniques for statistical re...
Brian Gallagher, Hanghang Tong, Tina Eliassi-Rad, ...