Investigating Bi-Level Optimization for Learning and Vision From a Unified Pe…

Bi-Level Optimization (BLO) is originated from the area of economic game theory and then introduced into the optimization community. BLO is able to handle problems with a hierarchical structure, in…

A Novel Approach to Large-Scale Dynamically Weighted Directed Network Represe…

A d ynamically w eighted d irected n etwork (DWDN) is frequently encountered in various big data-related applications like a terminal interaction pattern analysis system (TIPAS) concerned in this s…

Robust Low-Tubal-Rank Tensor Recovery From Binary Measurements

Low-rank tensor recovery (LRTR) is a natural extension of low-rank matrix recovery (LRMR) to high-dimensional arrays, which aims to reconstruct an underlying tensor X from incomplete linear measure…

Plenty is Plague : Fine-Grained Learning for Visual Question Answering

Visual Question Answering (VQA) has attracted extensive research focus recently. Along with the ever-increasing data scale and model complexity, the enormous training cost has become an emerging ch…

Ball kk-Means : Fast Adaptive Clustering With No Bounds

This paper presents a novel accelerated exact k -means called as “Ball k -means” by using the ball to describe each cluster, which focus on reducing the point-centroid distance computation. The…

Few-Example Object Detection with Model Communication

Decomposition-Based Evolutionary Multiobjective Optimization to Self-Paced Le…

Kronecker-Basis-Representation Based Tensor Sparsity and Its Applications to …

Robust Online Matrix Factorization for Dynamic Background Subtraction

Active Self-Paced Learning for Cost-Effective and Progressive Face Identifica…