Relevance feedback (RF) is an iterative process, which refines the retrievals by utilizing the user's feedback on previously retrieved results. Traditional RF techniques solel...
Peng-Yeng Yin, Bir Bhanu, Kuang-Cheng Chang, Anlei...
Reinforcement learning policies face the exploration versus exploitation dilemma, i.e. the search for a balance between exploring the environment to find profitable actions while t...
Clustering is a central unsupervised learning task with a wide variety of applications. Not surprisingly, there exist many clustering algorithms. However, unlike classification ta...
Link prediction is a fundamental problem in social network analysis and modern-day commercial applications such as Facebook and Myspace. Most existing research approaches this pro...
This paper introduces a new algorithm, namely the EquiCorrelation Network (ECON), to perform supervised classification, and regression. ECON is a kernelized LARS-like algorithm, b...
Manuel Loth, Philippe Preux, Samuel Delepoulle, Ch...