Most of supervised learning algorithms assume the stability of the target concept over time. Nevertheless in many real-user modeling systems, where the data is collected over an ex...
This paper proposes a method to recover the embedding
of the possible shapes assumed by a deforming nonrigid
object by comparing triplets of frames from an orthographic
video se...
Vincent Rabaud (University of California, San Dieg...
Recent research studied the problem of publishing microdata without revealing sensitive information, leading to the privacy preserving paradigms of k-anonymity and -diversity. k-a...
Gabriel Ghinita, Panagiotis Karras, Panos Kalnis, ...
Energy-based learning (EBL) is a general framework to describe supervised and unsupervised training methods for probabilistic and non-probabilistic factor graphs. An energy-based ...
In this paper, we present a novel statistical full-chip leakage power analysis method. The new method can provide a general framework to derive the full-chip leakage current or po...
Ruijing Shen, Ning Mi, Sheldon X.-D. Tan, Yici Cai...