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Mining useful clusters from high dimensional data has received significant attention of the computer vision and pattern recognition community in the recent years. Linear and non-linear dimensionality reduction has played an important role to overcome the c ...

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Energy Efficient Collaborative Beamforming in Wireless Sensor Networks

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Monopulse Beam Synthesis Using a Sparse Single Layer of Weights

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Global Identification of Kinetic Parameters via the Extent-based Incremental Approach

Exact Algorithms for $ L ^{ 1 } $ -TV Regularization of Real-Valued or Circle-Valued Signals

Multilinear Low-Rank Tensors on Graphs & Applications

Fast Robust PCA on Graphs

A new mathematical representation of demand using choice-based optimization method

Rigorous optimization recipes for sparse and low rank inverse problems with applications in data sciences

Path-following gradient-based decomposition algorithms for separable convex optimization

PURIFY: A new algorithmic framework for next-generation radio-interferometric imaging

Energy Efficient Collaborative Beamforming in Wireless Sensor Networks

Dictionary learning over large distributed models via dual-ADMM strategies

Global Identification of Kinetic Parameters via the Extent-based Incremental Approach

Exact Algorithms for $ L ^{ 1 } $ -TV Regularization of Real-Valued or Circle-Valued Signals

Fast Robust PCA on Graphs

Rigorous optimization recipes for sparse and low rank inverse problems with applications in data sciences

Energy Efficient Collaborative Beamforming in Wireless Sensor Networks

A new mathematical representation of demand using choice-based optimization method

Multilinear Low-Rank Tensors on Graphs & Applications

Path-following gradient-based decomposition algorithms for separable convex optimization

PURIFY: A new algorithmic framework for next-generation radio-interferometric imaging

Dictionary learning over large distributed models via dual-ADMM strategies